How to Automate X Account Operations with a Codex Skill

Key takeaways

Build a Codex skill that runs the operating loop of one X account: pick today's slot from a logged content mix, draft in the right shape, reject weak hooks with a deterministic gate, and review performance from an X API pull or a manual export.

Have Codex build it for you. Paste this article into a Codex session and ask it to create the skill: "Read this article and build the x-growth-operator skill into this project, exactly as written." Every file is below in full, including the four scripts. Nothing in the skill posts, schedules, or writes to X on its own.

What you will finish with

One skill file, four Python scripts, and three small state files. Together they run the operating loop of a single X account: decide what goes out today, draft it in the shape that slot calls for, throw the draft out if the first line fails the gate, record what you published, then pull the numbers back and adjust.

This is built for one person running one account, or a small team running one brand account. The failure it prevents is not bad writing. It is drift. The content mix slides toward whatever is easy to write this week, hooks get written last and stay weak, and nobody opens the analytics until a month has passed and the pattern is set.

What you need before starting:

  • An agent session with write access to your project directory. Codex works; so does Claude Code or anything else that can create files and run Python.
  • The X account you intend to operate, and the standing to run it.
  • Python 3.8 or newer. All four scripts use the standard library only, so there is nothing to install.
  • About 30 minutes for the build and a first planning run.
  • For the review stage, one of two data paths: an X API key on a paid tier, or a manual export from X analytics. Neither is required to start. The loop works without them; you just cannot close the feedback half yet.

Done means: the skill directory exists, x-ops/ holds a filled-in brief and two empty tables, and mix_ledger.py plan returns a dated slot assignment that matches the brief.

Why the loop is the part worth automating

Writing is the easy half, and it is already the half models are good at. What decays is everything around it. A person can hold a ratio like "half of what I publish should be hands-on" in their head for about two weeks. After that the ratio quietly becomes "whatever I finished today."

The three things that actually break are all state problems:

The mix. You cannot tell whether you are off-ratio without a record of what you already published. Memory is not a record, and the failure is invisible from inside a single week.

The hook. The opening line is the sentence that decides whether anything else you wrote gets read, and it is the one most likely to be written last, when your attention is gone. Judging your own hook is unreliable in a specific way: you already know what the body says, so the gap feels closed to you even when it is wide open to a reader who has not read it yet.

The review. Numbers have to be pulled, matched to what you published, and read against the slot each post was assigned to. That is twenty minutes of bookkeeping per week, which is exactly the amount of work that never survives a busy week.

A chat session cannot hold any of this. A skill can, because a skill has files, and files can be counted by a script. The ledger is the memory, the gate is the discipline, and the review is a command you can run on a bad week.

The strategy layer, meaning what to publish and why a particular post shape earns a particular response, is a separate problem. The guide to growing blog traffic from an X account covers the distribution side in detail. This article is the execution layer: turning that judgment into something that runs.

Before you start

Three assumptions. Check them, because the skill is built on top of them.

You have one account and one brief. The skill is deliberately single-tenant. One x-ops/ directory describes one account. Running two accounts means two directories with two ledgers. Sharing a ledger across accounts destroys the only thing the ledger is for.

You are willing to write drafts and press publish yourself. The skill produces text and records. It never calls a write endpoint. Scripts make that easy to hold to: there is no publish function anywhere in the four files, so the boundary is checkable rather than a promise.

You can produce metrics in one of two shapes. Either you hold an X API key on a paid developer tier, or you can export your post-level analytics from X and map a few columns. Details are in the metrics section. If neither is true today, build the skill anyway and leave metrics.tsv empty until it is.

Install the skill

Six files, four of them scripts. Build this tree:

text
your-project/
├── .codex/
│   └── skills/
│       └── x-growth-operator/
│           ├── SKILL.md
│           ├── templates/
│           │   └── account-brief.yaml
│           └── scripts/
│               ├── mix_ledger.py
│               ├── hook_lint.py
│               ├── metrics.py
│               └── weekly_review.py
└── x-ops/
    ├── account-brief.yaml        ← you fill this in, once
    ├── mix-ledger.tsv            ← header row only
    ├── metrics.tsv               ← header row only
    └── scripts/                  ← copy of the skill's scripts/

The scripts live in two places on purpose. Keeping a copy inside the skill means the skill stays portable; keeping a copy under x-ops/ means the commands stay short and the whole working directory can be moved or archived in one piece. If you would rather not duplicate them, symlink x-ops/scripts to the skill's scripts/ and adjust the paths in the commands below.

Create the two tables as header-only files before anything else:

bash
printf 'date\tslot\tshape\ttarget_signal\thook_pattern\ttopic\tpost_url\n' > x-ops/mix-ledger.tsv
printf 'post_url\tcollected_at\timpressions\tlikes\treplies\treposts\tbookmarks\tprofile_clicks\n' > x-ops/metrics.tsv

Leave both with nothing but the header. The first planning run will complain if a header is wrong, which is a much better failure than discovering it twenty posts in.

The skill files

`SKILL.md` is what the agent reads. It holds the rules, the four-step loop, the failure table, and the reference tables that the drafting steps depend on. Keeping those tables inside the file the agent always reads is deliberate; a reference that lives in a separate document is a reference that gets skipped.

`templates/account-brief.yaml` is the only file you write by hand. Positioning, pillars, tone limits, the mix target, and the planning weights.

`scripts/mix_ledger.py` does the mix arithmetic. It reads the brief's mix_target block and the ledger, and answers one question: which slot is furthest behind in the trailing window.

`scripts/hook_lint.py` is the gate. Four mechanical checks on the first line of a draft, non-zero exit on any failure, so the agent can branch on it.

`scripts/metrics.py` ingests performance data by either path and normalizes both into the same table.

`scripts/weekly_review.py` joins the two tables, computes medians per slot, and names the four patterns worth acting on. It also enforces the 48-hour rule in code, which is the part people skip when they are impatient to see numbers.

SKILL.md

File map of the x-growth-operator skill: SKILL.md and account-brief.yaml on the skill side, with mix_ledger.py, hook_lint.py, metrics.py and weekly_review.py on the scripts side

Save as .codex/skills/x-growth-operator/SKILL.md.

markdown
---
name: x-growth-operator
description: Run the operating loop for one X account. Chooses today's content slot from a logged mix, drafts the post in the matching shape, rejects weak hooks with a deterministic gate, records what was published, and reviews performance from an X API pull or a manually imported metrics file. Use when the user asks to plan, draft, gate, or review posts for their own X account.
---

# X Growth Operator

One account per `x-ops/` directory. The state files are the memory; read them rather than working from recollection.

```text
x-ops/
├── account-brief.yaml    positioning, pillars, tone, mix target, signal weights
├── mix-ledger.tsv        one row per published post
├── metrics.tsv           one row per post per collection date
└── scripts/
    ├── mix_ledger.py     plan / log / report
    ├── hook_lint.py      the four-check hook gate
    ├── metrics.py        pull (X API) / import (your own export)
    └── weekly_review.py  join, medians, named patterns
```

## 0. Rules that never bend

1. Never post, schedule, or call any X write endpoint. Output is a draft block for the user to copy. Publishing is a human action.
2. Never state a metric that is not in `x-ops/metrics.tsv`. Missing data is reported as missing, never estimated.
3. Never recommend a slot without running `mix_ledger.py plan` first.
4. Never produce engagement pods, bulk follow or unfollow sequences, or the same text repeated across accounts. If asked, refuse and name the platform rule it violates.
5. Never draft a post whose only purpose is to trigger a reaction the content does not support.

## 1. First run

If `x-ops/account-brief.yaml` is missing or still the template, stop and build it with the user before anything else. Ask, do not infer. The `mix_target` block is required by `mix_ledger.py`; the rest guides your drafting.

Copy `scripts/` alongside the skill and create the two state files as header-only tables:

```bash
cp -r <skill-dir>/scripts x-ops/scripts
printf 'date\tslot\tshape\ttarget_signal\thook_pattern\ttopic\tpost_url
' > x-ops/mix-ledger.tsv
printf 'post_url\tcollected_at\timpressions\tlikes\treplies\treposts\tbookmarks\tprofile_clicks
' > x-ops/metrics.tsv
```

Then write `x-ops/account-brief.yaml` from `templates/account-brief.yaml` with the user, filling in every field.

## 2. The daily loop

Four steps, in order. Do not skip the gate because a draft looks good.

### 2.1 Plan

```bash
python3 x-ops/scripts/mix_ledger.py plan --window 20
```

This reads the trailing window, compares the counts per slot against `mix_target`, and prints the slot with the largest deficit plus the arithmetic behind the pick. Report its output. Do not substitute your own judgement about which slot would be more interesting.

When the window holds fewer than 20 rows, the script says so. Pass that warning on rather than hiding it.

### 2.2 Draft

Load the shape for the selected slot from §9 and write the post.

- Single post: hook, the core claim in one or two sentences, the evidence, exactly one call to action.
- Thread: see §3.
- The target signal drives the ending. A post aimed at bookmarks ends with something worth keeping. A post aimed at replies ends with something a reader can disagree with.

### 2.3 Hook gate

```bash
python3 x-ops/scripts/hook_lint.py --hook "<first line>" --body "<full post>"
```

The script runs four mechanical checks and exits non-zero on any failure:

1. Banned openers, meaning openers that would still be true of a different post.
2. Concreteness: the hook needs a number, a named thing, or a scene. Otherwise it is a thesis wearing a hook's clothing.
3. Gap width: a total claim with no figure or boundary is too wide to close.
4. Payoff: every number and name in the hook must appear in the body.

The gate is four questions, not an oracle. Checks 2 and 3 are heuristics and will occasionally reject a deliberately plain hook. When you disagree with a rejection, keep the hook and say why. When you agree, show the rejected line and the rewrite side by side; never present only the fixed version.

A gate that never rejects anything is not running. If ten consecutive drafts all pass, read §9's hook failure table with the user and add their own clichés to the `BANNED` list in `hook_lint.py`.

### 2.4 Log

After the user confirms they published, append the row:

```bash
python3 x-ops/scripts/mix_ledger.py log \
  --slot A --shape tutorial --signal bookmark \
  --hook-pattern information-gap --topic "short topic label" \
  --url "x.com/HANDLE/status/ID"
```

Ask before logging; do not assume publication. A row with no url is unverified and cannot be joined to metrics later.

## 3. Thread mode

Use a thread when the slot is A or B and the material genuinely needs steps. Do not use a thread to say one thing at length.

At a target of five slots:

| Slot | Job | Fails when |
| --- | --- | --- |
| 1 | Promise the outcome, not the topic | It describes the subject instead of the result |
| 2-4 | The two to four points that carry the argument | More than one idea per slot |
| 5-6 | Steps, checklist, or a worked case | It restates slot 1 instead of adding proof |
| Last | Summary plus one call to action | Two calls to action |

Five is a target. Three is fine when the material is thin; seven only if every slot does distinct work.

## 4. Reply engine

Replies carry the second-highest weight in the planning model, which makes writing one a distribution action rather than a courtesy. Run it as its own pass.

Build a target list from accounts the user follows inside their topic pillars, and for each produce a reply in one of four kinds:

1. Add a number the original post left out.
2. Offer a counterexample from the user's own work, without hostility.
3. Ask the follow-up question the post's own logic demands.
4. Describe what happened when the user tried it.

Reject bare praise, agreement with no addition, replies that are really an advertisement for the user's own post, and any reply that drags in an unrelated account for reach. Do not use the mention mechanism on people who have not asked for it.

## 5. The two metrics paths

Both write the same file. The review does not care which one produced a row.

### Path A, the X API

```bash
export X_BEARER_TOKEN="..."          # user-context OAuth 2.0 token
python3 x-ops/scripts/metrics.py pull --dry-run     # inspect the request first
python3 x-ops/scripts/metrics.py pull
```

The script reads post ids from the ledger, batches them 100 at a time, requests both the public and non-public metric groups, and writes only the counters that come back. Bookmark and impression counts require user-context authentication and are returned only for the authenticated account's own posts, which is exactly the scope this loop needs.

Field availability, tier names, prices, and rate limits on the X developer platform change often. Confirm the current ones against the developer documentation before building anything on top, and never answer a rate-limit rejection by guessing the numbers.

### Path B, manual import

```bash
python3 x-ops/scripts/metrics.py import --file export.csv
python3 x-ops/scripts/metrics.py import --file export.csv --map "url=Post link,impressions=Views"
```

The script recognizes common header names automatically and leaves anything it cannot map as an empty field. An empty field is honest and is reported as unavailable. A filled-in guess contaminates every review built on it afterward.

Never write a metrics row to test the review. Run the review against an empty table instead; it should say it has no data rather than produce a summary.

## 6. Weekly review

```bash
python3 x-ops/scripts/weekly_review.py --window 20
```

The script joins the ledger to the metrics on the post id, excludes rows collected inside the 48-hour window, reports medians per slot, and names the patterns it can prove:

- High impressions, low reposts: reached people, did not travel.
- High bookmarks, low impressions: worth keeping, under-distributed. Rewrite around a new angle; do not re-post it.
- Low replies across every slot: a shape problem, not a post problem.
- One slot outperforming the rest on reach: record it and keep the ratio.

Report what it prints, including the gap lists. When the data cannot support a claim, say so instead of summarizing around the hole.

## 7. Failure modes

| Symptom | Likely cause | Recovery |
| --- | --- | --- |
| Plan returns the same slot repeatedly | Window below 20 rows, or posts are not being logged | Confirm the log step runs. Say the window is thin instead of repeating a slot |
| Every draft passes the gate | The gate is being read, not applied | Add the user's own clichés to `BANNED` and re-run |
| Metrics fail to join | Post url formats differ between ledger and export | Normalize both to the numeric post id |
| Review dominated by one post | A mean crept in, or the window is too small | Medians are already used; widen the window and report the outlier |
| Mix drifts anyway | Posts are published outside the loop | Log them. Off-loop posts are still part of the mix |
| Drafts sound different each week | The brief has no banned list | Add specific banned moves, each with an example |

## 8. The 48-hour window

The planning model treats the first two days after publication as the period when a post can still be picked up. Two consequences.

Do not re-run a post from outside the window as though it were fresh. If it deserves reviving, rewrite it around a new angle and publish new material.

Do not judge a post before the window closes. `weekly_review.py` excludes the early rows automatically; do not override that by hand.

## 9. Reference tables

### The four account roles

Pick exactly one for the brief. Everything else assumes a single consistent position.

| Role | The account is | Publishes mostly |
| --- | --- | --- |
| Research translator | Reading primary sources and restating them clearly | Slot B |
| Engineering practitioner | Building things and reporting what broke | Slot A |
| Product and application advocate | Showing what a tool does in real use | Slots A and C |
| Industry observer | Tracking where the field is going and betting on it | Slots B and D |

### Content mix

| Slot | Share | What it is |
| --- | --- | --- |
| A | 50 | Hands-on tutorials, prompts, and worked skill or tool examples |
| B | 20 | Close reads of papers, releases, and trend shifts |
| C | 15 | Project progress and retrospectives |
| D | 10 | Industry opinion with a stated position |
| E | 5 | The flexible slot, for whatever the week hands you |

### The six shapes

| Shape | Opens with | Aimed at |
| --- | --- | --- |
| Discovery | A thing the reader did not know existed | Bookmark, profile click |
| Review | I tested this, here is the verdict | Reply, bookmark |
| Tutorial | Here is how to do the thing | Bookmark |
| Opinion | Here is what I think, and why | Reply |
| Retro | Here is what happened and what I learned | Reply, profile click |
| Announcement | Here is what shipped | Profile click, repost |

### Three hook tension sources

1. **Information gap.** Withhold one specific thing the reader needs, and make the edges of the gap visible. A gap the reader cannot see the shape of reads as vagueness.
2. **Scene resonance.** Open inside a situation the reader has been in. A scene earns the second sentence; an abstraction does not.
3. **Counterintuitive conflict.** State the thing that contradicts expectation, then earn it. Only usable when the body actually earns it.

### Four hooks that fail

| Failure | What it looks like | Fix |
| --- | --- | --- |
| Thesis in a hook's clothing | The main claim, stated flat, with no gap and no scene | Move the claim into the body. Open with the evidence that made you believe it |
| Template that outlived its edits | An opener that fits any post on any account | Delete the first line. Start with the second |
| Gap opened too wide | A total claim with no figure, boundary, or condition | Add the constraint. Say what it does not apply to |
| Gap the body never closes | A sharp hook followed by general advice | Cut the hook, or write the body the hook promised |

### Single post structure

Hook, then the core claim in one or two sentences, then the evidence, then one call to action. Two to three sentences total for the common case.

### The verified output block

Every draft leaves the loop in this shape:

```text
SLOT      A (deficit 2.0 over a 20-row window)
SHAPE     tutorial
SIGNAL    bookmark
HOOK      <the first line>
BODY      <the post>
CTA       <the one action>
GATE      check1 pass | check2 pass | check3 pass | check4 pass
```

If the GATE line is missing, the draft did not go through the gate. Run it again before showing the draft.

templates/account-brief.yaml

Save as .codex/skills/x-growth-operator/templates/account-brief.yaml, then copy it to x-ops/account-brief.yaml and fill it in. The mix_target block is read by the script; the rest guides drafting. Nothing else in the skill reads this file, so a field you leave blank is a field the agent will guess at.

yaml
# x-ops/account-brief.yaml
# Fill this in with the user before the first planning run. Every field here is
# read by the skill or by a script. Do not leave a field as a guess.

account:
  handle: ""
  positioning: ""        # exactly one of the four roles in SKILL.md section 9
  audience: ""           # who reads this, in one sentence
  language: ""           # the language post drafts are written in

pillars:                 # 2-4 topics this account is allowed to publish about
  - ""
  - ""

tone:
  allowed: []            # moves that fit this account
  banned: []             # words or moves it never uses, each with a reason

# Read by mix_ledger.py, which parses this block only. Must total 100.
mix_target:
  A: 50
  B: 20
  C: 15
  D: 10
  E: 5

# Planning weights, not measurements. These drive which signal a draft is aimed
# at, not how results are scored. The top three are the relative multipliers
# this skill was tuned around. The middle band is ordinal, meaning "more than a
# like, less than a bookmark", and the numbers are editable placeholders.
# Change any of them and say so in the review.
signal_weights:
  repost: 20
  reply: 13.5
  bookmark: 10
  profile_click: 8
  link_click: 7
  video_completion: 6
  dwell: 6
  like: 1

thread_length: 5         # target slots, usable range 3 to 7
window: 20               # the trailing post count every ratio is computed over

scripts/mix_ledger.py

The mix arithmetic. plan picks the slot, log records a published post, report shows actual against target. It reads only the mix_target block of the brief, so a malformed brief fails here first, which is the right place for it to fail.

python
#!/usr/bin/env python3
"""Content-mix ledger for the x-growth-operator skill.

One job: never let a slot be chosen from memory. The ledger is the record,
this script is the arithmetic.

Usage:
  mix_ledger.py plan   [--window 20] [--ops DIR]
  mix_ledger.py log    --slot A --shape tutorial --signal bookmark
                       --hook-pattern information-gap --topic "..."
                       [--url URL] [--date YYYY-MM-DD] [--ops DIR]
  mix_ledger.py report [--window 20] [--ops DIR]

Reads the mix target from x-ops/account-brief.yaml (the mix_target block only)
and the record from x-ops/mix-ledger.tsv.
"""

import argparse
import datetime as dt
import os
import re
import sys

HEADER = ["date", "slot", "shape", "target_signal", "hook_pattern", "topic", "post_url"]


def ops_dir(arg):
    return arg or os.environ.get("X_OPS_DIR") or "x-ops"


def read_target(brief_path):
    """Return {slot: share} from the mix_target block, or None if unreadable."""
    if not os.path.exists(brief_path):
        return None
    target = {}
    inside = False
    with open(brief_path, encoding="utf-8") as fh:
        for raw in fh:
            line = raw.rstrip("\n")
            if re.match(r"^mix_target\s*:", line):
                inside = True
                continue
            if inside:
                if line.strip() and not line.startswith((" ", "\t")):
                    break  # next top-level key
                m = re.match(r"^\s+([A-Za-z])\s*:\s*(\d+(?:\.\d+)?)\s*$", line)
                if m:
                    target[m.group(1).upper()] = float(m.group(2))
    return target or None


def read_rows(path):
    if not os.path.exists(path):
        return []
    rows = []
    with open(path, encoding="utf-8") as fh:
        for n, raw in enumerate(fh):
            line = raw.rstrip("\n")
            if not line.strip():
                continue
            parts = line.split("\t")
            if n == 0 and parts[0].strip().lower() == "date":
                continue  # header
            if parts[0].strip().lower() == "date":
                continue
            parts += [""] * (len(HEADER) - len(parts))
            rows.append(dict(zip(HEADER, parts)))
    return rows


def window_rows(rows, size):
    return rows[-size:] if size and size > 0 else rows


def deficits(rows, target):
    """Positive number means the slot is behind its share of the window."""
    n = len(rows)
    order = sorted(target.keys())
    counts = {s: 0 for s in order}
    for r in rows:
        s = (r["slot"] or "").strip().upper()
        if s in counts:
            counts[s] += 1
    total = sum(target.values()) or 100.0
    out = {}
    for s in order:
        share = target[s] / total
        out[s] = {
            "count": counts[s],
            "expected": share * n,
            "deficit": share * n - counts[s],
            "share_actual": (counts[s] / n * 100) if n else 0.0,
            "share_target": share * 100,
        }
    return out, counts, n


def last_seen(rows):
    seen = {}
    for i, r in enumerate(rows):
        s = (r["slot"] or "").strip().upper()
        if s:
            seen[s] = (r["date"], i)
    return seen


def cmd_plan(args):
    d = ops_dir(args.ops)
    ledger = os.path.join(d, "mix-ledger.tsv")
    target = read_target(os.path.join(d, "account-brief.yaml"))
    if not target:
        sys.exit("could not read a mix_target block from %s/account-brief.yaml" % d)

    rows = window_rows(read_rows(ledger), args.window)
    info, counts, n = deficits(rows, target)

    if n == 0:
        pick = sorted(target.keys())[0]
        print("window: empty, no rows logged yet")
        print("slot:   %s (default first slot; the ledger has nothing to count)" % pick)
        print("note:   below %d rows the deficit is noise. Publish and log anyway." % args.window)
        return 0

    thin = n < args.window
    seen = last_seen(rows)
    ranked = sorted(
        info.items(),
        key=lambda kv: (-kv[1]["deficit"], seen.get(kv[0], ("", -1))[1]),
    )
    pick, stats = ranked[0]

    print("window: last %d logged posts%s" % (n, " (THIN, fewer than %d)" % args.window if thin else ""))
    print()
    print("slot  count  expected  deficit  actual%   target%")
    for s, st in sorted(info.items()):
        print(
            "  %-4s %5d %9.1f %8.1f %7.1f%% %7.1f%%"
            % (s, st["count"], st["expected"], st["deficit"], st["share_actual"], st["share_target"])
        )
    print()
    print("slot:   %s" % pick)
    print("why:    deficit %.1f over a %d-row window%s" % (stats["deficit"], n, " (tie broken by least recent)" if len(ranked) > 1 and ranked[1][1]["deficit"] == stats["deficit"] else ""))
    if thin:
        print("warning: window below %d rows. Treat the pick as provisional." % args.window)
    return 0


def cmd_log(args):
    d = ops_dir(args.ops)
    os.makedirs(d, exist_ok=True)
    ledger = os.path.join(d, "mix-ledger.tsv")
    new = not os.path.exists(ledger)
    date = args.date or dt.date.today().isoformat()
    row = [date, args.slot.upper(), args.shape, args.signal, args.hook_pattern, args.topic, args.url or ""]
    if "\t" in "".join(row):
        sys.exit("fields may not contain tabs")
    with open(ledger, "a", encoding="utf-8") as fh:
        if new:
            fh.write("\t".join(HEADER) + "\n")
        fh.write("\t".join(row) + "\n")
    print("logged: %s" % "\t".join(row))
    if not args.url:
        print("note:   post_url is empty, so this row is unverified and cannot be joined to metrics")
    return 0


def cmd_report(args):
    d = ops_dir(args.ops)
    target = read_target(os.path.join(d, "account-brief.yaml"))
    if not target:
        sys.exit("could not read a mix_target block from %s/account-brief.yaml" % d)
    rows = window_rows(read_rows(os.path.join(d, "mix-ledger.tsv")), args.window)
    info, counts, n = deficits(rows, target)
    if n == 0:
        print("no rows in the window; nothing to report")
        return 0
    print("%d rows in window" % n)
    print()
    print("slot  count  expected  delta   actual%   target%   status")
    for s, st in sorted(info.items()):
        status = "ok"
        if st["deficit"] > 1.5:
            status = "BEHIND"
        elif st["deficit"] < -1.5:
            status = "over"
        print(
            "  %-4s %5d %9.1f %+7.1f %7.1f%% %7.1f%%  %s"
            % (s, st["count"], st["expected"], st["deficit"], st["share_actual"], st["share_target"], status)
        )
    return 0


def main():
    ap = argparse.ArgumentParser(description="x-growth-operator content-mix ledger")
    sub = ap.add_subparsers(dest="cmd", required=True)

    p = sub.add_parser("plan", help="pick today's slot from the trailing window")
    p.add_argument("--window", type=int, default=20)
    p.add_argument("--ops")
    p.set_defaults(func=cmd_plan)

    p = sub.add_parser("log", help="append a published post to the ledger")
    p.add_argument("--slot", required=True)
    p.add_argument("--shape", required=True)
    p.add_argument("--signal", required=True, help="the signal this post targets")
    p.add_argument("--hook-pattern", required=True, dest="hook_pattern")
    p.add_argument("--topic", required=True)
    p.add_argument("--url", default="")
    p.add_argument("--date")
    p.add_argument("--ops")
    p.set_defaults(func=cmd_log)

    p = sub.add_parser("report", help="actual mix vs target")
    p.add_argument("--window", type=int, default=20)
    p.add_argument("--ops")
    p.set_defaults(func=cmd_report)

    args = ap.parse_args()
    return args.func(args)


if __name__ == "__main__":
    sys.exit(main())

scripts/hook_lint.py

The gate. Four checks, non-zero exit on failure, so an agent can branch on the exit code instead of interpreting prose. The BANNED list is the part you are meant to edit; seventeen openers ship with it and it should grow with your own feed's clichés.

python
#!/usr/bin/env python3
"""Deterministic hook gate for the x-growth-operator skill.

Four checks on the first line of a draft, all mechanical. Exits 1 if any
check fails so a caller can branch on the exit code.

Usage:
  hook_lint.py --hook "..." --body "..."
  hook_lint.py --hook "..." --body-file post.txt
  hook_lint.py --card x-ops/post-card.md          # reads HOOK/BODY blocks

Checks
  1 banned openers      - openers that fit any post on any account
  2 concreteness        - needs a number, a name, or a scene
  3 gap width           - total claims with no figure or boundary
  4 payoff              - every number and name in the hook appears in the body

Check 2 and 3 are heuristics that catch the two most common failure shapes.
They produce false positives on deliberately plain hooks. When you disagree
with a rejection, keep the hook and say why; the gate is four questions, not
an oracle.
"""

import argparse
import re
import sys

BANNED = [
    r"^in today'?s\b",
    r"^let'?s dive in\b",
    r"^let'?s talk about\b",
    r"^we'?re excited to\b",
    r"^excited to announce\b",
    r"^here'?s why\b",
    r"^here are \d+ (things|ways|tips|reasons)\b",
    r"^a thread\b",
    r"^thread\b",
    r"^hot take\b",
    r"^unpopular opinion\b",
    r"^game[- ]?chang(er|ing)\b",
    r"^the future of \w+ is\b",
    r"^\w+ is (dead|dying)\b",
    r"^stop doing\b",
    r"^nobody talks about\b",
    r"^most people (get|don'?t)\b",
]

# Words that signal a total claim the body probably cannot pay off.
WIDE = [
    "everything", "everyone", "nobody", "always", "never", "all of",
    "the only", "completely", "totally", "100%", "forever", "instantly",
]

SCENE_MARKERS = [
    r"\bi\b", r"\bwe\b", r"\bmy\b", r"\bour\b", r"\byesterday\b",
    r"\blast (week|month|night)\b", r"\bthis (morning|week|month)\b",
    r"\bwhen i\b", r"\bafter \d", r"\bthree (weeks|months|days)\b",
]

# Capitalised words that are not proper nouns.
STOP_CAPS = {
    "The", "This", "That", "These", "Those", "It", "We", "I", "You", "They",
    "He", "She", "A", "An", "And", "But", "Or", "So", "If", "When", "Why",
    "How", "What", "Every", "Most", "Some", "No", "Not", "Do", "Does", "Did",
    "My", "Our", "Your", "Their", "Its", "There", "Here", "Stop", "Start",
    "Never", "Always", "Just", "Only", "One", "Two", "Three", "In", "On",
    "At", "After", "Before", "Because", "Then", "Now", "Today", "Yesterday",
    "Everything", "Nothing", "Everyone", "Nobody", "Anything", "Something",
    "Anyone", "Someone", "Everywhere", "Nothing's", "Its",
}

CAP = re.compile(r"\b[A-Z][A-Za-z0-9.+#-]{1,}\b")
SENT_SPLIT = re.compile(r"(?<=[.!?])\s+")


def proper_nouns(text):
    """Capitalised words that are not the first token of a sentence.

    Sentence-initial capitals carry no signal, which is the whole reason this
    is not a one-line regex.
    """
    found = []
    for sentence in SENT_SPLIT.split(text.strip()):
        tokens = sentence.split()
        for tok in tokens[1:]:
            for word in CAP.findall(tok):
                if word not in STOP_CAPS:
                    found.append(word)
    return found


def first_line(hook):
    return hook.strip().splitlines()[0].strip() if hook.strip() else ""


def check_banned(hook):
    low = hook.lower()
    for pat in BANNED:
        if re.search(pat, low):
            return False, "banned opener matching /%s/" % pat
    return True, "no banned opener"


def check_concrete(hook):
    digits = re.findall(r"\d", hook)
    caps = proper_nouns(hook)
    scene = [p for p in SCENE_MARKERS if re.search(p, hook, re.I)]
    if digits:
        return True, "carries a number"
    if caps:
        return True, "names %s" % ", ".join(sorted(set(caps))[:3])
    if scene:
        return True, "opens inside a scene"
    return False, "no number, no name, no scene. This reads as a thesis, not a hook"


def check_width(hook):
    low = hook.lower()
    hits = [w for w in WIDE if re.search(r"\b%s\b" % re.escape(w), low)]
    has_number = bool(re.search(r"\d", hook))
    if hits and not has_number:
        return False, "total claim (%s) with no figure or boundary to close it" % ", ".join(hits)
    if hits:
        return True, "total claim present but bounded by a figure"
    return True, "gap width not obviously too wide"


def check_payoff(hook, body):
    tokens = set(re.findall(r"\d+(?:[.,]\d+)?", hook))
    tokens |= set(proper_nouns(hook))
    missing = sorted(t for t in tokens if t not in body)
    if missing:
        return False, "the body never mentions %s" % ", ".join(missing)
    return True, "every number and name in the hook appears in the body"


def run(hook, body):
    line = first_line(hook)
    if not line:
        print("FAIL  the hook is empty")
        return 1
    results = [
        ("1 banned openers", check_banned(line)),
        ("2 concreteness  ", check_concrete(line)),
        ("3 gap width     ", check_width(line)),
        ("4 payoff        ", check_payoff(line, body or "")),
    ]
    print("hook: %s" % line)
    print("chars: %d" % len(line))
    print()
    failed = 0
    for name, (ok, why) in results:
        print("%s  %s  %s" % ("pass" if ok else "FAIL", name, why))
        if not ok:
            failed += 1
    print()
    if failed:
        print("gate: REJECTED on %d check(s). Rewrite the hook, do not soften the body." % failed)
        return 1
    print("gate: passed")
    return 0


def read_card(path):
    text = open(path, encoding="utf-8").read()
    hook = body = ""
    m = re.search(r"^HOOK[ \t]*(.*)$", text, re.M)
    if m:
        hook = m.group(1).strip()
    m = re.search(r"^BODY[ \t]*(.*?)(?=^\w+[ \t]|\Z)", text, re.M | re.S)
    if m:
        body = m.group(1).strip()
    return hook, body


def main():
    ap = argparse.ArgumentParser(description="x-growth-operator hook gate")
    ap.add_argument("--hook")
    ap.add_argument("--body", default="")
    ap.add_argument("--body-file")
    ap.add_argument("--card")
    args = ap.parse_args()

    hook, body = args.hook, args.body
    if args.card:
        hook, body = read_card(args.card)
    if args.body_file:
        body = open(args.body_file, encoding="utf-8").read()
    if not hook:
        sys.exit("no hook supplied; pass --hook or --card")
    return run(hook, body)


if __name__ == "__main__":
    sys.exit(main())

scripts/metrics.py

Both data paths, one output table. pull talks to the X API, import reads your own export, and neither one guesses a number it did not receive.

python
#!/usr/bin/env python3
"""Metrics ingestion for the x-growth-operator skill.

Two paths, one output file. The review does not care which path produced a row.

  metrics.py pull    read post ids from the ledger, ask the X API, append rows
  metrics.py import  read your own CSV/TSV, map columns, append rows

Both append to x-ops/metrics.tsv:
  post_url  collected_at  impressions  likes  replies  reposts  bookmarks  profile_clicks

An absent counter is written as an empty field and reported as unavailable.
Nothing is ever estimated.

Path A needs a user-context OAuth 2.0 token in $X_BEARER_TOKEN, and an access
tier that permits reading. Field availability differs by tier and auth method,
so this script requests both the public and non-public metric groups and fills
only the counters that come back. Confirm the current tier, fields, and rate
limits against X's developer documentation before relying on them.
"""

import argparse
import csv
import datetime as dt
import json
import os
import re
import sys
import time
import urllib.error
import urllib.parse
import urllib.request

HEADER = ["post_url", "collected_at", "impressions", "likes", "replies", "reposts", "bookmarks", "profile_clicks"]

API = "https://api.x.com/2/tweets"
BATCH = 100

# API field group -> our column
FIELD_MAP = {
    "impression_count": "impressions",
    "like_count": "likes",
    "reply_count": "replies",
    "retweet_count": "reposts",
    "bookmark_count": "bookmarks",
    "user_profile_clicks": "profile_clicks",
}

# Accepted header names per column, for the manual path.
ALIASES = {
    "post_url": ["post_url", "url", "post url", "link", "permalink", "tweet url", "post link"],
    "collected_at": ["collected_at", "date", "collected", "export date"],
    "impressions": ["impressions", "impression_count", "impressions total", "views"],
    "likes": ["likes", "like_count", "favorites", "likes total"],
    "replies": ["replies", "reply_count", "replies total"],
    "reposts": ["reposts", "retweets", "retweet_count", "reposts total"],
    "bookmarks": ["bookmarks", "bookmark_count", "bookmarks total"],
    "profile_clicks": ["profile_clicks", "user_profile_clicks", "profile clicks", "profile visits"],
}


def ops_dir(arg):
    return arg or os.environ.get("X_OPS_DIR") or "x-ops"


def append_rows(path, rows):
    new = not os.path.exists(path)
    with open(path, "a", encoding="utf-8", newline="") as fh:
        w = csv.writer(fh, delimiter="\t")
        if new:
            w.writerow(HEADER)
        for r in rows:
            w.writerow([r.get(c, "") for c in HEADER])


def post_ids_from_ledger(path):
    ids, order = [], []
    if not os.path.exists(path):
        sys.exit("no ledger at %s" % path)
    with open(path, encoding="utf-8") as fh:
        for raw in fh:
            parts = raw.rstrip("\n").split("\t")
            if len(parts) < 7 or parts[0].strip().lower() == "date":
                continue
            url = parts[6].strip()
            if not url or url.startswith("<"):
                continue
            m = re.search(r"/status(?:es)?/(\d+)", url) or re.fullmatch(r"(\d+)", url)
            if m:
                ids.append(m.group(1))
                order.append(url)
    return ids, order


def api_get(url, token, timeout=30):
    req = urllib.request.Request(url, headers={
        "Authorization": "Bearer %s" % token,
        "User-Agent": "x-growth-operator metrics.py",
    })
    with urllib.request.urlopen(req, timeout=timeout) as resp:
        return json.loads(resp.read().decode("utf-8"))


def cmd_pull(args):
    d = ops_dir(args.ops)
    ids, order = post_ids_from_ledger(os.path.join(d, "mix-ledger.tsv"))
    if not ids:
        print("no post ids in the ledger. Log a published post with --url first.")
        return 0

    collected = args.collected or dt.date.today().isoformat()
    fields = "public_metrics,non_public_metrics,created_at"
    batches = [ids[i:i + BATCH] for i in range(0, len(ids), BATCH)]

    if args.dry_run:
        for b in batches:
            print("%s?ids=%s&tweet.fields=%s" % (API, ",".join(b), fields))
        print("\n%d ids in %d request(s). Token read from $X_BEARER_TOKEN." % (len(ids), len(batches)))
        return 0

    token = os.environ.get("X_BEARER_TOKEN")
    if not token:
        sys.exit("$X_BEARER_TOKEN is not set. Export a user-context OAuth 2.0 token, or use the import path.")

    rows, missing = [], []
    for b in batches:
        q = urllib.parse.urlencode({"ids": ",".join(b), "tweet.fields": fields})
        url = "%s?%s" % (API, q)
        for attempt in range(4):
            try:
                payload = api_get(url, token)
                break
            except urllib.error.HTTPError as e:
                if e.code == 429 and attempt < 3:
                    wait = int(e.headers.get("x-rate-limit-reset", "0"))
                    delay = max(5, min(60, wait - int(time.time()))) if wait else 15
                    print("rate limited, waiting %ds" % delay, file=sys.stderr)
                    time.sleep(delay)
                    continue
                print("HTTP %s on batch starting %s: %s" % (e.code, b[0], e.read()[:200].decode("utf-8", "replace")), file=sys.stderr)
                payload = None
                break
            except Exception as e:
                print("request failed: %s" % e, file=sys.stderr)
                payload = None
                break
        if not payload:
            missing.extend(b)
            continue

        seen = set()
        for item in payload.get("data") or []:
            seen.add(item.get("id"))
            values = {"post_url": "x.com/i/status/%s" % item["id"], "collected_at": collected}
            groups = [item.get("public_metrics") or {}, item.get("non_public_metrics") or {}]
            for src_col, dest in FIELD_MAP.items():
                for g in groups:
                    if src_col in g:
                        values[dest] = g[src_col]
                        break
            # keep the original url when we can match it back
            for u in order:
                if u.endswith(str(item.get("id"))):
                    values["post_url"] = u
                    break
            rows.append(values)

        if payload.get("errors"):
            for err in payload["errors"]:
                rid = (err.get("value") or err.get("resource_id") or "?")
                missing.append(str(rid))
        missing.extend([i for i in b if i not in seen and i not in missing])

    if rows:
        append_rows(os.path.join(d, "metrics.tsv"), rows)
    print("appended %d row(s) for %s" % (len(rows), collected))
    if missing:
        print("no data returned for %d id(s): %s" % (len(set(missing)), ", ".join(sorted(set(missing))[:8])))
    if not rows:
        print("nothing written. Check that the token is user-context and the tier allows reads.")
    return 0


def detect_delim(sample):
    return "\t" if sample.count("\t") > sample.count(",") else ","


def cmd_import(args):
    d = ops_dir(args.ops)
    path = args.file
    if path == "-":
        sample = sys.stdin.read()
        fh = sample.splitlines()
    else:
        with open(path, encoding="utf-8") as f:
            sample = f.read()
        fh = sample.splitlines()
    if not fh:
        sys.exit("empty input")

    delim = detect_delim(sample[:4000])
    reader = csv.DictReader(fh, delimiter=delim)
    headers = reader.fieldnames or []

    mapping = {}
    explicit = {}
    if args.map:
        for pair in args.map.split(","):
            if "=" in pair:
                k, v = pair.split("=", 1)
                explicit[k.strip().lower()] = v.strip()

    for col in HEADER:
        if col in explicit:
            src = explicit[col]
            if src and src not in headers:
                sys.exit("--map points %s at %r, which is not in the file. Headers: %s" % (col, src, headers))
            mapping[col] = src
            continue
        lower = {h.lower().strip(): h for h in headers}
        for alias in ALIASES[col]:
            if alias in lower:
                mapping[col] = lower[alias]
                break
        else:
            mapping[col] = None

    unmapped = [c for c in HEADER if not mapping.get(c) and c != "collected_at"]
    if unmapped:
        print("unmapped columns, will be left empty: %s" % ", ".join(unmapped))
        print("use --map \"%s=<your header>\" to fill them" % unmapped[0])

    collected = args.collected or dt.date.today().isoformat()
    rows, blanks = [], {c: 0 for c in HEADER}
    for rec in reader:
        row = {}
        for col in HEADER:
            src = mapping.get(col)
            val = ""
            if src:
                val = (rec.get(src) or "").strip()
            if col == "collected_at" and not val:
                val = collected
            if col == "post_url" and re.fullmatch(r"\d+", val or ""):
                # a bare post id becomes a url; anything else is left alone
                val = "x.com/i/status/%s" % val
            if not val and col != "post_url":
                blanks[col] += 1
            row[col] = val
        if row["post_url"]:
            rows.append(row)

    if not rows:
        sys.exit("no usable rows: every row was missing a post url")

    append_rows(os.path.join(d, "metrics.tsv"), rows)
    print("appended %d row(s) for %s" % (len(rows), collected))
    thin = [c for c, n in blanks.items() if n == len(rows) and c != "post_url"]
    if thin:
        print("always empty, reported as unavailable rather than zero: %s" % ", ".join(thin))
    return 0


def main():
    ap = argparse.ArgumentParser(description="x-growth-operator metrics ingestion")
    sub = ap.add_subparsers(dest="cmd", required=True)

    p = sub.add_parser("pull", help="path A: pull from the X API")
    p.add_argument("--collected")
    p.add_argument("--ops")
    p.add_argument("--dry-run", action="store_true", dest="dry_run")
    p.set_defaults(func=cmd_pull)

    p = sub.add_parser("import", help="path B: import your own export")
    p.add_argument("--file", required=True, help="CSV/TSV path, or - for stdin")
    p.add_argument("--map", help='override column mapping, e.g. "url=Post link,impressions=Views"')
    p.add_argument("--collected")
    p.add_argument("--ops")
    p.set_defaults(func=cmd_import)

    args = ap.parse_args()
    return args.func(args)


if __name__ == "__main__":
    sys.exit(main())

scripts/weekly_review.py

The review. Joins the two tables on the post id, enforces the 48-hour exclusion in code, reports medians rather than means, and names only the patterns it can prove from the rows it has.

python
#!/usr/bin/env python3
"""Weekly review for the x-growth-operator skill.

Joins the ledger to the metrics, reports per slot letter, and names the four
patterns worth acting on. Medians, not means: one good post should not define
a whole slot.

Rows collected inside the 48-hour window are excluded by default, because a
post at hour six has not finished.

Usage:
  weekly_review.py [--window 20] [--exclude-hours 48] [--min-posts 3] [--ops DIR]
"""

import argparse
import csv
import datetime as dt
import os
import statistics as st
import sys

COUNTERS = ["impressions", "likes", "replies", "reposts", "bookmarks", "profile_clicks"]
LEDGER_HEADER = ["date", "slot", "shape", "target_signal", "hook_pattern", "topic", "post_url"]


def ops_dir(arg):
    return arg or os.environ.get("X_OPS_DIR") or "x-ops"


def read_tsv(path, header):
    if not os.path.exists(path):
        return []
    rows = []
    with open(path, encoding="utf-8") as fh:
        rdr = csv.reader(fh, delimiter="\t")
        for i, parts in enumerate(rdr):
            if not parts or not any(p.strip() for p in parts):
                continue
            if i == 0 and parts[0].strip().lower() in ("date", "post_url"):
                continue
            if parts[0].strip().lower() in ("date", "post_url"):
                continue
            parts = parts + [""] * (len(header) - len(parts))
            rows.append(dict(zip(header, parts)))
    return rows


def key(url):
    """Normalise a post url to a bare id so the two files can be joined."""
    url = (url or "").strip().split("?")[0].rstrip("/")
    return url.rsplit("/", 1)[-1].lower() if url else ""


def parse_date(s):
    s = (s or "").strip()
    for fmt in ("%Y-%m-%d", "%Y/%m/%d", "%m/%d/%Y", "%d/%m/%Y"):
        try:
            return dt.datetime.strptime(s, fmt).date()
        except ValueError:
            continue
    return None


def to_num(v):
    v = (v or "").strip().replace(",", "").replace("%", "")
    if not v:
        return None
    try:
        return float(v)
    except ValueError:
        return None


def main():
    ap = argparse.ArgumentParser(description="x-growth-operator weekly review")
    ap.add_argument("--window", type=int, default=20)
    ap.add_argument("--exclude-hours", type=int, default=48, dest="exclude_hours")
    ap.add_argument("--min-posts", type=int, default=3, dest="min_posts",
                    help="minimum posts in a slot before its median is reported")
    ap.add_argument("--ops")
    args = ap.parse_args()

    d = ops_dir(args.ops)
    ledger = read_tsv(os.path.join(d, "mix-ledger.tsv"), LEDGER_HEADER)
    metrics = read_tsv(os.path.join(d, "metrics.tsv"), ["post_url", "collected_at"] + COUNTERS)

    if not ledger:
        print("no ledger rows. Nothing to review.")
        return 0

    ledger = ledger[-args.window:] if args.window > 0 else ledger
    by_id = {}
    for r in metrics:
        k = key(r["post_url"])
        if not k:
            continue
        by_id.setdefault(k, []).append(r)

    joined, no_metrics, early = [], [], 0
    for r in ledger:
        k = key(r["post_url"])
        if not k:
            no_metrics.append(r)
            continue
        candidates = by_id.get(k)
        if not candidates:
            no_metrics.append(r)
            continue
        pub = parse_date(r["date"])
        usable = []
        for c in candidates:
            cd = parse_date(c["collected_at"])
            if pub and cd and (cd - pub).days * 24 < args.exclude_hours:
                early += 1
                continue
            usable.append(c)
        if not usable:
            no_metrics.append(r)
            continue
        latest = max(usable, key=lambda c: parse_date(c["collected_at"]) or dt.date.min)
        joined.append((r, latest))

    orphans = [r for r in metrics if key(r["post_url"]) not in {key(l["post_url"]) for l in ledger}]

    print("# Weekly review")
    print()
    print("%d ledger rows in window, %d joined to metrics, %d without usable metrics."
          % (len(ledger), len(joined), len(no_metrics)))
    if early:
        print("%d metrics row(s) excluded for being inside the %dh window."
              % (early, args.exclude_hours))
    print()

    if not joined:
        print("No joinable data. The review cannot say anything yet, and it will not guess.")
        if no_metrics:
            no_url = [r for r in no_metrics if not (r.get("post_url") or "").strip()]
            waiting = [r for r in no_metrics if (r.get("post_url") or "").strip()]
            print()
            if no_url:
                print("Ledger rows with no url (%d). These can never join:" % len(no_url))
                for r in no_url[:10]:
                    print("  %s  %s  %s" % (r["date"], r["slot"], r["topic"] or "(no topic)"))
            if waiting:
                print("Rows whose metrics are missing or still inside the %dh window (%d):"
                      % (args.exclude_hours, len(waiting)))
                for r in waiting[:10]:
                    print("  %s  %s  %s" % (r["date"], r["slot"], r["topic"] or "(no topic)"))
                print("Ingest again once the window closes. Lowering --exclude-hours to see numbers early is the failure this rule exists to prevent.")
        return 0

    slots = {}
    for l, m in joined:
        slots.setdefault((l["slot"] or "?").upper(), []).append((l, m))

    print("## By slot")
    print()
    print("slot  n  " + "  ".join("%s" % c.rjust(14) for c in COUNTERS))
    for s in sorted(slots):
        items = slots[s]
        cells = []
        for c in COUNTERS:
            vals = [to_num(m.get(c)) for _, m in items]
            vals = [v for v in vals if v is not None]
            if len(vals) < args.min_posts:
                cells.append("n/a".rjust(14))
            else:
                cells.append(("%.0f" % st.median(vals)).rjust(14))
        print("%-5s %d  %s" % (s, len(items), "  ".join(cells)))
    print()
    print("n/a means fewer than %d posts with that counter. It does not mean zero." % args.min_posts)
    print()

    print("## Patterns")
    print()
    flags = 0
    allr = [(l, m) for l, m in joined]
    imp = [(l, to_num(m.get("impressions"))) for l, m in allr if to_num(m.get("impressions")) is not None]
    if len(imp) >= args.min_posts:
        med_imp = st.median([v for _, v in imp])
        rep = [(l, to_num(m.get("reposts"))) for l, m in allr if to_num(m.get("reposts")) is not None]
        bkm = [(l, to_num(m.get("bookmarks"))) for l, m in allr if to_num(m.get("bookmarks")) is not None]
        if rep:
            med_rep = st.median([v for _, v in rep])
            hits = []
            for l, m in allr:
                i, rp = to_num(m.get("impressions")), to_num(m.get("reposts"))
                if i is not None and rp is not None and i > med_imp * 1.3 and rp <= med_rep:
                    hits.append(l)
            if hits:
                flags += 1
                print("**High impressions, low reposts** on %d post(s): reached people, did not travel." % len(hits))
                for l in hits[:5]:
                    print("  %s  %s  %s" % (l["date"], l["slot"], l["topic"]))
                print()
        if bkm:
            med_bk = st.median([v for _, v in bkm])
            hits = []
            for l, m in allr:
                i, bk = to_num(m.get("impressions")), to_num(m.get("bookmarks"))
                if i is not None and bk is not None and bk > med_bk * 1.3 and i <= med_imp:
                    hits.append(l)
            if hits:
                flags += 1
                print("**High bookmarks, low impressions** on %d post(s): worth keeping, nobody saw it." % len(hits))
                print("  Rewrite around a new angle rather than re-posting it.")
                for l in hits[:5]:
                    print("  %s  %s  %s" % (l["date"], l["slot"], l["topic"]))
                print()

    reps = [to_num(m.get("replies")) for _, m in allr]
    reps = [v for v in reps if v is not None]
    if reps:
        med_r = st.median(reps)
        per_slot = {}
        for s, items in slots.items():
            vals = [to_num(m.get("replies")) for _, m in items]
            vals = [v for v in vals if v is not None]
            if vals:
                per_slot[s] = st.median(vals)
        if per_slot and all(v <= med_r for v in per_slot.values()) and med_r < 3:
            flags += 1
            print("**Low replies across every slot** (median %.1f). The account is not inviting" % med_r)
            print("  disagreement anywhere. That is a shape problem, not a post problem.")
            print()

    if len(slots) >= 2:
        med_by_slot = {}
        for s, items in slots.items():
            vals = [to_num(m.get("impressions")) for _, m in items]
            vals = [v for v in vals if v is not None]
            if len(vals) >= args.min_posts:
                med_by_slot[s] = st.median(vals)
        if len(med_by_slot) >= 2 and max(med_by_slot.values()) > 1.6 * min(med_by_slot.values()):
            flags += 1
            best = max(med_by_slot, key=med_by_slot.get)
            print("**One slot outperforming the rest**: %s at %.0f median impressions vs %.0f for %s."
                  % (best, med_by_slot[best], min(med_by_slot.values()), min(med_by_slot, key=med_by_slot.get)))
            print("  Record it and keep the ratio. Reach is not the assignment. Change the brief")
            print("  only if the gap holds across two full windows.")
            print()

    if not flags:
        print("No patterns above threshold this window. That is a valid result, not a bug.")
        print()

    print("## Gaps")
    print()
    if no_metrics:
        print("- %d ledger row(s) with no usable metrics." % len(no_metrics))
        for r in no_metrics[:5]:
            print("    %s  %s  %s" % (r["date"], r["slot"], r["topic"] or "(no topic)"))
    if orphans:
        print("- %d metrics row(s) with no ledger entry. Publish outside the loop still counts." % len(orphans))
        for r in orphans[:5]:
            print("    %s  %s" % (r["collected_at"], r["post_url"]))
    if not no_metrics and not orphans:
        print("- none. Every row joined in both directions.")
    print()
    print("Every number above traces to a row in x-ops/metrics.tsv.")
    return 0


if __name__ == "__main__":
    sys.exit(main())

Running the minimum loop

Four commands, in order, one post at a time. This is what a working run looks like.

Plan. Ask for the slot. The script counts the trailing window and prints the arithmetic, not a vibe.

text
$ python3 x-ops/scripts/mix_ledger.py plan --window 20
window: last 20 logged posts

slot  count  expected  deficit  actual%   target%
  A       14      10.0     -4.0    70.0%    50.0%
  B        4       4.0      0.0    20.0%    20.0%
  C        1       3.0      2.0     5.0%    15.0%
  D        1       2.0      1.0     5.0%    10.0%
  E        0       1.0      1.0     0.0%     5.0%

slot:   C
why:    deficit 2.0 over a 20-row window

Check: the deficit is arithmetic you can verify by counting the ledger yourself. Slot C is two posts short of its fifteen percent share, and hands-on tutorials are four posts over theirs, which is the drift this whole loop exists to catch.

If it goes wrong: the most common cause is a ledger with five rows in it. The window is thin and the pick will swing. The script says so rather than pretending. It settles around twenty rows.

Draft. Write the post in the shape the slot calls for. A tutorial for slot A, a close read for B, a retro for C.

Check: you can point to the hook, the claim, the evidence, and the action as four separate pieces. If you cannot find the evidence, the post is an opinion wearing a tutorial's clothes.

If it goes wrong: the shape is right and the content is thin. Go back with the specific thing you wanted to say. The skill will not invent your expertise, and asking it to is how you end up publishing something that sounds like everyone else.

Gate. Run the first line through the linter before anything else happens to it.

text
$ python3 x-ops/scripts/hook_lint.py \
    --hook "In today's fast-paced AI landscape, building an audience is everything." \
    --body "Some general advice about posting."
hook: In today's fast-paced AI landscape, building an audience is everything.
chars: 71

FAIL  1 banned openers  banned opener matching /^in today'?s\b/
pass  2 concreteness    names AI
FAIL  3 gap width       total claim (everything) with no figure or boundary to close it
FAIL  4 payoff          the body never mentions AI

gate: REJECTED on 3 check(s). Rewrite the hook, do not soften the body.

That hook fails three ways at once, which is worth noticing. The opener is a template, the claim is total, and the body never mentions the one named thing the hook promised. A human reader would feel all three without naming any of them.

Here is the same gate on a line that passes:

text
$ python3 x-ops/scripts/hook_lint.py \
    --hook "I ran 40 posts through the same gate. 31 failed on one check." \
    --body "I ran 40 posts through the same gate last month. 31 failed on one check: the body never paid off the hook."
hook: I ran 40 posts through the same gate. 31 failed on one check.
chars: 61

pass  1 banned openers  no banned opener
pass  2 concreteness    carries a number
pass  3 gap width       gap width not obviously too wide
pass  4 payoff          every number and name in the hook appears in the body

gate: passed

Check: count how often the gate rejects. If it has never rejected anything across ten drafts, your BANNED list is too short. Open hook_lint.py and add the openers you keep seeing in your own feed. The list ships with seventeen and grows with use.

If it goes wrong: the rewrite is worse than the original. Keep the original and fix the specific check that failed. The gate is four yes-or-no questions, not a rewrite service.

Log. After you publish, record the row.

bash
python3 x-ops/scripts/mix_ledger.py log \
  --slot C --shape retro --signal reply \
  --hook-pattern scene --topic "gate rejection rate" \
  --url "x.com/yourhandle/status/1234567890"

Check: the ledger row count matches what you actually published. Count them.

If it goes wrong: you published something outside the loop. Log it anyway. An off-loop post still counts toward the mix, and a ledger that only records the posts you are proud of will lie to you at review time.

That is the whole minimum loop. It closes the planning and quality half. The feedback half needs numbers.

Closing the feedback half

Two paths, and the choice is a real trade rather than a preference.

Path A pulls from the X API. The script reads post ids out of the ledger, batches them a hundred at a time, requests both the public and non-public metric groups, and writes only the counters that come back.

bash
export X_BEARER_TOKEN="your user-context OAuth 2.0 token"
python3 x-ops/scripts/metrics.py pull --dry-run   # prints the request, calls nothing
python3 x-ops/scripts/metrics.py pull

Reading bookmark and impression counts requires user-context authentication and returns values only for the authenticated account's own posts, which happens to be exactly the scope this loop needs. If the token is missing the script exits with a message instead of failing halfway; if the tier does not permit a field, the field comes back absent and the row records it as empty.

Tier names, prices, available fields, and rate limits on the X developer platform change often enough that you should confirm the current ones against the documentation before building anything on top. The script handles a 429 by backing off and retrying, and it never fills a rate-limited gap with a guess.

Path B imports your own export. Ten minutes a week, zero dependencies, and no reason to feel like a temporary solution.

bash
python3 x-ops/scripts/metrics.py import --file export.csv
python3 x-ops/scripts/metrics.py import --file export.csv --map "url=Post link,impressions=Views"

The script recognizes common header names on its own and tells you which columns it could not map, so the first import doubles as a check on your export. Anything unmapped is written as an empty field and later reported as unavailable rather than as zero.

Both paths write the same table, so you can start on B and move to A later without touching the review. Every row carries a collection date, because metrics move after publication and a review that mixes a day-one read with a day-thirty read is not measuring anything.

One rule matters more than the rest: never invent a row to test the review. Run the review against an empty table instead. It should tell you it has no data, and if it produces a summary anyway, something is broken.

The advanced loop

Three additions once the minimum loop is running.

The reply pass. In the planning model, replies carry roughly thirteen times the weight of a like, which makes writing one a distribution action rather than a courtesy. Build a target list from accounts you already follow inside your topic pillars, and for each one produce a reply in one of four kinds: add a number the original post left out, offer a counterexample from your own work, ask the follow-up question its own logic demands, or describe what happened when you tried it.

What to reject matters more than what to accept. Bare praise, agreement with no addition, and replies that are secretly an advertisement for your own post all burn the only thing that makes a reply worth writing, which is that you said something the original did not.

The 48-hour window. The planning model treats the first two days after publication as the period when a post can still be picked up. Two rules follow. Do not re-run a month-old post as though it were fresh; if it deserves reviving, rewrite it around a new angle and publish new material. And do not judge a post before the window closes. weekly_review.py excludes the early rows automatically, and overriding that by hand is the fastest way to make the review lie.

The weekly review. One command, and it prints what it can prove.

bash
python3 x-ops/scripts/weekly_review.py --window 20

It joins the ledger to the metrics on the post id, uses medians rather than means so one good post does not define a whole slot, and names four patterns: high impressions with low reposts, meaning you reached people and did not travel; high bookmarks with low impressions, meaning the post was worth keeping and nobody saw it; low replies across every slot, which is a shape problem rather than a post problem; and one slot outperforming the rest on reach, which you record and do not act on. The last one is the ratio doing its job.

The output also carries a gap list in both directions. Ledger rows with no metrics, and metrics rows with no ledger entry, each mean something upstream is broken. A post published outside the loop still counts toward the mix, so log it rather than letting it disappear.

When it breaks

What you see

What it usually means

What to do

The same slot three days running

The window is thin, or posts are not being logged

Confirm the log step runs. Until there are about twenty rows, expect noise and say so

Every draft passes the gate

The gate is being read, not applied

Add your own clichés to BANNED in hook_lint.py and re-run

Most metrics rows fail to join

Post url formats differ between the ledger and the export

Both sides normalize to the numeric post id; check that post_url is populated in the ledger

The review is dominated by one post

The window is too small for medians to hold

Widen --window and report the outlier on its own

The mix drifts anyway

Posts are being published outside the loop

Log them. Off-loop posts are still part of the mix

Drafts read in a different voice each week

The brief has no banned list

Add the specific moves to avoid, each with an example

import maps almost nothing

Your export uses header names outside the alias list

Pass --map once, write the mapping into your notes, reuse it

Keeping the mix honest

The mix is the only part of this loop that fails silently. Nothing breaks when you publish four tutorials in a row. The account just narrows, and you find out four months later when the same people are the only ones reading.

Bar chart of actual against target share per slot across the last 20 logged posts, with slot A over its target and slots C, D and E under theirs

Two habits hold it, and both are in the script.

Count the trailing window, not the calendar. Twenty posts is a stable sample; two weeks is not, because the number of posts in two weeks is exactly the thing that varies. When the ledger holds fewer than twenty rows, plan prints a thin-window warning rather than a ratio that will swing on the next post.

Let the deficit pick, and let reach lose. When one slot is visibly outperforming the others on impressions, the pull is to publish more of it. That is the moment the ratio exists for. Record the observation, keep the plan, and revisit it after the window fills. If the imbalance holds across two full windows, change the target in the brief. Change the brief rather than the behaviour, so the next person reading the ledger can see why.

FAQ

Can it publish for me?

No, and that is deliberate. The skill writes drafts and records, and none of the four scripts contains a publish call. Automating the publishing action on X is a separate decision with its own platform-rule consequences, and it changes what the account is. Decide that on its own terms, not as a convenience feature.

Do I need the paid X API?

Only for path A. The loop runs without any metrics at all; you just cannot close the review. Manual import is the cheap path and it is not a temporary one. Ten minutes a week with honest empty cells beats a pipeline that fills gaps with estimates.

What if my account is not about AI?

The four roles, the six shapes, and the mix ratios are topic-agnostic. The only AI-specific content is the example material in the tables. Replace the pillars in the brief with your own and the rest holds.

Will this make my posts sound generated?

It pushes the other way. The gate rejects openers that would fit any post on any account, which is the specific failure that reads as generated. The part that stays yours is the evidence, because the skill will not invent it and you should not ask it to.

How long before the review says anything useful?

About twenty logged posts. Below that the medians are noise. Run the loop for the discipline until then and ignore the numbers.

Author: Rowan Blake, Content Automation Analyst for 100+ Publishing Pipelines at Auspia. Rowan writes about automated briefs, content pipelines, and AI-assisted production systems.

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