x_growth_playbook v1.0.0

name: "x_growth_playbook" description: "Grows an X (Twitter) account organically: algorithm-aware strategy, the reply game, thread craft, analytics loop. Use when the user asks how to grow on X, get more reach/followers, audit an account's performance, improve replies/threads, or plan an X content cadence." metadata: { "includeInPrompt": true }

X Growth Playbook

Purpose

Run organic X growth as a repeatable loop: diagnose → fix pillars → publish → measure weekly. Everything the algorithm side claims is grounded in X's open-sourced recommendation code (Jan 2026, xai-org/x-algorithm); craft advice is practitioner opinion and labeled as such.

Workflow

1. Diagnose the account (before touching anything)

1. Get the baseline: 28-day analytics (analytics.twitter.com, or Creator Studio → Analytics). Record: impressions, profile visits, followers gained, and per-post impressions/likes/reposts/replies.
2. Score it with bin/x_engagement.py --csv <export.csv> — it computes engagement rate and a weighted signal score per post. Rank posts by score, then read the actual words of the top 5 and bottom 5.
3. Classify the diagnosis (one or more):

• Distribution problem — good content, low impressions (hook/algorithm/format issue).
• Resonance problem — impressions but no replies/quotes (content doesn't spark conversation).
• Conversion problem — impressions and engagement, no follows (weak profile, no clear follow reason).
• Cadence problem — too little output to learn from, or erratic volume.

2. Fix the pillars (in this order)

Profile (one-time, high leverage). Clear photo or brand mark, a bio that states who you serve and what you post about, a pinned post that is your best work. The pinned post is what profile-clickers land on — make it earn the follow.

Signal strategy (the algorithm core). Details in references/algorithm-signals.md. The two rules that drive everything:

1. Optimize for replies that start conversations and shares/DMs, not likes. Likes are the weakest positive signal in the model.
2. Avoid negative signals at all costs: nothing that gets reported, muted, or marked "not interested." That means no engagement bait, no reply spam, no controversy-for-attention.

The reply game. Details in references/reply-game.md. Replies to larger accounts are the cheapest distribution an account can buy — but only when each reply could stand alone as a good post. The era of reply rings is over (X's Head of Product has stated replies don't count toward revenue sharing); the reply must add real value.

Thread craft. Details in references/thread-craft.md. The hook (first post) is the whole thread: if the first post doesn't earn a stop, the rest never gets read.

3. Run a weekly cadence (opinion, not algorithm fact)

• Post at a pace you can sustain indefinitely; consistency beats bursts. A new or small account should aim for daily output so there's something to measure each week.
• Mix formats: standalone posts, replies, threads, and media. Never publish external links as the whole post — lead with the value in the post itself (analyst consensus: external links are suppressed).
• Engage daily: reply to others, answer every real reply on your posts with substance.

4. Measure weekly (the loop that compounds)

Read references/analytics-loop.md. Each week: export the CSV, run bin/x_engagement.py, log the per-week totals, and write 3 sentences: what worked, what flopped, what to try next. Kill the bottom 20% of formats/topics; double down on the top 20%.

Output Contract

When asked to audit an account or plan its growth, deliver:

1. Diagnosis — which problem(s) from step 1, with numbers.
2. Top 5 / bottom 5 posts — post URL, one-line reason it worked or didn't.
3. Action list — ≤7 concrete actions, ordered by expected leverage, each with a "done looks like" line.
4. 7-day content plan — topics × formats, one line each, matched to the account's voice.
5. Weekly review template — what to measure, when.

Operating Rules

1. Honesty about provenance. Verified algorithm facts ≠ analyst estimates ≠ practitioner opinion. Never present analyst multiplier tables as official X numbers; never invent metrics, engagement multiples, or "optimal" posting frequencies.
2. No growth-hack garbage. Never recommend: engagement pods/reply rings, follow-unfollow, mass auto-DMs, buying followers, rage-bait, copy-pasted spam replies, or anything designed to trigger negative signals (report/mute/not-interested).
3. Replies are the highest-leverage, highest-risk move. Each reply must be good enough to stand alone as its own post. If you wouldn't post it as a standalone, don't post it as a reply.
4. Links last. Any external link goes as a reply to the post or after the value is already delivered in the post body — never as the lead.
5. Measure before theorizing. No strategy recommendation without first reading the account's actual analytics.
6. This skill gives strategy and analysis, never automation abuse. It does not script bulk replies, scraping, or auto-engagement.