Grow the account: 10 AI skills for social media

engagement-replies

reply to every comment in your own voice

How the two work together

Claude thinks it through. Paste the Claude prompt into Claude Code, or drop the folder into your skills folder. Claude does the judgement: what to look for, what is worth doing, what is right.

Codex gets it done. At the hand-off point Claude runs Codex on your machine with one command and passes it the Codex prompt. Codex does the mechanical part and hands the result back. Claude checks it before you see it.

No API key to set up: Claude calls the Codex you already have installed. If Codex is not installed, Claude does that half itself and tells you.

Prompt for Claude

---
name: engagement-replies
description: Writes one reply to every comment on your post in your own voice, ordered by which replies actually grow the account. Use once the comments arrive.
---

# Reply to every comment in your own voice

Paste the comments, get a paste-ready reply for each, in your words.

## Claude does

1. Ask for four things, guess none: the post in full; the comments with each commenter's name and headline; the platform; and 5 to 10 of the user's own past replies as a voice sample. No sample, ask once and stop. An invented voice is what makes replies read as bot output.
2. Build a voice card first: sentence length, contractions, greetings, sign-offs, emoji count, capitalisation. Both leading skill repos load a persistent voice file before any draft; this does it in session.
3. Sort every comment: question, added insight, disagreement, agreement, spam. Spam gets nothing.
4. Rank by growth value, not arrival order: questions, then added insight (longest threads), then disagreement, then praise. Buffer's reply study, roughly 2 million posts and 220,000 accounts, measured +30% engagement on LinkedIn and +42% on Threads for accounts that reply. Target is all of them, inside 60 minutes.
5. Length by bucket. Praise: 1 sentence naming something specific they said. Question: 2 to 3 sentences with a real answer, never "great question". Added insight: 2 sentences building on their point, ending with a question back. Disagreement: 2 to 3 sentences conceding the true part first, no link, no pitch.
6. Write the pinned first comment, 1 to 2 lines, carrying any link, because links in the body suppress reach. Charlie Hills' set ships a skill for exactly this.
7. Flag what Claude will not answer: legal claims, pricing disputes, a named client, anyone visibly upset. These return as a note, never a draft.

## Then Codex does

Codex takes the bulk formatting: build the per-comment file, count characters against the platform ceiling, strip hashtags, catch repeated openings, order the list. Mechanical, because every judgement call is already fixed in the drafts.

```
codex exec --sandbox danger-full-access --skip-git-repo-check -C "<working folder>" - < CODEX.md
```

Claude fills these into CODEX.md first: `{VOICE_CARD}` from step 2, `{COMMENTS_AND_DRAFTS}` (comment, bucket, draft), `{PLATFORM}`, `{ACCOUNT_NAME}` (whose name they go out under).

## Claude checks

1. Read every reply against the voice card. A word the sample never uses gets rewritten, not shipped.
2. Check openings. Two replies opening the same way is the clearest tell of automated replying: reject and rerun.
3. Confirm no reply invents a number, date, client name or quote absent from the post or comment. Popular caption repos circulate precise statistics with no source; this is the mistake to catch.
4. Confirm no hashtags. Metricool's 2026 Instagram study, 24,364,803 posts, measured hashtags at -31.70% views.
5. Confirm the step 7 flags are still flagged and undrafted.
6. Any failure: rerun Codex naming it. Never hand-patch and call it passed.

## Rules

- Reply to every comment that is not spam, inside the hour.
- Never open with "Great question" or "Thanks for sharing".
- Never answer a disagreement with a link.
- Never score on likes. Metricool's 2026 LinkedIn study, 673,658 posts, found likes down 13% while engagement rose 14%.
- Public information only.
- Never invent a fact, a number or a quote.
- Anything sent in someone's name says whose name it is.

## If Codex is not installed

Claude does the formatting and checking itself, and says so in one line at the top.

## Built from

- charlie947/social-media-skills, https://github.com/charlie947/social-media-skills, 3,283 stars from api.github.com; ships pinned-comment and the voice-file-first pattern.
- Buffer, State of Social Media Engagement 2026, https://buffer.com/resources/state-of-social-media-engagement-2026/, roughly 2M posts, 220,000+ accounts; the reply uplift figures.
- Metricool 2026 Instagram Study, https://metricool.com/press-release-instagram-study-2026/, 24,364,803 posts; hashtag penalty.
- Metricool 2026 LinkedIn Study, https://metricool.com/press-release-linkedin-study-2026/, 673,658 posts; likes down 13%, engagement up 14%.

Prompt for Codex

# Reply to every comment in your own voice - Codex task

You are formatting and checking replies that are already written. Do not rewrite voice or change what a reply says. Your job is counting, deduplicating and laying out.

## You are given

- `{ACCOUNT_NAME}` - the person whose name these replies go out under. State it in every file.
- `{PLATFORM}` - LinkedIn, Instagram, Threads, TikTok or X. Sets the character ceiling.
- `{VOICE_CARD}` - sentence length, contractions yes or no, emoji count per reply, greetings and sign-offs, capitalisation habit.
- `{COMMENTS_AND_DRAFTS}` - a list. Each entry: commenter name, headline if known, comment text, bucket (question / added-insight / disagreement / agreement), draft reply.

## Produce

Three files in the working folder.

1. `replies.md` - ordered: questions, then added-insight, then disagreement, then agreement. Per entry, in order: `### <n>. <commenter name>`, the comment as a blockquote, the reply in a fenced block for clean copying, then `chars: <n> | bucket: <bucket> | opening: <first three words>`.
2. `pinned-comment.md` - the pinned first comment, 1 to 2 lines, plus its character count. If none was supplied, write `NONE SUPPLIED` and nothing else.
3. `checks.md` - a table, one row per check: duplicate opening phrases, hashtags found, replies over the ceiling, emoji counts outside the voice card range, replies containing a digit or date, replies containing a URL. Each row PASS or FAIL with the offending reply numbers.

Ceilings: LinkedIn 750, Instagram 500, Threads 500, TikTok 150, X 280.

## Rules

- Never change the meaning of a draft. A reply over the ceiling is flagged FAIL with its count, text left intact. Do not cut it yourself.
- Strip every hashtag and record how many were removed.
- No two replies may open with the same first three words. Report duplicates, do not fix them.
- Flag but do not remove any reply containing a digit, date, currency symbol or URL. A human confirms the fact is real.
- Do not add greetings, sign-offs, emoji or names not already in the draft.
- Public information only. Never invent a fact, a number or a quote. Nothing is sent anywhere; this is text for a person to send under `{ACCOUNT_NAME}`.
- British English throughout.

## Return

Print to stdout, nothing else:

1. The three file paths written.
2. `TOTAL REPLIES: <n>` and the count per bucket.
3. The full contents of `checks.md`.
4. A final line: `ALL CHECKS PASS` or `FAILED: <check names>`.

Built from the best public work on this

Sources

3,283 stars and 771 forks read from api.github.com and independently re-verified with a raw curl and JSON parse. GitHub user `charlie947` resolves to Charlie Hills, ranked #1 worldwide for LinkedIn growth by Favikon, 415k+ followers across platforms. Ships a dedicated `pinned-comment` skill and the voice-file-first architecture (`about-me.md` plus `voice.md` loaded before any draft) that this skill copies.

52M+ posts across 10 platforms, with a reply sub-study of roughly 2 million posts and 220,000+ accounts across 6 platforms. The only source found that isolates the effect of replying to comments: +30% engagement on LinkedIn, +42% on Threads.

24,364,803 posts from 375,118 accounts, Jan-Feb 2025 against Jan-Feb 2026. Hashtags measured at -31.70% views and -33.89% interactions. Comment-focused calls to action +202.78% comments; questions +36.70% comments; story replies +88%.

673,658 posts from 63,108 accounts. Likes down 13%, comments down 17%, shares down 10%, yet overall engagement up 14%. This is why the skill refuses to score replies on likes.

Best public prompt we found for this job

https://github.com/charlie947/social-media-skills - the `pinned-comment` skill, inside the working skill set behind a 415k-follower content system. It is the only public prompt found that treats the first comment as a deliberate growth surface rather than an afterthought, and its wider repo establishes the pattern this skill uses: load a persistent voice file first, ask only for what is missing, then draft.

Its README states the operating scale plainly: "415k+ followers across LinkedIn, Instagram, Substack, X and YouTube. 100m+ views per year."

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