# Linkedin Comment Drafter

> Комменты и ответы в тредах LinkedIn: черновики + постинг через Publora, follow-up. Триггеры: «коммент на linkedin», «автор ответил».

- Skill: `jhamidun/linkedin-comment-drafter` (Agent Skill, multi-file: 3 files)
- Install (CLI): `npx skillmds@latest add jhamidun/linkedin-comment-drafter`
- Raw SKILL.md: https://api.skillmd.com/api/skills/jhamidun/linkedin-comment-drafter/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Coding & Dev Tools
- Author: JHamidun (https://skillmd.com/u/jhamidun)
- Updated: 2026-09-22
- Page: https://skillmd.com/skills/jhamidun/linkedin-comment-drafter

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# LinkedIn Comment Drafter

Produce conversation-provoking comments on any LinkedIn post from a URL. The skill targets the patterns that actually got author replies in 2026 testing (the missing-piece and specific-objection patterns) and avoids the thesis-restatement patterns that die with zero engagement.

## When to use

- User pastes a LinkedIn post URL and says "comment on this", "draft me a comment", "engage with this post"
- User wants to be among the first 3 commenters on a viral post
- User wants to reply to a closing question the author asked

## Input

A LinkedIn post URL in any of the standard shapes (see the top-level `SKILL.md` URL table).

## Output

1-3 draft comment variants, each with:
- 200-350 char body, 1-2 short paragraphs, no em dashes, no hashtags
- Assigned reaction type: `LIKE`, `PRAISE`, `EMPATHY`, `INTEREST`, `APPRECIATION`, or `ENTERTAINMENT`
- Pattern label (which of the 7 templates was used)
- Estimated engagement fit based on what the author typically responds to

Then waits for user approval. On "post", posts the reaction + comment through whatever publishing backend the user has configured — or returns a copy-paste block when none is (the default).

## Steps

1. **Parse the URL.** Use `lib.url_parser.parse_linkedin_url` to get `post_urn` and, if present, the post's activity ID.
2. **Fetch the post body.** HarvestAPI-клиент (corporate-knowledge repo) в этом окружении ОТСУТСТВУЕТ — fallback по умолчанию: попроси пользователя вставить текст поста + топ-3 существующих комментария (чтобы не дублировать takes), либо вытяни пост через ScraperVendor/browser (skill `dev-browser`).
3. **Detect the author's closing question.** If the post ends with a "?" line, the Answer-the-Closing-Question template usually wins.
4. **Draft comment variants.** Pick 2-3 templates from `references/comment-templates.md` that fit the post's topic. Fill them with user-voice phrasing.
5. **Run the humanizer pass.** Strip em dashes, AI vocab, uniform sentence rhythm. Add a specific number or named entity if missing.
6. **Present drafts for approval** using `lib.approval.render_approval_card`. Include: target URL, each variant, reaction suggestion, a one-line "why this template fits".
7. **On approval — adapt to the posting setup.** Автопостер LinkedIn в пак не входит — подключай свой; без него skill работает в ручном режиме:
   - **`manual`** (ничего не настроено — дефолт) → output the approved draft as a copy-paste block: текст варианта, целевой URL, рекомендованная реакция. Do NOT attempt to post programmatically.
   - **`diy`** (`LINKEDIN_SKILLS_CUSTOM_POSTER` set) → invoke the user's configured custom poster command with the draft text + target URL as arguments.
   - **свой API-публикатор** (например, Postiz self-hosted или собственный клиент LinkedIn API) → react to the post with the chosen reaction type, pause 8-15s, then post a top-level comment (no parent). Return the comment URN.

## Templates (see `references/comment-templates.md` for full list)

- **T1 Missing-Piece** (highest hit rate): `[Name] the [their-thesis] argument misses one piece.. [what-moved]. when [their-condition], the real differentiator is [specific-skill], not [their-focus].`
- **T2 Answer-the-Closing-Question**: direct answer + one concrete example + why it matters
- **T3 Data-First**: `half the [population] I see now [behavior]. the [old-assumption] broke around [date]. [new-rule].`
- **T4 Practitioner Observation**: `when X the system does Y, when X' it does Y'. that's when [outcome] kicks in.`
- **T5 Counter-with-Concession**: agree on point 1, push back on point 2 with one rooted reason
- **T6 Quotable-Reframe**: one line under 12 words + expansion
- **T7 Ask-a-Sharper-Question**: `the harder version of this question is..`

## Hard rules

- 200-350 chars. Don't exceed.
- Always capitalize the author's name (e.g., "Dharmesh", not "dharmesh").
- No em dashes, no hashtags, no emoji unless the post itself uses them.
- No mention of the user's own product by name. Describe what they do instead.
- Never paste generic praise ("Great post!", "This.", "100%"). The skill refuses.
- Skip the comment if the post is sponsored, a generic listicle, or the author has already deleted it.

## Example invocation

> User: "Comment on this: https://www.linkedin.com/posts/dharmesh_activity-7448808898326654978-iW20"
>
> Skill: [parses URL, fetches post, detects closing question "Seen this in your market?", drafts 3 variants]
>
> Skill returns: T2 Answer-the-Closing-Question variant as primary pick, with T1 Missing-Piece as backup, reaction `INTEREST`, one-line rationale, and approval prompt.

## Files in this skill

- `SKILL.md` — this file
- `references/comment-templates.md` — the 7 templates with fill-in slots and real examples
- `references/voice-rules.md` — the specific voice rules from user feedback memories

## Related skills

- `references/linkedin-reply-handler/` — if you're replying to a comment (not posting top-level)
- `linkedin-humanizer` — for aggressive AI-tell scrubbing
- `../linkedin-post-writer/references/linkedin-hook-extractor/` — if you want to use the author's own hook as the basis for your reply