Linkedin-skills linkedin-comment-drafter
Draft a high-quality LinkedIn comment on any post from a URL. Use when the user gives a LinkedIn post URL and asks to comment on it. The skill parses the URL, reads the post context, drafts 1-3 comment variants in the user's voice using 2026 hook patterns (first-commenter, data-first, answer-the-closing-question, quotable-reframe), picks a reaction type, and waits for approval before posting via Publora. Keywords: linkedin comment, engage post, comment draft, first commenter, linkedin reply strategy.
git clone https://github.com/sergebulaev/linkedin-skills
T=$(mktemp -d) && git clone --depth=1 https://github.com/sergebulaev/linkedin-skills "$T" && mkdir -p ~/.claude/skills && cp -r "$T/skills/linkedin-comment-drafter" ~/.claude/skills/sergebulaev-linkedin-skills-linkedin-comment-drafter && rm -rf "$T"
skills/linkedin-comment-drafter/SKILL.mdLinkedIn 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 (Kevin Payne / Ivan Tsybaev 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
, orAPPRECIATIONENTERTAINMENT - 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", calls Publora to react + comment.
Steps
- Parse the URL. Use
to getlib.url_parser.parse_linkedin_url
and, if present, the post's activity ID.post_urn - Fetch the post body. If HarvestAPI is available via
, pull the post text and top 3 existing comments (to avoid duplicate takes). If not, ask the user to paste the post text.corporate-knowledge/personal/knowledge/tools/social_poster/src/harvest_client.py - Detect the author's closing question. If the post ends with a "?" line, the Answer-the-Closing-Question template usually wins.
- Draft comment variants. Pick 2-3 templates from
that fit the post's topic. Fill them with user-voice phrasing.references/comment-templates.md - Run the humanizer pass. Strip em dashes, AI vocab, uniform sentence rhythm. Add a specific number or named entity if missing.
- Present drafts for approval using
. Include: target URL, each variant, reaction suggestion, a one-line "why this template fits".lib.approval.render_approval_card - On approval — adapt to the active backend. Call
:lib.active_backend()
(PUBLORA_API_KEY set) → react to the post with the chosen reaction type, pause 8-15s, then post viapublora
(top-level, nolib.PubloraClient.create_comment
). Return the comment URN.parent_comment
(no backend configured — the default) → output the approved draft viamanual
. This gives the user a copy-paste block plus a one-time setup prompt for Publora (the preferred auto-post path). Do NOT attempt to post programmatically.lib.manual_mode_message(draft_text, target_url, kind="comment")
(LINKEDIN_SKILLS_CUSTOM_POSTER set) → invoke the user's configured custom poster command with the draft text + target URL as arguments.diy
Templates (see references/comment-templates.md
for full list)
references/comment-templates.md- T1 Missing-Piece (Kevin Payne pattern, 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
, one-line rationale, and approval prompt.INTEREST
Files in this skill
— this fileSKILL.md
— the 7 templates with fill-in slots and real examplesreferences/comment-templates.md
— the specific voice rules from user feedback memoriesreferences/voice-rules.md
Related skills
— if you're replying to a comment (not posting top-level)linkedin-reply-handler
— for aggressive AI-tell scrubbinglinkedin-humanizer
— if you want to use the author's own hook as the basis for your replylinkedin-hook-extractor