linkedin-skills is a collection of Claude Code and Codex skills for creating and managing LinkedIn content from a terminal. It helps users draft posts, comments, and replies, review their feeds, and plan a publishing cadence while requiring approval before publication. The catalogue entries are the project's skills, instructions, and plugin for using these workflows with coding agents.
Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add sergebulaev/linkedin-skills --skill linkedin-reply-handlergit clone --depth 1 https://github.com/sergebulaev/linkedin-skillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/sergebulaev/linkedin-skills/linkedin-reply-handler)<a href="https://agentmods.dev/skills/sergebulaev/linkedin-skills/linkedin-reply-handler"><img src="https://agentmods.dev/badge/skills/sergebulaev/linkedin-skills/linkedin-reply-handler/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/sergebulaev/linkedin-skills/linkedin-reply-handler"><img src="https://agentmods.dev/badge/skills/sergebulaev/linkedin-skills/linkedin-reply-handler.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00108 | $0.03403 |
| Opus 5.5 | $0.00043 | $0.01361 |
| Sonnet 5.5 | $0.00022 | $0.00681 |
| Haiku 4.5 | $0.00011 | $0.00340 |
Grade A, and why
linkedin-reply-handler scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 11d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 162 lines — stays where its author put it; the contents beside it link to each section on GitHub.
LinkedIn Reply Handler
Drafts a reply to a specific LinkedIn comment, or sweeps an entire comment thread (every top-level comment and its replies) from just the post URL and drafts a reply to each one worth answering. Both modes correctly handle LinkedIn's 2-level thread flattening: if you're replying to a reply, the Publora API needs the TOP-level comment URN as parentComment, not the reply's URN.
When to use
Single comment:
- User pastes a LinkedIn comment URL (contains
?commentUrn=...) and says "reply to this" - An author replied to the user's comment and the user wants to continue the thread
- User wants to re-engage a conversation that's gone dormant
Whole thread (just a post URL, no comment URLs):
- User pastes a post URL and says "reply to all the comments", "clear my inbox on this post", "draft replies for everyone who commented", "sweep the comments on this post"
- User wants to catch up on a post that has accumulated comments over several days
Not for:
- Commenting on someone else's post (not replying to comments on the user's own post) →
linkedin-comment-drafter - Reading engagement without drafting anything →
linkedin-engager-analyticsorlinkedin-thread-monitor
Input
Either shape works:
- A LinkedIn URL containing
commentUrn=urn:li:comment:(activity:POST,COMMENT_ID)— either the direct comment permalink or a feed URL with the query fragment. Triggers single-comment mode. - Just a LinkedIn post URL, in any of the standard shapes (see root
SKILL.mdURL table) — no comment URLs needed. Triggers whole-thread mode.
Output
Single comment:
- 1-2 reply drafts, 150-300 chars each
- Reaction suggestion for the comment being replied to (always react before replying)
- Thread context summary (who said what, when)
- Approval card → on user "post", fires reaction + reply via Publora
Whole thread:
- A filtered roster: how many comments were fetched, how many were filtered out and why, how many drafts follow
- One reply draft per comment worth replying to (150-300 chars each), each tagged with its target comment, the correct
parentCommentURN, and a reaction suggestion - A single batch approval card covering every draft
- On approval, posts all of them (reaction + reply, per comment)
What ships with it
4 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 11d ago Changed acd48d54b179
- 1mo ago Changed · +9 lines 4fa68ca268de
- 1mo ago Changed 562a72d9581c
- 1mo ago Changed · +48 lines · +20 tokens per session 0cc94133713a
- 1mo ago Changed d784f1da688c
- 1mo ago Changed 20bf9710162f
- 1mo ago Changed · +18 lines ec45b3e8f8e1
- 1mo ago First seen · 87 lines · 88 tokens per session scan A bf9110953c9c
linkedin-reply-handler is a skill published in the GitHub repository sergebulaev/linkedin-skills (5,223 stars, last pushed 5d ago), licensed MIT. It adds 108 tokens to every session and 3,403 once invoked, about $0.0004 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other skills, from other repositories
linkedin-content-calendar-planner
Generate a 4-week LinkedIn content calendar tuned to the user's pillars, posting cadence, and audience. Returns a day-by-day plan with topic, format, hook angle, and CTA per post. Use when the user wants a system for the next month instead of inventing content every morning. Once the plan is confirmed it writes a…
linkedin-comment-opportunity-finder
Find the LinkedIn posts the user should comment on today to earn visibility, followers, and inbound. Pulls live candidates from the Taplio engagement feeds (the personalized selection, a curated creator feed for their niche, or a keyword search), scores each post on recency, audience overlap, engagement velocity, and…
linkedin-comment-reply-manager
Clear the comment inbox under the user's own LinkedIn posts. Pulls the comments that still need an answer (already answered, own, and hidden comments are filtered out), triages each one (question, pushback, lead signal, praise, spam), drafts a reply in the user's voice, and schedules the approved replies to post under…
linkedin-daily-engagement-routine
Run the user's daily 15-minute LinkedIn engagement session end to end : answer what is waiting under their own posts, pick today's 5 posts to comment on from the Taplio feeds, draft every reply and comment in their voice, get one batch approval, schedule everything, and close with the queue, yesterday's failures, and…
linkedin-engagement-watchlist-builder
Build the bench of creators the user should engage with every day. Samples the Taplio curated feeds that match their niche, the personalized selection, and a keyword search, clusters the live posts by author, and returns a ranked watchlist of 10 to 15 creators split into reach targets (bigger audiences, for…
linkedin-smart-comment-writer
Write a LinkedIn comment that gets noticed by the post author and the audience, save it as a Taplio comment draft, and, only on the user's explicit go, schedule it to post under their name. Avoids the generic great-post trap : 3 options on one angle (add, disagree, story, framework, question), ranked by likelihood of…