Plan, draft, audit, and publish LinkedIn posts and comments.
SkillScore91Maintained
Automatic
◆Marketing & Content pack
Last verified 8/15/2026
What it changes
Passed 19 of 21 test cases with the skill, and 11 of 21 without it.
Without skill50%
With skill91%
Checks it passed that the model alone missed
Names supreme_coder/linkedin-post as the actor ID.
Returns the draft formatted in a copy-paste text block.
Omits the specific brand name SnapBackup from the comment.
and 8 more in the full report
10 fixed10 passed either way1 still failing1 broke
Pass-rate lift
+41 pp
Tokens
+121%
Agent turns
0%
Response time
-44%
Model gemini-3.6-flashMeasured 8/15/2026v220 of 22 cases passed with skill · 21 comparable
Tokens, turns and time describe resource use, not a dollar price.
See it in action
One of 10 test cases the skill fixed. Same model, same prompt, with and without the skill.
1 of 10
Prompt
When retrieving a public LinkedIn post body by URL without using login cookies, which public web actor ID should be invoked?
What was checked, without and with the skill
Checked
Without skill
With skill
Names supreme_coder/linkedin-post as the actor ID.
Missed
Passed
case-11 · gemini-3.6-flash · 8/15/2026 · answers are capped and redacted
What's inside
The instructions your model reads when the skill loads.
SKILL.md133 lines2 files
LinkedIn Marketing Skills
A bundle of 11 focused skills for LinkedIn content ops in 2026, built for Claude Code and Codex. Each skill is single-purpose, follows the draft → approval → publish pattern, and uses the Publora API for posting.
When to use this bundle
Writing a viral post → use linkedin-post-writer
Commenting on someone else's post → use linkedin-comment-drafter
Replying to a comment (yours or someone else's) → use linkedin-reply-handler
Reviewing a draft before publishing, removing AI tells, scoring AI emoji density, defending a flagged rule, or running 5 AI detectors in parallel → use linkedin-humanizer (rewrite + --mode audit pre-publish review; folds in the former post-audit, emoji-detector, rules-explainer, and detector-tester sub-tools)
Extracting a hook formula from a viral post → use linkedin-hook-extractor
Planning a week of LinkedIn content → use linkedin-content-planner
Tracking which of your comments got author replies → use linkedin-thread-monitor
Analyzing who liked / commented on any post (audience segmentation) → use linkedin-engager-analytics
Auditing / rewriting a LinkedIn profile → use linkedin-profile-optimizer
Running an employee advocacy program across a marketing team → use linkedin-employee-advocacy
Adapting content from another platform (tweet, video, blog) into a native LinkedIn post → use linkedin-repurposer
Founders edition
For founders building trust with investors, hires, and design partners, the bundle ships a dedicated founder layer:
references/founder-topics.md — 10 founder content angles (A1-A10) as fill-in templates: reprice the category, content-to-pipeline, audience of one, the scarce-shots math, the unglamorous bet, the limit of delegation, designed serendipity, the evasive-sentence test, the delegation line, the learning gate. Each maps to a primary goal and a hook formula.
4 structural formulas (F17-F20) in references/hook-formulas.md — controlled A/B anecdote, false-binary dissolve, anecdote-meets-evidence bridge, diverging-curves close. They shape a post's logic rather than its topic and back the founder angles.
A founders-edition pillar set (Conviction / Building in public / The math / Proof) in linkedin-content-planner.
linkedin-post-writer offers a founder angle before picking a formula when the writer is a founder; linkedin-content-planner asks "founder plan or general plan?" and swaps the pillar set. The founder angles compound trust with a narrow, high-value audience instead of chasing broad reach.
Core pattern
Every action-taking skill follows three steps:
Parse the input. User provides a LinkedIn URL (post or comment). The skill uses lib/url_parser.py to extract the post URN and any comment ID.
Draft the content. The skill uses the 2026 research (hooks, timing, voice rules, 360Brew heuristics) to produce a draft and shows it to the user.
Wait for approval. The user replies with "post", "yes", or suggests edits. Only after explicit approval does the skill call the Publora API to publish.