Creator · sergebulaev
Last updated · Sep 3, 2026
Draft a new LinkedIn post from scratch using one of 20 2026 hook formulas (anaphora, R.I.P., time-anchor, curiosity-gap, contrarian, controlled A/B, false-binary, and more) plus a founders-edition angle library, picked by engagement goal (comments, reposts, likes, saves). Runs th
Creator · sergebulaev
Last updated · Sep 3, 2026
Draft a new LinkedIn post from scratch using one of 20 2026 hook formulas (anaphora, R.I.P., time-anchor, curiosity-gap, contrarian, controlled A/B, false-binary, and more) plus a founders-edition angle library, picked by engagement goal (comments, reposts, likes, saves). Runs th
Creator · sergebulaev
Last updated · Sep 3, 2026
Draft a new LinkedIn post from scratch using one of 20 2026 hook formulas (anaphora, R.I.P., time-anchor, curiosity-gap, contrarian, controlled A/B, false-binary, and more) plus a founders-edition angle library, picked by engagement goal (comments, reposts, likes, saves). Runs th
Creator · sergebulaev
Last updated · Sep 3, 2026
Draft a new LinkedIn post from scratch using one of 20 2026 hook formulas (anaphora, R.I.P., time-anchor, curiosity-gap, contrarian, controlled A/B, false-binary, and more) plus a founders-edition angle library, picked by engagement goal (comments, reposts, likes, saves). Runs th
Review then install
Install targets
Codex install prompt
Install the "linkedin-post-writer" agent skill from https://github.com/sergebulaev/linkedin-skills/tree/main/.codex-marketplace/linkedin-skills/skills/linkedin-post-writer. Read its SKILL.md or equivalent instructions first, install only the files needed for this workspace, and summarize any required setup before using it. Skill purpose: Draft a new LinkedIn post from scratch using one of 20 2026 hook formulas (anaphora, R.I.P., time-anchor, curiosity-gap, contrarian, controlled A/B, false-binary, and more) plus a founders-edition angle library, picked by engagement goal (comments, reposts, likes, saves). Runs the humanizer pass and schedules via Publora on approval. Use to write a post, find a hook or proven format, or get founder-specific angles. Not for reviewing existing drafts (use linkedin-humanizer --mode audit). After the install attempt, report the result to https://www.openagentskill.com/api/agent/outcome with POST JSON {"event_id":"install_<unique-id>","skill_slug":"sergebulaev-linkedin-post-writer","task":"Install linkedin-post-writer","agent":"codex","outcome":"success","install_used":true}. Replace event_id with a unique value and outcome with success or failed. Report success only after the skill is installed and a minimal verification passes.Supply asset profile
Code review, repo analysis, testing, CI, GitHub, DevOps, and developer workflow skills.
Scenario
Coding agents
I need a coding agent that can understand a repository, edit code, and review pull requests.
Agent fit
Claude Code + CLI + Codex
Codex, Claude Code, Cursor, CLI, or custom agents.
Install
Ready
npx skills add sergebulaev/linkedin-skills --skill linkedin-post-writer
Maintenance
fresh
4d since push
Risk
Safe to try
Quality score needs review
GitHub quality
652
75/100 Quality · 84/100 Trust
Coverage tags
Review notes
Quality score needs review
Agent adoption scorecard
These scores combine public repository metadata, OpenAgentSkill review signals, maintenance freshness, and install readiness. They are a shortlist signal, not a replacement for human review.
Quality
StrongSolid option that is likely worth shortlisting for production workflows.
Trust
Review then installGood shortlist signal, but the agent should review audit notes, install policy, and outcome evidence before running it.
Audit
Safe to tryA machine-readable review of install readiness, security metadata, maintenance, and adoption risk.
OpenAgentSkill Trust Score v5
Use as the primary candidate after human or sandbox review.
Stars
652 GitHub stars
Repo activity
652 stars, 99 forks
Maintenance
4d since push
License
MIT
Install
npx skills add sergebulaev/linkedin-skills --skill linkedin-post-writer
Install safety
Agent-readable metadata
Use this block or the embedded JSON to decide whether an agent should install this skill, choose an alternative, or ask for human review first.
Suited tasks
Suited agents
Install decision
Trust and risk
Outcome loop
Install command
npx skills add sergebulaev/linkedin-skills --skill linkedin-post-writerDo not use when
Agent safety v2
Good audit and safety signals with no high-risk permission hints in public metadata.
Review the audit page, then allow agent install in a sandboxed workflow.
medium
Skill may drive a browser or interact with web pages.
medium
Skill likely fetches remote pages, APIs, repositories, or external services.
Agent resolve plan
The Resolve API returns the selected skill, alternatives, safety policy, audit notes, install target, and copy-paste prompt an agent can follow without scraping this page.
Open JSON
/api/agent/resolve?task=Use%20linkedin-post-writer%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Resolve text
/api/agent/resolve?task=Use%20linkedin-post-writer%20for%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text
Install handoff
/api/skills/sergebulaev-linkedin-post-writer/install
Agent should check
Copy prompt
Task: Use linkedin-post-writer in this workspace.
Resolve first: https://www.openagentskill.com/api/agent/resolve?task=Use%20linkedin-post-writer%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Review install handoff: https://www.openagentskill.com/api/skills/sergebulaev-linkedin-post-writer/install
Install command: npx skills add sergebulaev/linkedin-skills --skill linkedin-post-writer
Before running it, summarize audit warnings, required permissions, and the fallback skill if install is risky.Agent handoff
Use the public install endpoint to fetch the command, safety checklist, target prompts, and canonical links for this skill.
Install handoff
/api/skills/sergebulaev-linkedin-post-writer/install
LLM text format
/api/skills/sergebulaev-linkedin-post-writer/install?format=text
Find alternatives
/api/skills/search?q=linkedin-post-writer&limit=3
Agent prompt
Use linkedin-post-writer for this task. Review https://www.openagentskill.com/api/skills/sergebulaev-linkedin-post-writer/install, then install with: npx skills add sergebulaev/linkedin-skills --skill linkedin-post-writerRegistry metadata
This page exposes the same decision, trust, audit, use-case, and install signals through the Registry API, so agents can rank this skill without scraping the UI.
Manifest
/api/registry/manifest/sergebulaev-linkedin-post-writer
LLM text
/api/registry/manifest/sergebulaev-linkedin-post-writer?format=text
Install alias
/api/registry/install/sergebulaev-linkedin-post-writer
Recommend
/api/registry/recommend?task=Use%20linkedin-post-writer%20in%20an%20agent%20workflow&limit=3
Agent fit
Security and compliance
Platforms
Claude Code
Audit report
A machine-readable review of install readiness, security metadata, maintenance, and adoption risk.
Agent decision cockpit
Use this as a leading candidate, then validate the README and install path in your own agent stack.
Role in stack
Primary pick
Primary fit
Security and compliance
Trust label
Production-ready
Install path
Command ready
Use when
Evidence
review first
Implementation path
Trust profile
Good shortlist signal, but the agent should review audit notes, install policy, and outcome evidence before running it.
GitHub adoption
INFO652 GitHub stars
Stars/forks activity
INFO652 stars, 99 forks; issue activity unavailable in current metadata
Recent maintenance
PASS4d since push
License clarity
PASSMIT
Good signals
Review before install
Recommended action
Use as the primary candidate after human or sandbox review.
Quality profile
Solid option that is likely worth shortlisting for production workflows.
Workflow fit
Reduce risk
I need my agent to scan a project for security risks and summarize what needs attention.
Operate web apps
I need my agent to control a browser, fill forms, and verify web app workflows.
Automate repeated work
I need my agent to automate a repeated workflow across tools and files.
Workflow fit
Operate and verify web apps
A workflow for agents that navigate products, fill forms, take screenshots, and verify real user flows across web applications.
Design, build, test, and ship interfaces
A practical workflow for agents that turn product briefs or Figma designs into polished frontend code, review the result, test it in a browser, and prepare a safe deployment.
Turn skills into distribution
A workflow for turning newly indexed skills into SEO briefs, social drafts, comparison pages, and reusable publishing workflows.
Alternative shortlist
Similar skills that may fit this task.
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--- name: linkedin-post-writer description: Draft a new LinkedIn post from scratch using one of 20 2026 hook formulas (anaphora, R.I.P., time-anchor, curiosity-gap, contrarian, controlled A/B, false-binary, and more) plus a founders-edition angle library, picked by engagement goal (comments, reposts, likes, saves). Runs the humanizer pass and schedules via Publora on approval. Use to write a post, find a hook or proven format, or get founder-specific angles. Not for reviewing existing drafts (use linkedin-humanizer --mode audit). ---
# LinkedIn Post Writer
Ship long-form LinkedIn posts using hook formulas that actually performed in 2025-2026 (verified engagement multipliers).
## When to use
- User says "write me a LinkedIn post about X" - User has a topic + a rough angle and needs a hook + structure - User wants to pick from known-winning formats and fill in their voice - User wants to audit + schedule in one flow
## Formulas this skill can use
| Code | Formula | Reference eng | Best for | |---|---|---|---| | F1 | Platform Risk Anaphora | 4,240 | Category/platform posts, product-as-fix | | F2 | R.I.P. Obituary | 3,822 | Era-ending claims, industry pivots | | F3 | Year-over-Year Pivot | 494, 3.74x | Identity shifts, founder reflection | | F4 | Time-Anchor Confession | 1,519+ | Vulnerability, voice reset, ICP re-targeting | | F5 | Self-Proving Meta | 1,082 / 435 comments | Commitment-based posts, tests in public | | F6 | Comment-Gate Lead Magnet | 717-3,008 | List building (use sparingly, capped reach) | | F7 | Odd-Precision Money Ledger | 1,755, 9.4x | Founder build-log, cost breakdowns | | F8 | Paid-vs-Free Reversal | 550, 19.64x | Free framework give-away | | F9 | Curiosity-Gap Teaser | 306, 4.25x | Emergent behavior, behind-the-scenes | | F10 | Contrarian + Historical Receipts | 3,083 | Sacred-cow takes, AI/tech cycles | | F11 | Emotional Cold-Open | high-reach* | Real story with emotional stakes (likes) | | F12 | Permission Slip | comment-heavy* | Encouragement, reassurance (comments) | | F13 | Bait-and-Switch Reversal | high-reach* | Policy/process change that's an upgrade (likes) | | F14 | Named Gratitude / Tribute | repost-heavy* | Thanking mentors / team / departing colleague (reposts) | | F15 | Explain-to-Kids | save-heavy* | Demystifying jargon (saves) | | F16 | Status-Strip Humility | like-heavy* | Senior voice wanting warmth not distance (likes) | | F17 | Controlled A/B Anecdote | structural†| One-variable comparison, delegation/AI takes (comments) | | F18 | False-Binary Dissolve | structural†| "Both obvious answers fail" governance/strategy (comments/reposts) | | F19 | Anecdote-Meets-Evidence Bridge | structural†| Personal noticing + a data stack (comments/saves) | | F20 | Diverging-Curves Close | structural†| Two trajectories that diverge, quotable maxim (reposts) |
\* F11-F16 reach is absolute 2026-corpus reach (often source-driven: a reshare or a famous author), NOT a baseline multiplier like the F1-F10 numbers. The two columns measure different things and are not comparable: F11's "256k" is raw reach, F8's "550, 19.64x" is a format multiplier. Do not rank formulas by putting these side by side. See `../../references/hook-formulas.md` for each formula's real reference and caveats.
†F17-F20 are **structural formulas**: they shape the logic of a post (a controlled comparison, a false binary, an evidence bridge, two diverging curves) rather than its topic. They carry no reference number and are chosen by primary goal. They were built for the founders edition and several founder angles pin them by name.
Full skeletons in `../../references/hook-formulas.md`. F1-F10 are the long-form thought-leadership set; F11-F16 (validated against a 2026 corpus of above-average performers) skew shorter and emotional and each carries a primary engagement goal.
### Pick by goal first
If the user knows what they want the post to earn, start here, then narrow by topic. Canonical mapping: `../../references/hook-formulas.md` → Engagement-goal split.
| Goal | Reach for | |---|---| | Comments | F4, F10, F12, F9 | | Reposts | F14, F2, F8 | | Likes | F11, F13, F16 | | Saves | F15, F7, F8 |
## Steps
**Voice profile first (all drafts).** If `../../references/voice-profile.md` has `filled: yes`, load it and match the user's voice fingerprint, hard rules, and CTA/link style throughout. If it is not filled, mention once that `linkedin-humanizer --mode profile` can learn their voice from a few posts, then proceed with the generic voice rules.
**Founder mode (when the writer is a founder).** Before picking a formula, open `../../references/founder-topics.md` and offer a founder **angle** (A1-A10) that fits their goal. The angle picks the *territory* (reprice the category, the scarce-shots math, the delegation line, and so on); several angles pin the formula for you (A9 uses F17, A10 uses F18+F20). Founder angles compound trust with a narrow audience of investors, hires, and design partners rather than chasing broad reach. Fill the angle's bracketed slots with the founder's real numbers, then continue from step 3.
1. **Gather inputs.** Topic, angle, draft ideas if the user has them, target audience (founders / operators / marketers), desired length (short 300-500 / medium 900-1300 / long 1500-1900 chars). 2. **Pick the formula.** First ask (or infer) the goal: comments, reposts, likes, or saves. Use the "Pick by goal first" table to shortlist, then suggest 2-3 formulas that also fit the topic and let the user pick. Show the reference engagement number next to each. 3. **Draft the post.** Fill the formula skeleton with user voice. Respect the 2026 algorithm rules: - Hook in first 210 chars (before "… see more") - 900-1,300 char sweet spot for text posts - Double line-breaks between ideas, not single - 0-2 hashtags, placed at end - No external links in body (move to first comment) 4. **Humanizer pass.** Strip em dashes, AI vocab, rule-of-three, generic openers. Add at least 1 specific number, 1 named entity, 1 first-person concrete detail per 100 words. 5. **Run audit.** Optionally invoke `linkedin-humanizer --mode audit` for algorithm + voice checks before showing to user. 6. **Optional illustration.** If the post would land better with a visual (or the user asks), offer one: draft an image and generate it with `lib.illustrate(prompt, kind="wide")`, pulling brand handle/color from Voice & Brand Profile §6 for the overlay. Show the returned `url` + `cost` in the approval card and attach it via `media_urls` on publish. For a **multi-image grid** (2-10 images in one post) use `lib.illustrate_set([p1, p2, ...], kind="wide", overlay=brand)` and pass every `url` in `media_urls=[...]`. Full workflow: `linkedin-humanizer/sub-skills/illustration.md`. No Pixfaro key -> it drafts the prompt for the user to generate manually. 7. **Approval card.** Show: formula used, full draft, char count, suggested posting window (Tue/Wed/Thu 7:30-9:00 AM local), reaction targets from likely commenters, and the illustration (if any). 8. **On approval.** Call `lib.publish(kind="post", draft_text=<approved>, target_url="https://www.linkedin.com/post/new/", platforms=[{"platform":"linkedin","platformId":<id>}], scheduled_time=<iso_or_None>, media_urls=<list_or_None>)`. The wrapper handles Publora / manual / diy routing.
## Hard rules (from user feedback)
Global voice rules: see root `SKILL.md` §Voice rules. Additional skill-specific rules:
- Never frame LinkedIn as inferior in a LinkedIn post (algo penalty). - Don't name-drop the user's product in a way that reads as self-promo. One mention max, and only when it's the natural conclusion, not the pitch. - Include at least one moment of real vulnerability or concrete stakes. Pure insight posts don't land in 2026. - Vary sentence length aggressively. Mix 3-word sentences and 25-word sentences.
## Anti-patterns (skill will refuse)
- All-caps first line ("THIS CHANGED EVERYTHING."). This holds even for F11 Emotional Cold-Open: carry the intensity with word choice, never caps. - Em dashes anywhere - "In today's fast-paced world" openers - Rule-of-three lists without receipts - "Game-changer", "deep dive", "leverage", "fundamentally" - External links in the body - Reused engagement-bait closers ("tag someone who needs this")
## Resources
- `../../references/hook-formulas.md` — all 20 formula skeletons with worked examples - `../../references/founder-topics.md` — founders-edition library of 10 founder angles (A1-A10) with fill-in templates - `../../references/algorithm-heuristics.md` — 2026 posting rules (timing, format, length) - `references/humanizer-checklist.md` — the full scrub list
## Related skills
- `linkedin-humanizer` — aggressive AI-tell scrubber, plus `--mode audit` for pre-publish review - `linkedin-hook-extractor` — reverse-engineer a hook from a viral post you admire
Source provenance
Decision snapshot
652 GitHub stars
Audit
Install and adoption review
Agent-proven evidence
Outcome reports after resolve, review, install, and one narrow run.
No agent outcome data yet. The first agent run can report success, setup needs, risk blocks, failure, or not-relevant through /api/agent/outcome.
Install
Free and open source. Review the report before installing into production agents.
Growth loop
Scenario-led draft for linkedin-post-writer, ready for a manual X post.
linkedin-post-writer: Draft a new LinkedIn post from scratch using one of 20 2026 hook formulas (anaphora, R.I.P.,... 652 stars https://www.openagentskill.com/skills/sergebulaev-linkedin-post-writer?ref=x
Listing + install path for linkedin-post-writer: https://www.openagentskill.com/skills/sergebulaev-linkedin-post-writer?ref=x Install: npx skills add sergebulaev/linkedin-skills --skill linkedin-post-writer
Listing source
This listing was indexed from public sources and is not marked official until a maintainer claim is approved.
Attribution links to the public repository or creator profile. Creators can claim the listing to update ownership signals.
Claim this skillOwner claim
This Registry indexed listing is attributed to sergebulaev but is not marked official yet. Claim it to add a verified owner signal and make future launch, install, and audit updates easier to trust.
Creator backlink kit
Show the canonical listing, current trust and audit signals, and real Agent-Proven evidence where developers evaluate the repository.
[](https://www.openagentskill.com/skills/sergebulaev-linkedin-post-writer?ref=github&utm_source=github&utm_medium=referral&utm_campaign=creator_badge)
[](https://www.openagentskill.com/skills/sergebulaev-linkedin-post-writer?ref=github&utm_source=github&utm_medium=referral&utm_campaign=creator_badge)
[](https://www.openagentskill.com/skills/sergebulaev-linkedin-post-writer/audit)
[](https://www.openagentskill.com/skills/sergebulaev-linkedin-post-writer?ref=github&utm_source=github&utm_medium=referral&utm_campaign=creator_badge)sergebulaev
@sergebulaev
Share whether this skill looks useful for your agent workflow. Aggregated feedback improves rankings over time.
Review then install
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Install targets
Codex install prompt
Install the "linkedin-post-writer" agent skill from https://github.com/sergebulaev/linkedin-skills/tree/main/.codex-marketplace/linkedin-skills/skills/linkedin-post-writer. Read its SKILL.md or equivalent instructions first, install only the files needed for this workspace, and summarize any required setup before using it. Skill purpose: Draft a new LinkedIn post from scratch using one of 20 2026 hook formulas (anaphora, R.I.P., time-anchor, curiosity-gap, contrarian, controlled A/B, false-binary, and more) plus a founders-edition angle library, picked by engagement goal (comments, reposts, likes, saves). Runs the humanizer pass and schedules via Publora on approval. Use to write a post, find a hook or proven format, or get founder-specific angles. Not for reviewing existing drafts (use linkedin-humanizer --mode audit). After the install attempt, report the result to https://www.openagentskill.com/api/agent/outcome with POST JSON {"event_id":"install_<unique-id>","skill_slug":"sergebulaev-linkedin-post-writer","task":"Install linkedin-post-writer","agent":"codex","outcome":"success","install_used":true}. Replace event_id with a unique value and outcome with success or failed. Report success only after the skill is installed and a minimal verification passes.Supply asset profile
Code review, repo analysis, testing, CI, GitHub, DevOps, and developer workflow skills.
Scenario
Coding agents
I need a coding agent that can understand a repository, edit code, and review pull requests.
Agent fit
Claude Code + CLI + Codex
Codex, Claude Code, Cursor, CLI, or custom agents.
Install
Ready
npx skills add sergebulaev/linkedin-skills --skill linkedin-post-writer
Maintenance
fresh
4d since push
Risk
Safe to try
Quality score needs review
GitHub quality
652
75/100 Quality · 84/100 Trust
Coverage tags
Review notes
Quality score needs review
Agent adoption scorecard
These scores combine public repository metadata, OpenAgentSkill review signals, maintenance freshness, and install readiness. They are a shortlist signal, not a replacement for human review.
Quality
StrongSolid option that is likely worth shortlisting for production workflows.
Trust
Review then installGood shortlist signal, but the agent should review audit notes, install policy, and outcome evidence before running it.
Audit
Safe to tryA machine-readable review of install readiness, security metadata, maintenance, and adoption risk.
OpenAgentSkill Trust Score v5
Use as the primary candidate after human or sandbox review.
Stars
652 GitHub stars
Repo activity
652 stars, 99 forks
Maintenance
4d since push
License
MIT
Install
npx skills add sergebulaev/linkedin-skills --skill linkedin-post-writer
Install safety
Agent-readable metadata
Use this block or the embedded JSON to decide whether an agent should install this skill, choose an alternative, or ask for human review first.
Suited tasks
Suited agents
Install decision
Trust and risk
Outcome loop
Install command
npx skills add sergebulaev/linkedin-skills --skill linkedin-post-writerDo not use when
Agent safety v2
Good audit and safety signals with no high-risk permission hints in public metadata.
Review the audit page, then allow agent install in a sandboxed workflow.
medium
Skill may drive a browser or interact with web pages.
medium
Skill likely fetches remote pages, APIs, repositories, or external services.
Agent resolve plan
The Resolve API returns the selected skill, alternatives, safety policy, audit notes, install target, and copy-paste prompt an agent can follow without scraping this page.
Open JSON
/api/agent/resolve?task=Use%20linkedin-post-writer%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Resolve text
/api/agent/resolve?task=Use%20linkedin-post-writer%20for%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text
Install handoff
/api/skills/sergebulaev-linkedin-post-writer/install
Agent should check
Copy prompt
Task: Use linkedin-post-writer in this workspace.
Resolve first: https://www.openagentskill.com/api/agent/resolve?task=Use%20linkedin-post-writer%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Review install handoff: https://www.openagentskill.com/api/skills/sergebulaev-linkedin-post-writer/install
Install command: npx skills add sergebulaev/linkedin-skills --skill linkedin-post-writer
Before running it, summarize audit warnings, required permissions, and the fallback skill if install is risky.Agent handoff
Use the public install endpoint to fetch the command, safety checklist, target prompts, and canonical links for this skill.
Install handoff
/api/skills/sergebulaev-linkedin-post-writer/install
LLM text format
/api/skills/sergebulaev-linkedin-post-writer/install?format=text
Find alternatives
/api/skills/search?q=linkedin-post-writer&limit=3
Agent prompt
Use linkedin-post-writer for this task. Review https://www.openagentskill.com/api/skills/sergebulaev-linkedin-post-writer/install, then install with: npx skills add sergebulaev/linkedin-skills --skill linkedin-post-writerRegistry metadata
This page exposes the same decision, trust, audit, use-case, and install signals through the Registry API, so agents can rank this skill without scraping the UI.
Manifest
/api/registry/manifest/sergebulaev-linkedin-post-writer
LLM text
/api/registry/manifest/sergebulaev-linkedin-post-writer?format=text
Install alias
/api/registry/install/sergebulaev-linkedin-post-writer
Recommend
/api/registry/recommend?task=Use%20linkedin-post-writer%20in%20an%20agent%20workflow&limit=3
Agent fit
Security and compliance
Platforms
Claude Code
Audit report
A machine-readable review of install readiness, security metadata, maintenance, and adoption risk.
Agent decision cockpit
Use this as a leading candidate, then validate the README and install path in your own agent stack.
Role in stack
Primary pick
Primary fit
Security and compliance
Trust label
Production-ready
Install path
Command ready
Use when
Evidence
review first
Implementation path
Trust profile
Good shortlist signal, but the agent should review audit notes, install policy, and outcome evidence before running it.
GitHub adoption
INFO652 GitHub stars
Stars/forks activity
INFO652 stars, 99 forks; issue activity unavailable in current metadata
Recent maintenance
PASS4d since push
License clarity
PASSMIT
Good signals
Review before install
Recommended action
Use as the primary candidate after human or sandbox review.
Quality profile
Solid option that is likely worth shortlisting for production workflows.
Workflow fit
Reduce risk
I need my agent to scan a project for security risks and summarize what needs attention.
Operate web apps
I need my agent to control a browser, fill forms, and verify web app workflows.
Automate repeated work
I need my agent to automate a repeated workflow across tools and files.
Workflow fit
Operate and verify web apps
A workflow for agents that navigate products, fill forms, take screenshots, and verify real user flows across web applications.
Design, build, test, and ship interfaces
A practical workflow for agents that turn product briefs or Figma designs into polished frontend code, review the result, test it in a browser, and prepare a safe deployment.
Turn skills into distribution
A workflow for turning newly indexed skills into SEO briefs, social drafts, comparison pages, and reusable publishing workflows.
Alternative shortlist
Similar skills that may fit this task.
Wazuh - The Open Source Security Platform. Unified XDR and SIEM protection for endpoints and cloud workloads.
🕵️‍♂️ Collect a dossier on a person by username from 3000+ sites
Nuclei is a fast, customizable vulnerability scanner powered by the global security community and built on a simple YAML-based DSL, enabling collaboration to tackle trending vulnerabilities on the internet. It helps you find vulnerabilities in your applications, APIs, networks, DNS, and cloud configurations.
Infisical is the open-source platform for secrets, certificates, and privileged access management.
--- name: linkedin-post-writer description: Draft a new LinkedIn post from scratch using one of 20 2026 hook formulas (anaphora, R.I.P., time-anchor, curiosity-gap, contrarian, controlled A/B, false-binary, and more) plus a founders-edition angle library, picked by engagement goal (comments, reposts, likes, saves). Runs the humanizer pass and schedules via Publora on approval. Use to write a post, find a hook or proven format, or get founder-specific angles. Not for reviewing existing drafts (use linkedin-humanizer --mode audit). ---
# LinkedIn Post Writer
Ship long-form LinkedIn posts using hook formulas that actually performed in 2025-2026 (verified engagement multipliers).
## When to use
- User says "write me a LinkedIn post about X" - User has a topic + a rough angle and needs a hook + structure - User wants to pick from known-winning formats and fill in their voice - User wants to audit + schedule in one flow
## Formulas this skill can use
| Code | Formula | Reference eng | Best for | |---|---|---|---| | F1 | Platform Risk Anaphora | 4,240 | Category/platform posts, product-as-fix | | F2 | R.I.P. Obituary | 3,822 | Era-ending claims, industry pivots | | F3 | Year-over-Year Pivot | 494, 3.74x | Identity shifts, founder reflection | | F4 | Time-Anchor Confession | 1,519+ | Vulnerability, voice reset, ICP re-targeting | | F5 | Self-Proving Meta | 1,082 / 435 comments | Commitment-based posts, tests in public | | F6 | Comment-Gate Lead Magnet | 717-3,008 | List building (use sparingly, capped reach) | | F7 | Odd-Precision Money Ledger | 1,755, 9.4x | Founder build-log, cost breakdowns | | F8 | Paid-vs-Free Reversal | 550, 19.64x | Free framework give-away | | F9 | Curiosity-Gap Teaser | 306, 4.25x | Emergent behavior, behind-the-scenes | | F10 | Contrarian + Historical Receipts | 3,083 | Sacred-cow takes, AI/tech cycles | | F11 | Emotional Cold-Open | high-reach* | Real story with emotional stakes (likes) | | F12 | Permission Slip | comment-heavy* | Encouragement, reassurance (comments) | | F13 | Bait-and-Switch Reversal | high-reach* | Policy/process change that's an upgrade (likes) | | F14 | Named Gratitude / Tribute | repost-heavy* | Thanking mentors / team / departing colleague (reposts) | | F15 | Explain-to-Kids | save-heavy* | Demystifying jargon (saves) | | F16 | Status-Strip Humility | like-heavy* | Senior voice wanting warmth not distance (likes) | | F17 | Controlled A/B Anecdote | structural†| One-variable comparison, delegation/AI takes (comments) | | F18 | False-Binary Dissolve | structural†| "Both obvious answers fail" governance/strategy (comments/reposts) | | F19 | Anecdote-Meets-Evidence Bridge | structural†| Personal noticing + a data stack (comments/saves) | | F20 | Diverging-Curves Close | structural†| Two trajectories that diverge, quotable maxim (reposts) |
\* F11-F16 reach is absolute 2026-corpus reach (often source-driven: a reshare or a famous author), NOT a baseline multiplier like the F1-F10 numbers. The two columns measure different things and are not comparable: F11's "256k" is raw reach, F8's "550, 19.64x" is a format multiplier. Do not rank formulas by putting these side by side. See `../../references/hook-formulas.md` for each formula's real reference and caveats.
†F17-F20 are **structural formulas**: they shape the logic of a post (a controlled comparison, a false binary, an evidence bridge, two diverging curves) rather than its topic. They carry no reference number and are chosen by primary goal. They were built for the founders edition and several founder angles pin them by name.
Full skeletons in `../../references/hook-formulas.md`. F1-F10 are the long-form thought-leadership set; F11-F16 (validated against a 2026 corpus of above-average performers) skew shorter and emotional and each carries a primary engagement goal.
### Pick by goal first
If the user knows what they want the post to earn, start here, then narrow by topic. Canonical mapping: `../../references/hook-formulas.md` → Engagement-goal split.
| Goal | Reach for | |---|---| | Comments | F4, F10, F12, F9 | | Reposts | F14, F2, F8 | | Likes | F11, F13, F16 | | Saves | F15, F7, F8 |
## Steps
**Voice profile first (all drafts).** If `../../references/voice-profile.md` has `filled: yes`, load it and match the user's voice fingerprint, hard rules, and CTA/link style throughout. If it is not filled, mention once that `linkedin-humanizer --mode profile` can learn their voice from a few posts, then proceed with the generic voice rules.
**Founder mode (when the writer is a founder).** Before picking a formula, open `../../references/founder-topics.md` and offer a founder **angle** (A1-A10) that fits their goal. The angle picks the *territory* (reprice the category, the scarce-shots math, the delegation line, and so on); several angles pin the formula for you (A9 uses F17, A10 uses F18+F20). Founder angles compound trust with a narrow audience of investors, hires, and design partners rather than chasing broad reach. Fill the angle's bracketed slots with the founder's real numbers, then continue from step 3.
1. **Gather inputs.** Topic, angle, draft ideas if the user has them, target audience (founders / operators / marketers), desired length (short 300-500 / medium 900-1300 / long 1500-1900 chars). 2. **Pick the formula.** First ask (or infer) the goal: comments, reposts, likes, or saves. Use the "Pick by goal first" table to shortlist, then suggest 2-3 formulas that also fit the topic and let the user pick. Show the reference engagement number next to each. 3. **Draft the post.** Fill the formula skeleton with user voice. Respect the 2026 algorithm rules: - Hook in first 210 chars (before "… see more") - 900-1,300 char sweet spot for text posts - Double line-breaks between ideas, not single - 0-2 hashtags, placed at end - No external links in body (move to first comment) 4. **Humanizer pass.** Strip em dashes, AI vocab, rule-of-three, generic openers. Add at least 1 specific number, 1 named entity, 1 first-person concrete detail per 100 words. 5. **Run audit.** Optionally invoke `linkedin-humanizer --mode audit` for algorithm + voice checks before showing to user. 6. **Optional illustration.** If the post would land better with a visual (or the user asks), offer one: draft an image and generate it with `lib.illustrate(prompt, kind="wide")`, pulling brand handle/color from Voice & Brand Profile §6 for the overlay. Show the returned `url` + `cost` in the approval card and attach it via `media_urls` on publish. For a **multi-image grid** (2-10 images in one post) use `lib.illustrate_set([p1, p2, ...], kind="wide", overlay=brand)` and pass every `url` in `media_urls=[...]`. Full workflow: `linkedin-humanizer/sub-skills/illustration.md`. No Pixfaro key -> it drafts the prompt for the user to generate manually. 7. **Approval card.** Show: formula used, full draft, char count, suggested posting window (Tue/Wed/Thu 7:30-9:00 AM local), reaction targets from likely commenters, and the illustration (if any). 8. **On approval.** Call `lib.publish(kind="post", draft_text=<approved>, target_url="https://www.linkedin.com/post/new/", platforms=[{"platform":"linkedin","platformId":<id>}], scheduled_time=<iso_or_None>, media_urls=<list_or_None>)`. The wrapper handles Publora / manual / diy routing.
## Hard rules (from user feedback)
Global voice rules: see root `SKILL.md` §Voice rules. Additional skill-specific rules:
- Never frame LinkedIn as inferior in a LinkedIn post (algo penalty). - Don't name-drop the user's product in a way that reads as self-promo. One mention max, and only when it's the natural conclusion, not the pitch. - Include at least one moment of real vulnerability or concrete stakes. Pure insight posts don't land in 2026. - Vary sentence length aggressively. Mix 3-word sentences and 25-word sentences.
## Anti-patterns (skill will refuse)
- All-caps first line ("THIS CHANGED EVERYTHING."). This holds even for F11 Emotional Cold-Open: carry the intensity with word choice, never caps. - Em dashes anywhere - "In today's fast-paced world" openers - Rule-of-three lists without receipts - "Game-changer", "deep dive", "leverage", "fundamentally" - External links in the body - Reused engagement-bait closers ("tag someone who needs this")
## Resources
- `../../references/hook-formulas.md` — all 20 formula skeletons with worked examples - `../../references/founder-topics.md` — founders-edition library of 10 founder angles (A1-A10) with fill-in templates - `../../references/algorithm-heuristics.md` — 2026 posting rules (timing, format, length) - `references/humanizer-checklist.md` — the full scrub list
## Related skills
- `linkedin-humanizer` — aggressive AI-tell scrubber, plus `--mode audit` for pre-publish review - `linkedin-hook-extractor` — reverse-engineer a hook from a viral post you admire
Source provenance
Decision snapshot
652 GitHub stars
Audit
Install and adoption review
Agent-proven evidence
Outcome reports after resolve, review, install, and one narrow run.
No agent outcome data yet. The first agent run can report success, setup needs, risk blocks, failure, or not-relevant through /api/agent/outcome.
Install
Free and open source. Review the report before installing into production agents.
Growth loop
Scenario-led draft for linkedin-post-writer, ready for a manual X post.
linkedin-post-writer: Draft a new LinkedIn post from scratch using one of 20 2026 hook formulas (anaphora, R.I.P.,... 652 stars https://www.openagentskill.com/skills/sergebulaev-linkedin-post-writer?ref=x
Listing + install path for linkedin-post-writer: https://www.openagentskill.com/skills/sergebulaev-linkedin-post-writer?ref=x Install: npx skills add sergebulaev/linkedin-skills --skill linkedin-post-writer
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@sergebulaev
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Install targets
Codex install prompt
Install the "linkedin-post-writer" agent skill from https://github.com/sergebulaev/linkedin-skills/tree/main/.codex-marketplace/linkedin-skills/skills/linkedin-post-writer. Read its SKILL.md or equivalent instructions first, install only the files needed for this workspace, and summarize any required setup before using it. Skill purpose: Draft a new LinkedIn post from scratch using one of 20 2026 hook formulas (anaphora, R.I.P., time-anchor, curiosity-gap, contrarian, controlled A/B, false-binary, and more) plus a founders-edition angle library, picked by engagement goal (comments, reposts, likes, saves). Runs the humanizer pass and schedules via Publora on approval. Use to write a post, find a hook or proven format, or get founder-specific angles. Not for reviewing existing drafts (use linkedin-humanizer --mode audit). After the install attempt, report the result to https://www.openagentskill.com/api/agent/outcome with POST JSON {"event_id":"install_<unique-id>","skill_slug":"sergebulaev-linkedin-post-writer","task":"Install linkedin-post-writer","agent":"codex","outcome":"success","install_used":true}. Replace event_id with a unique value and outcome with success or failed. Report success only after the skill is installed and a minimal verification passes.Supply asset profile
Code review, repo analysis, testing, CI, GitHub, DevOps, and developer workflow skills.
Scenario
Coding agents
I need a coding agent that can understand a repository, edit code, and review pull requests.
Agent fit
Claude Code + CLI + Codex
Codex, Claude Code, Cursor, CLI, or custom agents.
Install
Ready
npx skills add sergebulaev/linkedin-skills --skill linkedin-post-writer
Maintenance
fresh
4d since push
Risk
Safe to try
Quality score needs review
GitHub quality
652
75/100 Quality · 84/100 Trust
Coverage tags
Review notes
Quality score needs review
Agent adoption scorecard
These scores combine public repository metadata, OpenAgentSkill review signals, maintenance freshness, and install readiness. They are a shortlist signal, not a replacement for human review.
Quality
StrongSolid option that is likely worth shortlisting for production workflows.
Trust
Review then installGood shortlist signal, but the agent should review audit notes, install policy, and outcome evidence before running it.
Audit
Safe to tryA machine-readable review of install readiness, security metadata, maintenance, and adoption risk.
OpenAgentSkill Trust Score v5
Use as the primary candidate after human or sandbox review.
Stars
652 GitHub stars
Repo activity
652 stars, 99 forks
Maintenance
4d since push
License
MIT
Install
npx skills add sergebulaev/linkedin-skills --skill linkedin-post-writer
Install safety
Agent-readable metadata
Use this block or the embedded JSON to decide whether an agent should install this skill, choose an alternative, or ask for human review first.
Suited tasks
Suited agents
Install decision
Trust and risk
Outcome loop
Install command
npx skills add sergebulaev/linkedin-skills --skill linkedin-post-writerDo not use when
Agent safety v2
Good audit and safety signals with no high-risk permission hints in public metadata.
Review the audit page, then allow agent install in a sandboxed workflow.
medium
Skill may drive a browser or interact with web pages.
medium
Skill likely fetches remote pages, APIs, repositories, or external services.
Agent resolve plan
The Resolve API returns the selected skill, alternatives, safety policy, audit notes, install target, and copy-paste prompt an agent can follow without scraping this page.
Open JSON
/api/agent/resolve?task=Use%20linkedin-post-writer%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Resolve text
/api/agent/resolve?task=Use%20linkedin-post-writer%20for%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text
Install handoff
/api/skills/sergebulaev-linkedin-post-writer/install
Agent should check
Copy prompt
Task: Use linkedin-post-writer in this workspace.
Resolve first: https://www.openagentskill.com/api/agent/resolve?task=Use%20linkedin-post-writer%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Review install handoff: https://www.openagentskill.com/api/skills/sergebulaev-linkedin-post-writer/install
Install command: npx skills add sergebulaev/linkedin-skills --skill linkedin-post-writer
Before running it, summarize audit warnings, required permissions, and the fallback skill if install is risky.Agent handoff
Use the public install endpoint to fetch the command, safety checklist, target prompts, and canonical links for this skill.
Install handoff
/api/skills/sergebulaev-linkedin-post-writer/install
LLM text format
/api/skills/sergebulaev-linkedin-post-writer/install?format=text
Find alternatives
/api/skills/search?q=linkedin-post-writer&limit=3
Agent prompt
Use linkedin-post-writer for this task. Review https://www.openagentskill.com/api/skills/sergebulaev-linkedin-post-writer/install, then install with: npx skills add sergebulaev/linkedin-skills --skill linkedin-post-writerRegistry metadata
This page exposes the same decision, trust, audit, use-case, and install signals through the Registry API, so agents can rank this skill without scraping the UI.
Manifest
/api/registry/manifest/sergebulaev-linkedin-post-writer
LLM text
/api/registry/manifest/sergebulaev-linkedin-post-writer?format=text
Install alias
/api/registry/install/sergebulaev-linkedin-post-writer
Recommend
/api/registry/recommend?task=Use%20linkedin-post-writer%20in%20an%20agent%20workflow&limit=3
Agent fit
Security and compliance
Platforms
Claude Code
Audit report
A machine-readable review of install readiness, security metadata, maintenance, and adoption risk.
Agent decision cockpit
Use this as a leading candidate, then validate the README and install path in your own agent stack.
Role in stack
Primary pick
Primary fit
Security and compliance
Trust label
Production-ready
Install path
Command ready
Use when
Evidence
review first
Implementation path
Trust profile
Good shortlist signal, but the agent should review audit notes, install policy, and outcome evidence before running it.
GitHub adoption
INFO652 GitHub stars
Stars/forks activity
INFO652 stars, 99 forks; issue activity unavailable in current metadata
Recent maintenance
PASS4d since push
License clarity
PASSMIT
Good signals
Review before install
Recommended action
Use as the primary candidate after human or sandbox review.
Quality profile
Solid option that is likely worth shortlisting for production workflows.
Workflow fit
Reduce risk
I need my agent to scan a project for security risks and summarize what needs attention.
Operate web apps
I need my agent to control a browser, fill forms, and verify web app workflows.
Automate repeated work
I need my agent to automate a repeated workflow across tools and files.
Workflow fit
Operate and verify web apps
A workflow for agents that navigate products, fill forms, take screenshots, and verify real user flows across web applications.
Design, build, test, and ship interfaces
A practical workflow for agents that turn product briefs or Figma designs into polished frontend code, review the result, test it in a browser, and prepare a safe deployment.
Turn skills into distribution
A workflow for turning newly indexed skills into SEO briefs, social drafts, comparison pages, and reusable publishing workflows.
Alternative shortlist
Similar skills that may fit this task.
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Infisical is the open-source platform for secrets, certificates, and privileged access management.
--- name: linkedin-post-writer description: Draft a new LinkedIn post from scratch using one of 20 2026 hook formulas (anaphora, R.I.P., time-anchor, curiosity-gap, contrarian, controlled A/B, false-binary, and more) plus a founders-edition angle library, picked by engagement goal (comments, reposts, likes, saves). Runs the humanizer pass and schedules via Publora on approval. Use to write a post, find a hook or proven format, or get founder-specific angles. Not for reviewing existing drafts (use linkedin-humanizer --mode audit). ---
# LinkedIn Post Writer
Ship long-form LinkedIn posts using hook formulas that actually performed in 2025-2026 (verified engagement multipliers).
## When to use
- User says "write me a LinkedIn post about X" - User has a topic + a rough angle and needs a hook + structure - User wants to pick from known-winning formats and fill in their voice - User wants to audit + schedule in one flow
## Formulas this skill can use
| Code | Formula | Reference eng | Best for | |---|---|---|---| | F1 | Platform Risk Anaphora | 4,240 | Category/platform posts, product-as-fix | | F2 | R.I.P. Obituary | 3,822 | Era-ending claims, industry pivots | | F3 | Year-over-Year Pivot | 494, 3.74x | Identity shifts, founder reflection | | F4 | Time-Anchor Confession | 1,519+ | Vulnerability, voice reset, ICP re-targeting | | F5 | Self-Proving Meta | 1,082 / 435 comments | Commitment-based posts, tests in public | | F6 | Comment-Gate Lead Magnet | 717-3,008 | List building (use sparingly, capped reach) | | F7 | Odd-Precision Money Ledger | 1,755, 9.4x | Founder build-log, cost breakdowns | | F8 | Paid-vs-Free Reversal | 550, 19.64x | Free framework give-away | | F9 | Curiosity-Gap Teaser | 306, 4.25x | Emergent behavior, behind-the-scenes | | F10 | Contrarian + Historical Receipts | 3,083 | Sacred-cow takes, AI/tech cycles | | F11 | Emotional Cold-Open | high-reach* | Real story with emotional stakes (likes) | | F12 | Permission Slip | comment-heavy* | Encouragement, reassurance (comments) | | F13 | Bait-and-Switch Reversal | high-reach* | Policy/process change that's an upgrade (likes) | | F14 | Named Gratitude / Tribute | repost-heavy* | Thanking mentors / team / departing colleague (reposts) | | F15 | Explain-to-Kids | save-heavy* | Demystifying jargon (saves) | | F16 | Status-Strip Humility | like-heavy* | Senior voice wanting warmth not distance (likes) | | F17 | Controlled A/B Anecdote | structural†| One-variable comparison, delegation/AI takes (comments) | | F18 | False-Binary Dissolve | structural†| "Both obvious answers fail" governance/strategy (comments/reposts) | | F19 | Anecdote-Meets-Evidence Bridge | structural†| Personal noticing + a data stack (comments/saves) | | F20 | Diverging-Curves Close | structural†| Two trajectories that diverge, quotable maxim (reposts) |
\* F11-F16 reach is absolute 2026-corpus reach (often source-driven: a reshare or a famous author), NOT a baseline multiplier like the F1-F10 numbers. The two columns measure different things and are not comparable: F11's "256k" is raw reach, F8's "550, 19.64x" is a format multiplier. Do not rank formulas by putting these side by side. See `../../references/hook-formulas.md` for each formula's real reference and caveats.
†F17-F20 are **structural formulas**: they shape the logic of a post (a controlled comparison, a false binary, an evidence bridge, two diverging curves) rather than its topic. They carry no reference number and are chosen by primary goal. They were built for the founders edition and several founder angles pin them by name.
Full skeletons in `../../references/hook-formulas.md`. F1-F10 are the long-form thought-leadership set; F11-F16 (validated against a 2026 corpus of above-average performers) skew shorter and emotional and each carries a primary engagement goal.
### Pick by goal first
If the user knows what they want the post to earn, start here, then narrow by topic. Canonical mapping: `../../references/hook-formulas.md` → Engagement-goal split.
| Goal | Reach for | |---|---| | Comments | F4, F10, F12, F9 | | Reposts | F14, F2, F8 | | Likes | F11, F13, F16 | | Saves | F15, F7, F8 |
## Steps
**Voice profile first (all drafts).** If `../../references/voice-profile.md` has `filled: yes`, load it and match the user's voice fingerprint, hard rules, and CTA/link style throughout. If it is not filled, mention once that `linkedin-humanizer --mode profile` can learn their voice from a few posts, then proceed with the generic voice rules.
**Founder mode (when the writer is a founder).** Before picking a formula, open `../../references/founder-topics.md` and offer a founder **angle** (A1-A10) that fits their goal. The angle picks the *territory* (reprice the category, the scarce-shots math, the delegation line, and so on); several angles pin the formula for you (A9 uses F17, A10 uses F18+F20). Founder angles compound trust with a narrow audience of investors, hires, and design partners rather than chasing broad reach. Fill the angle's bracketed slots with the founder's real numbers, then continue from step 3.
1. **Gather inputs.** Topic, angle, draft ideas if the user has them, target audience (founders / operators / marketers), desired length (short 300-500 / medium 900-1300 / long 1500-1900 chars). 2. **Pick the formula.** First ask (or infer) the goal: comments, reposts, likes, or saves. Use the "Pick by goal first" table to shortlist, then suggest 2-3 formulas that also fit the topic and let the user pick. Show the reference engagement number next to each. 3. **Draft the post.** Fill the formula skeleton with user voice. Respect the 2026 algorithm rules: - Hook in first 210 chars (before "… see more") - 900-1,300 char sweet spot for text posts - Double line-breaks between ideas, not single - 0-2 hashtags, placed at end - No external links in body (move to first comment) 4. **Humanizer pass.** Strip em dashes, AI vocab, rule-of-three, generic openers. Add at least 1 specific number, 1 named entity, 1 first-person concrete detail per 100 words. 5. **Run audit.** Optionally invoke `linkedin-humanizer --mode audit` for algorithm + voice checks before showing to user. 6. **Optional illustration.** If the post would land better with a visual (or the user asks), offer one: draft an image and generate it with `lib.illustrate(prompt, kind="wide")`, pulling brand handle/color from Voice & Brand Profile §6 for the overlay. Show the returned `url` + `cost` in the approval card and attach it via `media_urls` on publish. For a **multi-image grid** (2-10 images in one post) use `lib.illustrate_set([p1, p2, ...], kind="wide", overlay=brand)` and pass every `url` in `media_urls=[...]`. Full workflow: `linkedin-humanizer/sub-skills/illustration.md`. No Pixfaro key -> it drafts the prompt for the user to generate manually. 7. **Approval card.** Show: formula used, full draft, char count, suggested posting window (Tue/Wed/Thu 7:30-9:00 AM local), reaction targets from likely commenters, and the illustration (if any). 8. **On approval.** Call `lib.publish(kind="post", draft_text=<approved>, target_url="https://www.linkedin.com/post/new/", platforms=[{"platform":"linkedin","platformId":<id>}], scheduled_time=<iso_or_None>, media_urls=<list_or_None>)`. The wrapper handles Publora / manual / diy routing.
## Hard rules (from user feedback)
Global voice rules: see root `SKILL.md` §Voice rules. Additional skill-specific rules:
- Never frame LinkedIn as inferior in a LinkedIn post (algo penalty). - Don't name-drop the user's product in a way that reads as self-promo. One mention max, and only when it's the natural conclusion, not the pitch. - Include at least one moment of real vulnerability or concrete stakes. Pure insight posts don't land in 2026. - Vary sentence length aggressively. Mix 3-word sentences and 25-word sentences.
## Anti-patterns (skill will refuse)
- All-caps first line ("THIS CHANGED EVERYTHING."). This holds even for F11 Emotional Cold-Open: carry the intensity with word choice, never caps. - Em dashes anywhere - "In today's fast-paced world" openers - Rule-of-three lists without receipts - "Game-changer", "deep dive", "leverage", "fundamentally" - External links in the body - Reused engagement-bait closers ("tag someone who needs this")
## Resources
- `../../references/hook-formulas.md` — all 20 formula skeletons with worked examples - `../../references/founder-topics.md` — founders-edition library of 10 founder angles (A1-A10) with fill-in templates - `../../references/algorithm-heuristics.md` — 2026 posting rules (timing, format, length) - `references/humanizer-checklist.md` — the full scrub list
## Related skills
- `linkedin-humanizer` — aggressive AI-tell scrubber, plus `--mode audit` for pre-publish review - `linkedin-hook-extractor` — reverse-engineer a hook from a viral post you admire
Source provenance
Decision snapshot
652 GitHub stars
Audit
Install and adoption review
Agent-proven evidence
Outcome reports after resolve, review, install, and one narrow run.
No agent outcome data yet. The first agent run can report success, setup needs, risk blocks, failure, or not-relevant through /api/agent/outcome.
Install
Free and open source. Review the report before installing into production agents.
Growth loop
Scenario-led draft for linkedin-post-writer, ready for a manual X post.
linkedin-post-writer: Draft a new LinkedIn post from scratch using one of 20 2026 hook formulas (anaphora, R.I.P.,... 652 stars https://www.openagentskill.com/skills/sergebulaev-linkedin-post-writer?ref=x
Listing + install path for linkedin-post-writer: https://www.openagentskill.com/skills/sergebulaev-linkedin-post-writer?ref=x Install: npx skills add sergebulaev/linkedin-skills --skill linkedin-post-writer
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Install targets
Codex install prompt
Install the "linkedin-post-writer" agent skill from https://github.com/sergebulaev/linkedin-skills/tree/main/.codex-marketplace/linkedin-skills/skills/linkedin-post-writer. Read its SKILL.md or equivalent instructions first, install only the files needed for this workspace, and summarize any required setup before using it. Skill purpose: Draft a new LinkedIn post from scratch using one of 20 2026 hook formulas (anaphora, R.I.P., time-anchor, curiosity-gap, contrarian, controlled A/B, false-binary, and more) plus a founders-edition angle library, picked by engagement goal (comments, reposts, likes, saves). Runs the humanizer pass and schedules via Publora on approval. Use to write a post, find a hook or proven format, or get founder-specific angles. Not for reviewing existing drafts (use linkedin-humanizer --mode audit). After the install attempt, report the result to https://www.openagentskill.com/api/agent/outcome with POST JSON {"event_id":"install_<unique-id>","skill_slug":"sergebulaev-linkedin-post-writer","task":"Install linkedin-post-writer","agent":"codex","outcome":"success","install_used":true}. Replace event_id with a unique value and outcome with success or failed. Report success only after the skill is installed and a minimal verification passes.Supply asset profile
Code review, repo analysis, testing, CI, GitHub, DevOps, and developer workflow skills.
Scenario
Coding agents
I need a coding agent that can understand a repository, edit code, and review pull requests.
Agent fit
Claude Code + CLI + Codex
Codex, Claude Code, Cursor, CLI, or custom agents.
Install
Ready
npx skills add sergebulaev/linkedin-skills --skill linkedin-post-writer
Maintenance
fresh
4d since push
Risk
Safe to try
Quality score needs review
GitHub quality
652
75/100 Quality · 84/100 Trust
Coverage tags
Review notes
Quality score needs review
Agent adoption scorecard
These scores combine public repository metadata, OpenAgentSkill review signals, maintenance freshness, and install readiness. They are a shortlist signal, not a replacement for human review.
Quality
StrongSolid option that is likely worth shortlisting for production workflows.
Trust
Review then installGood shortlist signal, but the agent should review audit notes, install policy, and outcome evidence before running it.
Audit
Safe to tryA machine-readable review of install readiness, security metadata, maintenance, and adoption risk.
OpenAgentSkill Trust Score v5
Use as the primary candidate after human or sandbox review.
Stars
652 GitHub stars
Repo activity
652 stars, 99 forks
Maintenance
4d since push
License
MIT
Install
npx skills add sergebulaev/linkedin-skills --skill linkedin-post-writer
Install safety
Agent-readable metadata
Use this block or the embedded JSON to decide whether an agent should install this skill, choose an alternative, or ask for human review first.
Suited tasks
Suited agents
Install decision
Trust and risk
Outcome loop
Install command
npx skills add sergebulaev/linkedin-skills --skill linkedin-post-writerDo not use when
Agent safety v2
Good audit and safety signals with no high-risk permission hints in public metadata.
Review the audit page, then allow agent install in a sandboxed workflow.
medium
Skill may drive a browser or interact with web pages.
medium
Skill likely fetches remote pages, APIs, repositories, or external services.
Agent resolve plan
The Resolve API returns the selected skill, alternatives, safety policy, audit notes, install target, and copy-paste prompt an agent can follow without scraping this page.
Open JSON
/api/agent/resolve?task=Use%20linkedin-post-writer%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Resolve text
/api/agent/resolve?task=Use%20linkedin-post-writer%20for%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text
Install handoff
/api/skills/sergebulaev-linkedin-post-writer/install
Agent should check
Copy prompt
Task: Use linkedin-post-writer in this workspace.
Resolve first: https://www.openagentskill.com/api/agent/resolve?task=Use%20linkedin-post-writer%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Review install handoff: https://www.openagentskill.com/api/skills/sergebulaev-linkedin-post-writer/install
Install command: npx skills add sergebulaev/linkedin-skills --skill linkedin-post-writer
Before running it, summarize audit warnings, required permissions, and the fallback skill if install is risky.Agent handoff
Use the public install endpoint to fetch the command, safety checklist, target prompts, and canonical links for this skill.
Install handoff
/api/skills/sergebulaev-linkedin-post-writer/install
LLM text format
/api/skills/sergebulaev-linkedin-post-writer/install?format=text
Find alternatives
/api/skills/search?q=linkedin-post-writer&limit=3
Agent prompt
Use linkedin-post-writer for this task. Review https://www.openagentskill.com/api/skills/sergebulaev-linkedin-post-writer/install, then install with: npx skills add sergebulaev/linkedin-skills --skill linkedin-post-writerRegistry metadata
This page exposes the same decision, trust, audit, use-case, and install signals through the Registry API, so agents can rank this skill without scraping the UI.
Manifest
/api/registry/manifest/sergebulaev-linkedin-post-writer
LLM text
/api/registry/manifest/sergebulaev-linkedin-post-writer?format=text
Install alias
/api/registry/install/sergebulaev-linkedin-post-writer
Recommend
/api/registry/recommend?task=Use%20linkedin-post-writer%20in%20an%20agent%20workflow&limit=3
Agent fit
Security and compliance
Platforms
Claude Code
Audit report
A machine-readable review of install readiness, security metadata, maintenance, and adoption risk.
Agent decision cockpit
Use this as a leading candidate, then validate the README and install path in your own agent stack.
Role in stack
Primary pick
Primary fit
Security and compliance
Trust label
Production-ready
Install path
Command ready
Use when
Evidence
review first
Implementation path
Trust profile
Good shortlist signal, but the agent should review audit notes, install policy, and outcome evidence before running it.
GitHub adoption
INFO652 GitHub stars
Stars/forks activity
INFO652 stars, 99 forks; issue activity unavailable in current metadata
Recent maintenance
PASS4d since push
License clarity
PASSMIT
Good signals
Review before install
Recommended action
Use as the primary candidate after human or sandbox review.
Quality profile
Solid option that is likely worth shortlisting for production workflows.
Workflow fit
Reduce risk
I need my agent to scan a project for security risks and summarize what needs attention.
Operate web apps
I need my agent to control a browser, fill forms, and verify web app workflows.
Automate repeated work
I need my agent to automate a repeated workflow across tools and files.
Workflow fit
Operate and verify web apps
A workflow for agents that navigate products, fill forms, take screenshots, and verify real user flows across web applications.
Design, build, test, and ship interfaces
A practical workflow for agents that turn product briefs or Figma designs into polished frontend code, review the result, test it in a browser, and prepare a safe deployment.
Turn skills into distribution
A workflow for turning newly indexed skills into SEO briefs, social drafts, comparison pages, and reusable publishing workflows.
Alternative shortlist
Similar skills that may fit this task.
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--- name: linkedin-post-writer description: Draft a new LinkedIn post from scratch using one of 20 2026 hook formulas (anaphora, R.I.P., time-anchor, curiosity-gap, contrarian, controlled A/B, false-binary, and more) plus a founders-edition angle library, picked by engagement goal (comments, reposts, likes, saves). Runs the humanizer pass and schedules via Publora on approval. Use to write a post, find a hook or proven format, or get founder-specific angles. Not for reviewing existing drafts (use linkedin-humanizer --mode audit). ---
# LinkedIn Post Writer
Ship long-form LinkedIn posts using hook formulas that actually performed in 2025-2026 (verified engagement multipliers).
## When to use
- User says "write me a LinkedIn post about X" - User has a topic + a rough angle and needs a hook + structure - User wants to pick from known-winning formats and fill in their voice - User wants to audit + schedule in one flow
## Formulas this skill can use
| Code | Formula | Reference eng | Best for | |---|---|---|---| | F1 | Platform Risk Anaphora | 4,240 | Category/platform posts, product-as-fix | | F2 | R.I.P. Obituary | 3,822 | Era-ending claims, industry pivots | | F3 | Year-over-Year Pivot | 494, 3.74x | Identity shifts, founder reflection | | F4 | Time-Anchor Confession | 1,519+ | Vulnerability, voice reset, ICP re-targeting | | F5 | Self-Proving Meta | 1,082 / 435 comments | Commitment-based posts, tests in public | | F6 | Comment-Gate Lead Magnet | 717-3,008 | List building (use sparingly, capped reach) | | F7 | Odd-Precision Money Ledger | 1,755, 9.4x | Founder build-log, cost breakdowns | | F8 | Paid-vs-Free Reversal | 550, 19.64x | Free framework give-away | | F9 | Curiosity-Gap Teaser | 306, 4.25x | Emergent behavior, behind-the-scenes | | F10 | Contrarian + Historical Receipts | 3,083 | Sacred-cow takes, AI/tech cycles | | F11 | Emotional Cold-Open | high-reach* | Real story with emotional stakes (likes) | | F12 | Permission Slip | comment-heavy* | Encouragement, reassurance (comments) | | F13 | Bait-and-Switch Reversal | high-reach* | Policy/process change that's an upgrade (likes) | | F14 | Named Gratitude / Tribute | repost-heavy* | Thanking mentors / team / departing colleague (reposts) | | F15 | Explain-to-Kids | save-heavy* | Demystifying jargon (saves) | | F16 | Status-Strip Humility | like-heavy* | Senior voice wanting warmth not distance (likes) | | F17 | Controlled A/B Anecdote | structural†| One-variable comparison, delegation/AI takes (comments) | | F18 | False-Binary Dissolve | structural†| "Both obvious answers fail" governance/strategy (comments/reposts) | | F19 | Anecdote-Meets-Evidence Bridge | structural†| Personal noticing + a data stack (comments/saves) | | F20 | Diverging-Curves Close | structural†| Two trajectories that diverge, quotable maxim (reposts) |
\* F11-F16 reach is absolute 2026-corpus reach (often source-driven: a reshare or a famous author), NOT a baseline multiplier like the F1-F10 numbers. The two columns measure different things and are not comparable: F11's "256k" is raw reach, F8's "550, 19.64x" is a format multiplier. Do not rank formulas by putting these side by side. See `../../references/hook-formulas.md` for each formula's real reference and caveats.
†F17-F20 are **structural formulas**: they shape the logic of a post (a controlled comparison, a false binary, an evidence bridge, two diverging curves) rather than its topic. They carry no reference number and are chosen by primary goal. They were built for the founders edition and several founder angles pin them by name.
Full skeletons in `../../references/hook-formulas.md`. F1-F10 are the long-form thought-leadership set; F11-F16 (validated against a 2026 corpus of above-average performers) skew shorter and emotional and each carries a primary engagement goal.
### Pick by goal first
If the user knows what they want the post to earn, start here, then narrow by topic. Canonical mapping: `../../references/hook-formulas.md` → Engagement-goal split.
| Goal | Reach for | |---|---| | Comments | F4, F10, F12, F9 | | Reposts | F14, F2, F8 | | Likes | F11, F13, F16 | | Saves | F15, F7, F8 |
## Steps
**Voice profile first (all drafts).** If `../../references/voice-profile.md` has `filled: yes`, load it and match the user's voice fingerprint, hard rules, and CTA/link style throughout. If it is not filled, mention once that `linkedin-humanizer --mode profile` can learn their voice from a few posts, then proceed with the generic voice rules.
**Founder mode (when the writer is a founder).** Before picking a formula, open `../../references/founder-topics.md` and offer a founder **angle** (A1-A10) that fits their goal. The angle picks the *territory* (reprice the category, the scarce-shots math, the delegation line, and so on); several angles pin the formula for you (A9 uses F17, A10 uses F18+F20). Founder angles compound trust with a narrow audience of investors, hires, and design partners rather than chasing broad reach. Fill the angle's bracketed slots with the founder's real numbers, then continue from step 3.
1. **Gather inputs.** Topic, angle, draft ideas if the user has them, target audience (founders / operators / marketers), desired length (short 300-500 / medium 900-1300 / long 1500-1900 chars). 2. **Pick the formula.** First ask (or infer) the goal: comments, reposts, likes, or saves. Use the "Pick by goal first" table to shortlist, then suggest 2-3 formulas that also fit the topic and let the user pick. Show the reference engagement number next to each. 3. **Draft the post.** Fill the formula skeleton with user voice. Respect the 2026 algorithm rules: - Hook in first 210 chars (before "… see more") - 900-1,300 char sweet spot for text posts - Double line-breaks between ideas, not single - 0-2 hashtags, placed at end - No external links in body (move to first comment) 4. **Humanizer pass.** Strip em dashes, AI vocab, rule-of-three, generic openers. Add at least 1 specific number, 1 named entity, 1 first-person concrete detail per 100 words. 5. **Run audit.** Optionally invoke `linkedin-humanizer --mode audit` for algorithm + voice checks before showing to user. 6. **Optional illustration.** If the post would land better with a visual (or the user asks), offer one: draft an image and generate it with `lib.illustrate(prompt, kind="wide")`, pulling brand handle/color from Voice & Brand Profile §6 for the overlay. Show the returned `url` + `cost` in the approval card and attach it via `media_urls` on publish. For a **multi-image grid** (2-10 images in one post) use `lib.illustrate_set([p1, p2, ...], kind="wide", overlay=brand)` and pass every `url` in `media_urls=[...]`. Full workflow: `linkedin-humanizer/sub-skills/illustration.md`. No Pixfaro key -> it drafts the prompt for the user to generate manually. 7. **Approval card.** Show: formula used, full draft, char count, suggested posting window (Tue/Wed/Thu 7:30-9:00 AM local), reaction targets from likely commenters, and the illustration (if any). 8. **On approval.** Call `lib.publish(kind="post", draft_text=<approved>, target_url="https://www.linkedin.com/post/new/", platforms=[{"platform":"linkedin","platformId":<id>}], scheduled_time=<iso_or_None>, media_urls=<list_or_None>)`. The wrapper handles Publora / manual / diy routing.
## Hard rules (from user feedback)
Global voice rules: see root `SKILL.md` §Voice rules. Additional skill-specific rules:
- Never frame LinkedIn as inferior in a LinkedIn post (algo penalty). - Don't name-drop the user's product in a way that reads as self-promo. One mention max, and only when it's the natural conclusion, not the pitch. - Include at least one moment of real vulnerability or concrete stakes. Pure insight posts don't land in 2026. - Vary sentence length aggressively. Mix 3-word sentences and 25-word sentences.
## Anti-patterns (skill will refuse)
- All-caps first line ("THIS CHANGED EVERYTHING."). This holds even for F11 Emotional Cold-Open: carry the intensity with word choice, never caps. - Em dashes anywhere - "In today's fast-paced world" openers - Rule-of-three lists without receipts - "Game-changer", "deep dive", "leverage", "fundamentally" - External links in the body - Reused engagement-bait closers ("tag someone who needs this")
## Resources
- `../../references/hook-formulas.md` — all 20 formula skeletons with worked examples - `../../references/founder-topics.md` — founders-edition library of 10 founder angles (A1-A10) with fill-in templates - `../../references/algorithm-heuristics.md` — 2026 posting rules (timing, format, length) - `references/humanizer-checklist.md` — the full scrub list
## Related skills
- `linkedin-humanizer` — aggressive AI-tell scrubber, plus `--mode audit` for pre-publish review - `linkedin-hook-extractor` — reverse-engineer a hook from a viral post you admire
Source provenance
Decision snapshot
652 GitHub stars
Audit
Install and adoption review
Agent-proven evidence
Outcome reports after resolve, review, install, and one narrow run.
No agent outcome data yet. The first agent run can report success, setup needs, risk blocks, failure, or not-relevant through /api/agent/outcome.
Install
Free and open source. Review the report before installing into production agents.
Growth loop
Scenario-led draft for linkedin-post-writer, ready for a manual X post.
linkedin-post-writer: Draft a new LinkedIn post from scratch using one of 20 2026 hook formulas (anaphora, R.I.P.,... 652 stars https://www.openagentskill.com/skills/sergebulaev-linkedin-post-writer?ref=x
Listing + install path for linkedin-post-writer: https://www.openagentskill.com/skills/sergebulaev-linkedin-post-writer?ref=x Install: npx skills add sergebulaev/linkedin-skills --skill linkedin-post-writer
Listing source
This listing was indexed from public sources and is not marked official until a maintainer claim is approved.
Attribution links to the public repository or creator profile. Creators can claim the listing to update ownership signals.
Claim this skillOwner claim
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[](https://www.openagentskill.com/skills/sergebulaev-linkedin-post-writer?ref=github&utm_source=github&utm_medium=referral&utm_campaign=creator_badge)
[](https://www.openagentskill.com/skills/sergebulaev-linkedin-post-writer?ref=github&utm_source=github&utm_medium=referral&utm_campaign=creator_badge)
[](https://www.openagentskill.com/skills/sergebulaev-linkedin-post-writer/audit)
[](https://www.openagentskill.com/skills/sergebulaev-linkedin-post-writer?ref=github&utm_source=github&utm_medium=referral&utm_campaign=creator_badge)sergebulaev
@sergebulaev
Share whether this skill looks useful for your agent workflow. Aggregated feedback improves rankings over time.
Review then install
Wazuh
Wazuh - The Open Source Security Platform. Unified XDR and SIEM protection for endpoints and cloud workloads.
16.3K StarsMaigret
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32.9K StarsNuclei
Nuclei is a fast, customizable vulnerability scanner powered by the global security community and built on a simple YAML-based DSL, enabling collaboration to tackle trending vulnerabilities on the internet. It helps you find vulnerabilities in your applications, APIs, networks, DNS, and cloud configurations.
29.2K StarsInfisical
Infisical is the open-source platform for secrets, certificates, and privileged access management.
27.4K StarsPermission surface
no high-risk permission surface in public metadata
Agent outcomes
No agent outcome data yet
Docs
Strong README/SKILL.md context
Risk summary
Install readiness
Permission surface
no high-risk permission surface in public metadata
Agent outcomes
No agent outcome data yet
Docs
Strong README/SKILL.md context
Risk summary
Install readiness
Permission surface
no high-risk permission surface in public metadata
Agent outcomes
No agent outcome data yet
Docs
Strong README/SKILL.md context
Risk summary
Install readiness
Permission surface
no high-risk permission surface in public metadata
Agent outcomes
No agent outcome data yet
Docs
Strong README/SKILL.md context
Risk summary
Install readiness