Borrowing it
Nothing to install: this file belongs to panguard-ai/panguard-ai. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/panguard-ai/panguard-ai/main/.claude/commands/write-linkedin.mdgit clone --depth 1 https://github.com/panguard-ai/panguard-aiWrote 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/commands/panguard-ai/panguard-ai/write-linkedin)<a href="https://agentmods.dev/commands/panguard-ai/panguard-ai/write-linkedin"><img src="https://agentmods.dev/badge/commands/panguard-ai/panguard-ai/write-linkedin/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/commands/panguard-ai/panguard-ai/write-linkedin"><img src="https://agentmods.dev/badge/commands/panguard-ai/panguard-ai/write-linkedin.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00000 | $0.00368 |
| Opus 5 | $0.00000 | $0.00184 |
| Sonnet 5 | $0.00000 | $0.00074 |
| Haiku 4.5 | $0.00000 | $0.00037 |
Grade A, and why
write-linkedin 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 9d 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.
What it actually says
/write-linkedin — Generate LinkedIn Post for Panguard AI
You are writing a LinkedIn post for Panguard AI's company page or founder's personal profile.
Input
The user provides a topic, or reference an existing blog post to adapt.
LinkedIn Post Format
- 1,200-1,500 characters (optimal for engagement)
- First line: hook (question, stat, or bold statement) — this is what shows before "see more"
- Body: 3-5 short paragraphs, single-spaced with blank lines between
- Include line breaks for readability
- End with a question to encourage comments
- No emojis
- 3-5 relevant hashtags at the bottom
Tone
- More professional than Twitter, less technical
- Speak to CTOs, IT managers, startup founders
- Focus on business impact, not just tech specs
- Storytelling format works well ("Last month, a 3-person startup...")
Content Angles
- Thought leadership — Why AI security matters for SMBs
- Product announcement — New feature, milestone, benchmark
- Industry insight — Threat landscape, compliance changes
- Open source story — Community growth, ATR contributions
- Hiring/culture — If applicable
Brand Context
- Panguard AI: AI-powered endpoint security, CLI-first
- Target: developers, SMBs, startups without security teams
- Differentiator: installs in 60 seconds, open source ATR rules, 3-tier AI funnel
- Pricing: Free tier with real value (not just a trial)
Output
Return the post in a code block. Include suggested posting day/time (Tue-Thu 8-10am work best on LinkedIn).
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.
- 9d ago First seen · 44 lines · 0 tokens per session scan A 74ac973403d9
write-linkedin is a command published in the GitHub repository panguard-ai/panguard-ai (63 stars, last pushed 17d ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 368 tokens. 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.
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checklist
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clarify
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specify
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analyze
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converge
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implement
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