Anthropic-Cybersecurity-Skills/launch/launch-checklist.md

Launch Day Checklist

Pre-Launch (Night Before)

• Verify all 611 skills have valid SKILL.md with correct YAML frontmatter
• Confirm README.md is polished with clear description, structure, and contributing guide
• Ensure LICENSE file (MIT) is present in repo root
• Verify CONTRIBUTING.md exists with clear skill authoring instructions
• Check that repo description and topics are set on GitHub (cybersecurity, ai, agents, security, open-source)
• Pin the most impressive/representative issues (good first issues, feature requests)
• Confirm GitHub Actions CI passes on main branch
• Pre-write all launch posts (HN, Reddit, Twitter, LinkedIn, Dev.to) and have them ready to paste
• Test all links in launch posts point to correct repo URLs
• Draft responses to anticipated questions (see FAQ prep below)
• Set up monitoring: GitHub notifications on, email alerts for new issues/stars
• Ensure the repo is public (not private or internal)

Launch Morning

Hour 0: Go Live

• 6:00 AM Pacific / 9:00 AM Eastern: Post Show HN on Hacker News
  • Title: "Show HN: 611+ Cybersecurity Skills for AI Agents (agentskills.io open standard)"
  • Paste body from launch/hacker-news.md
• Immediately after HN: Post first Reddit post to r/netsec
• Post Twitter/X thread (all 7 tweets)
• Post LinkedIn article
• Bookmark HN post URL for monitoring

Hour 1-2: First Engagement Wave

• Monitor HN for comments -- respond to every comment within 1 hour
• Be technical in HN responses: reference specific skill files, tool commands, MITRE technique IDs
• Do NOT ask for upvotes anywhere -- ever
• Post to r/cybersecurity (2 hours after r/netsec post)

Hour 3-4: Second Wave

• Post to r/blueteamsec
• Post to r/hacking
• Continue monitoring and responding to HN and Reddit comments
• Track GitHub stars, forks, and issues

Hour 5-6: Third Wave

• Post to r/redteamsec
• Post to r/artificial
• Post to r/opensource
• Publish Dev.to article

Throughout the Day

• Respond to every GitHub issue within 2 hours
• Respond to every Reddit comment with substance
• Thank anyone who stars or shares the repo
• If any post gains traction, share it on Twitter with a brief note
• Monitor for any negative feedback or valid criticisms -- address them transparently

End of Day 1

• Record metrics: GitHub stars, forks, issues, traffic (Insights tab)
• Record metrics: HN points and rank position, Reddit upvotes per post
• Identify top questions/concerns from community -- plan content to address them
• Merge any quick-win PRs that come in (shows the project is active and welcoming)
• Post a "Day 1" update on Twitter if there's traction: "Thank you for the response. X stars, Y issues filed, here's what we're working on next."
• Join Discord servers (see launch/discord-servers.md) and introduce yourself and the project

Day 2+

• Send press email to Help Net Security (see launch/help-net-security-email.md)
• Continue engaging with all platforms daily for at least 1 week
• Post in Discord servers where appropriate (don't spam -- contribute value first, then mention the project)
• Write follow-up content based on community feedback:
  • Blog post addressing top questions
  • Tutorial: "How to contribute a skill in 10 minutes"
  • Deep dive into a specific subdomain
• Reach out to security influencers who engaged with the launch posts
• Track weekly metrics: stars, forks, contributors, issues opened/closed
• Plan the first community call or AMA if there's sufficient interest
• Submit to security newsletters (tl;dr sec, SANS NewsBites, etc.)
• Look for podcast/webinar opportunities if the project gets 500+ stars

FAQ Prep (Anticipated Questions)

"Aren't these just runbooks/cheat sheets?"

They're structured for machine consumption, not just human reading. The YAML frontmatter provides routing metadata that lets an agent know WHEN to use a skill, and the body provides the exact HOW. A cheat sheet doesn't have activation conditions or progressive disclosure.

"Can AI actually do security work?"

Not autonomously, and that's not the goal. These skills make AI agents useful assistants -- like giving a junior analyst a detailed procedure library. The human makes decisions; the agent provides precise, tool-specific guidance.

"Why not just fine-tune a model?"

Fine-tuning is expensive, hard to audit, and requires retraining for every update. A skill file can be reviewed, version-controlled, and updated by any practitioner. It's also transparent -- you can read exactly what the agent will do.

"Is this just for Claude/Anthropic?"

No. The agentskills.io format is agent-agnostic. Any AI agent that can read files can use these skills. The format is intentionally simple (YAML + Markdown) for maximum compatibility.

"How do you ensure quality?"

Every skill references real tools with real commands. Contributors are expected to be practitioners. The community review process catches errors. Bad skills get issues filed against them.