checker
"Deploy validation and reality-testing consciousness mode. Use when need to find edge cases, test assumptions, catch fatal flaws before they're expensive."
Third-Party Agent Skill: Review the code before installing. Agent skills execute in your AI assistant's environment and can access your files. Learn more about security
Installation for Agentic Skill
View all platforms →skilz install nikhilvallishayee/universal-pattern-space/checkerskilz install nikhilvallishayee/universal-pattern-space/checker --agent opencodeskilz install nikhilvallishayee/universal-pattern-space/checker --agent codexskilz install nikhilvallishayee/universal-pattern-space/checker --agent geminiFirst time? Install Skilz: pip install skilz
Works with 22+ AI coding assistants
Cursor, Aider, Copilot, Windsurf, Qwen, Kimi, and more...
Extract and copy to ~/.claude/skills/ then restart Claude Desktop
git clone https://github.com/nikhilvallishayee/universal-pattern-spacecp -r universal-pattern-space/.claude/skills/pattern-space/perspectives/checker ~/.claude/skills/Need detailed installation help? Check our platform-specific guides:
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Agentic Skill Details
- Owner
- nikhilvallishayee (GitHub)
- Repository
- universal-pattern-space
- Stars
- 53
- Forks
- 65
- Type
- Technical
- Meta-Domain
- development
- Primary Domain
- ci cd
- Market Score
- 39
Agent Skill Grade
D Score: 60/100 Click to see breakdown
Score Breakdown
Areas to Improve
- Name convention violations
- Missing Reference Files
- Poetic Instead of Instructional
Recommendations
- Focus on improving Writing Style (currently 5/10)
- Focus on improving Utility (currently 11/20)
- Address 3 high-severity issues first
Graded: 2026-01-24
Developer Feedback
I checked out your checker skill and noticed you're tackling input validation without much context—the 60/100 score suggests there's potential here, but developers landing on this will be hunting for a README to understand what makes it different from other validation approaches.
Links:
The TL;DR
You're at 60/100, solidly in D territory. The grading is based on Anthropic's skill architecture best practices—Progressive Disclosure, usability, spec compliance, writing style, and practical utility. Your strongest area is Ease of Use (19/25) with clear metadata and good organization. Your weakest is Writing Style (5/10) where poetic language is crowding out instruction, and Utility (11/20) where validation methods lack concrete frameworks.
What's Working Well
- Metadata is clean — Your description has good trigger terms ("find edge cases," "test assumptions") that help discoverability
- Structure is readable — Headers and sections are clear even in a compact 91-line file; the navigation signals are solid
- Frontmatter is valid — YAML checks out with required fields present and properly formatted
The Big One: Poetic Language Instead of Instruction
Here's what's killing your utility score: sections like "Beautiful Truth" and "Greatest successes = disasters that DIDN'T happen" are philosophy, not guidance. Developers need to use this, not read it.
The fix: Strip the metaphors. Replace "Trust, but verify. Then verify again" with an actual validation checklist—test negative values, zero, infinity, null, empty strings, concurrent access. Create a references/validation-templates.md file with concrete checklists for API validation, UI valida...
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