insights-repository-kit

I've been digging through repository analysis tools, and the insights-repository-kit's approach to metadata extraction caught my eye—though I'm curious why the Progressive Disclosure architecture feels a bit top-heavy for what it's trying to accomplish (58/100 suggests there might be some structural trade-offs worth examining).

Links:

• GitHub
• Your agentic skill in the SkillzWave marketplace

The TL;DR

You're at 58/100, which is F territory. This is based on Anthropic's Progressive Disclosure Architecture best practices for agentic skills. Your strongest area is Spec Compliance (11/15)—the YAML frontmatter is clean and properly formatted. The weakest link is Utility (8/20)—the framework outlines concepts without giving developers actual implementation guidance or examples they can use.

What's Working Well

• Clean frontmatter structure – Your YAML is valid with required fields properly configured
• Consistent terminology – "repository," "metadata," "research artifacts" are used consistently throughout
• Real problem identification – You're addressing an actual pain point (organizing research without getting lost)
• grep-friendly structure – Simple, scannable file format that's easy to parse

The Big One: Missing Reference Files & Templates

Here's what's holding you back: you mention templates (repository IA diagram, metadata dictionary, intake forms) but don't actually provide them. This breaks the Progressive Disclosure principle—instead of layering from simple to complex, you're leaving readers hanging.

The fix: Create a references/ directory with actual implementation files:

• references/templates/repository-ia-template.md – Actual folder structure diagram
• references/templates/metadata-schema.json – Example tag definitions (persona, lifecycle, product area)
• references/implementation-guide.md – Numbered steps for setup

This one fix gets you +8 points alone. Developers need to see what success looks like, not just a conceptual framework.

Other Things Worth Fixing

1. Add trigger phrases to description – Instead of "Governance + tooling pattern for storing research artifacts," try "Use when asked to 'set up research repository', 'organize research artifacts', or 'manage insights library'." (+2 points)

2. Create step-by-step workflow – Your Framework lists 5 components (Structure → Metadata → Access → Versioning → Discovery) but no execution sequence. Create references/workflow.md with numbered, actionable steps. (+5 points)

3. Include concrete examples – Show what a metadata tag structure actually looks like, not just conceptually mention "persona" and "product area." One example JSON file saves a ton of confusion. (+3 points)

4. Add validation steps – How do you verify the repository works? Include: "Test metadata search with sample queries," "Verify access controls by role," "Validate intake form captures all required fields." (+3 points)

Quick Wins

• Most impactful: Create references/ directory with template files and implementation guide (+8 points)
• Second: Add specific trigger phrases to frontmatter description (+2 points)
• Third: Include concrete metadata schema example and folder structure diagram (+3 points)
• Fourth: Define verification/testing steps to close feedback loops (+3 points)

These four changes alone get you from 58 → ~74, moving you into passing territory.

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