Wiki Enrich Skill

Enriches stub pages in the ld-wiki learning design knowledge base.

Quick Start

1. Read stub: Find and read the page to enrich.
2. Read exemplar: Check references/exemplars.md for the correct model.
3. Research: Use Google Search for 3-5 peer-reviewed sources (APA + DOI). For the Examples section, find and confirm real URLs for any publicly accessible product, platform, or program.
4. Draft: Match exemplar density and voice. Use OKF cross-links, relative to the page being written: slug.md for a page in the same folder, ../folder/slug.md for a page in a different folder. Verify each link's slug exists by checking the relevant folder's index.md before writing it.
5. Evidence: Apply tags from references/evidence-tags.md.
6. Finalize: Run python3 scripts/build_indexes.py to regenerate index.md, and python3 scripts/log_revision.py <page> --by gemini --type content --desc "..." to append to log.md and update the page's generated field.

Key Rules

• Cross-links: Always use relative markdown links: [Display Name](slug.md) for the same folder, [Display Name](../folder/slug.md) for a different one. Confirm slugs exist in the wiki before using them.
• Evidence Tags: Link tags to claims: [Claim statement](../claims/slug.md) [+M].
• Sources: Use real DOIs. In the Examples section, use markdown [Name](URL) links for publicly accessible products and programs — search for the URL if you don't know it. Only omit a link if the example has no public URL.
• Constraints: Use [-] or [~] tags for constraints.
• Missing pages: If you reference a theory, element, or principle that has no wiki page yet, create a minimal stub (OKF frontmatter + # Title only, status: draft) in the correct folder and add it to that folder's index.md.

Batch enrichment

When asked to enrich multiple pages of a type:

1. List all status: draft pages in the folder.
2. Confirm count with user.
3. Process one at a time.
4. Create stubs for new cross-links.
5. Run python3 scripts/build_indexes.py once at the end.

See references/operating-guide.md for full schemas.