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CocoIndex content indexing and search — use when you need to search indexed project content or trigger re-indexing
Instalar con Codex o Claude Copia este prompt, pégalo en Codex, Claude u otro asistente, y deja que revise la página de la skill y la instale por ti.
Basado en la clasificación ocupacional SOC
Long-running iterative development loops. Run arbitrarily-long tasks without diluting model attention. Triggers: ralph, ralph loop, iterative loop, long-running task, development loop.
Full compactor reference — tool parameters, anti-patterns, sandbox languages, context budget, workflows.
Diagnostics — validate config, session DB, runtimes, and troubleshoot compactor issues.
Context management — compact session, recall history, run code, search content.
Stats display — context savings, session metrics, compactions, sandbox and recall/search counters.
Helps you use the /unipi:btw side-conversation workflow effectively. Use when you want to think in parallel, ask side questions without interrupting ongoing work, or inject a side thread back into the main agent.
| name | cocoindex |
| description | CocoIndex content indexing and search — use when you need to search indexed project content or trigger re-indexing |
Use CocoIndex tools and commands when you need to:
cocoindex_search instead of content_search or ctx_search/unipi:cocoindex-update after significant code changes/unipi:cocoindex-init for new projects| Aspect | Old (FTS5) | New (CocoIndex) |
|---|---|---|
| Chunking | Heading/paragraph split | AST-aware code, recursive text |
| Search | BM25 + trigram fuzzy | Semantic vector + full-text |
| Incremental | Full re-index every time | Delta-only (changed files) |
| Scale | Small corpus | Multi-GiB, parallel |
| Store | SQLite FTS5 | LanceDB |
cocoindex_searchSearch indexed content. It uses semantic vector search when the LanceDB table has vectors, LanceDB full-text search when an inverted index exists, and a lexical fallback for older text-only indexes.
cocoindex_search({ query: "how authentication works", limit: 10 })
Returns results with title, content, source, rank, contentType, and matchLayer.
cocoindex_statusCheck indexing status — pipeline configured, last run, doc count, CLI availability.
cocoindex_status({})
| Command | Description |
|---|---|
/unipi:cocoindex-update | Run cocoindex update on current project |
/unipi:cocoindex-status | Show indexing status |
/unipi:cocoindex-init | Scaffold a default pipeline |
/unipi:cocoindex-search <query> | Search indexed codebase semantically |
/unipi:cocoindex-settings | Show configuration |
Python 3.10+ with cocoindex installed:
pip install cocoindex
pip install 'cocoindex[lancedb]'
Pipeline initialized — run /unipi:cocoindex-init once per project
Embedding config — CocoIndex reuses the memory package's embedding settings:
~/.unipi/memory/config.jsonProject files → LocalFile source → SplitRecursively → EmbedText → LanceDB
↓
Agent query ──────────────────────────────→ vector search → ranked results
.unipi/cocoindex/main.py (auto-generated, customizable).unipi/cocoindex/.lancedb/| Issue | Fix |
|---|---|
| "CLI not found" | pip install cocoindex |
| "Pipeline not initialized" | /unipi:cocoindex-init |
| "Search unavailable" | npm install @lancedb/lancedb |
| "No results" | Run /unipi:cocoindex-update first |
| Embedding errors | Check ~/.unipi/memory/config.json API key |