Files
roboco/docs/rag
0bf0cd69b3 fix(release): close the 0.19.0 scan findings — sandbox mongo tag, flow-verb timeout walls, video hardening (#329)
- mongo:8-alpine → mongo:8 (tag never existed; a mongo-opted project could spawn no agents) + a Docker Hub tag-existence e2e guard for every sandbox engine
- flow-verb timeouts at both walls: shared SLOW_VERBS policy (i_am_done / submit_up / submit_root / open_pr / i_will_work_on get the 900s server budget); the MCP client now outlasts the server budget (+10s headroom, orchestrator-injected env) so agents receive the middleware's clean 504 envelope instead of dying at the old flat 30s client timeout
- cancellation safety: the quality gate kills+reaps its child on CancelledError; create_pr records the PR via a shield-with-wait-out helper so the write can neither be skipped nor race get_db's rollback
- video engine: renderer sidecar isolated on a render-only network, 2g/2cpu caps, 570s render watchdog with exit-on-hang, 512MB tar decompression cap, CEO notification on terminal render failure, reject under the approve mutex (fail-closed on Redis-down)
- dead python-jose dependency removed (drops ecdsa and its unfixable Minerva advisory PYSEC-2026-1325); panel --font-mono now a real monospace stack

Co-authored-by: Renn F <rennf93@users.noreply.github.com>
2026-07-08 03:26:12 +02:00
..
2026-06-29 05:38:21 +02:00

RAG Knowledge Base Documentation

Optimized documentation for the RoboCo AI agent knowledge base. Each file is sized for effective RAG chunking.

Structure

docs/rag/
├── roles/           # Agent role responsibilities
├── workflows/       # Step-by-step task flows
├── standards/       # Coding, security, testing rules
├── architecture/    # System components
├── tools/           # MCP tools reference
└── troubleshooting/ # Common issues and fixes

Organization Principles

  1. One topic per file - Each file covers a single concept
  2. Chunk-friendly - Content fits in 512-1536 token chunks
  3. Self-contained - Each file provides complete context
  4. Actionable - Focus on what agents need to DO

For Agents

When searching the knowledge base:

  • Use roboco_kb_search() for semantic search
  • Use roboco_rag_query() for AI-synthesized answers
  • Use roboco_ask_mentor() for conversational help

See docs/rag/tools/kb-tools.md for the full KB tool reference.