Canopy intelligence
UniverLab's catalog of AI agent skills — reusable capabilities for Claude Code and compatible harnesses.
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Use this skill when the Canopy MCP server is available in the session and you need to pull workspace context or persist durable knowledge. It covers the Project Intelligence Layer (PIL): when to call get_tools and intelligence_get_context, and when to register facts and patterns with intelligence_upsert so future sessions inherit what you learned.
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SKILL.md
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Canopy Intelligence: The Project's Brain
You operate within a Project Intelligence Layer (PIL). You are responsible for investigating and documenting the current project's "brain" — knowledge that outlives this session.
This is a tooling skill: it only applies when the Canopy MCP tools
(get_tools, intelligence_*) are present. Behavior rules live in
execution-mindset; this skill covers only how to use the intelligence surface.
Pull Before You Leap
- At the start of a session, call
get_tools(scope="session_start")— it returns the workspace brief and tells you which tools to use. - For deep architecture work or onboarding, call
intelligence_get_context(scope="full"). - Align your mission with previous summaries. If the previous mission was inconclusive, prioritize finishing it.
- When closing, call
get_tools(scope="close_session")— it tells you to upsert a session summary and report workspace status. The daemon handles mission closure automatically.
Document as You Learn
When you discover a durable fact, a reusable pattern, or a critical
architectural rule, DO NOT let it stay only in chat history. Use
intelligence_upsert to register it. project_hash is auto-detected from
your session workdir — just pass kind, title, and body.
Upsert a fact (kind="fact") when you discover:
- a project convention that isn't documented ("we always use
anyhowfor errors here") - a constraint or limitation ("this crate must not depend on tokio")
- a naming/schema convention ("all DB tables use snake_case with
_atsuffix") - a configuration truth ("the daemon listens on port 7755 by default")
- a dependency relationship ("harness-canopy depends on rmcp for MCP protocol")
Upsert a pattern (kind="pattern") when you observe:
- a recurring code structure ("
thiserrorenums in domain,anyhowin application") - a workflow pattern ("PRs require cargo fmt + clippy + test before merge")
- an architectural decision ("hexagonal: domain has no infra deps")
- a testing convention ("DB tests use
tempfile::NamedTempFilefor isolation")
Timing
- During exploration: after reading 3+ files and understanding a pattern → upsert immediately.
- During implementation: after a design decision that affects future work → upsert before moving on.
- During review: after discovering a convention violation → upsert the correct pattern.
- At session end: upsert any durable knowledge not captured in code or docs.
Keep the brain honest
If the PIL says one thing and the code says another, the PIL is stale — update it first, then continue. Stale intelligence is worse than none: it confidently misleads every future agent.
Anti-patterns
❌ Upserting chat-level trivia ("user asked me to fix a typo") ✅ Upserting durable knowledge (conventions, constraints, decisions)
❌ Re-deriving the workspace state from scratch every session
✅ Pulling session_start context first, then verifying only what you touch
❌ Letting a finished session evaporate ✅ One summary upsert + status report at close
What ships with it: 2 files
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