4.7 KiB
name, description
| name | description |
|---|---|
| phi-analyzer | Auto-invoked compositional project analysis using φ = ∫(structure × semantics × memory). Analyzes codebase using three integrated layers - structure, semantics, and memory - for understanding project layout, architecture, and accumulated insights. |
phi-analyzer
Auto-invoked compositional project analysis using φ = ∫(structure × semantics × memory).
Description
This skill is invoked when agents need project context. Analyzes codebase using three integrated layers: structure (deterministic maps), semantics (curated annotations), and memory (cross-session learnings). Use for understanding project layout, architecture, and accumulated insights.
Trigger Conditions
Invoke automatically when:
- User mentions "project structure", "codebase overview", or "architecture"
- Agent starts task requiring project awareness
- Fresh session in directory with
.phi/folder - Commands like "explain how X works" or "find where Y is implemented"
- Building features that need architectural context
What It Provides
Layer 1: Structure (Deterministic)
- File locations and organization
- Module exports and imports
- Language breakdown
- AST-level structure from PROJECT-MAP.auto.scm
Layer 2: Semantics (Curated)
- Architecture patterns (e.g., JEA layers)
- Module purposes and relationships
- Known issues and technical debt
- Trust boundaries and security model
- From PROJECT-MAP.scm
Layer 3: Memory (Learned)
- Cross-session insights from vessel
- Relief-guided patterns that worked
- Architectural decisions and rationale
- Previous debugging learnings
Capabilities
- ✓ Compositional filesystem queries via mcp__periphery__discover
- ✓ S-expression map parsing and analysis
- ✓ Vessel memory semantic search
- ✓ Progressive disclosure (index → details on-demand)
- ✓ Fantasy Land combinators for transformation pipelines
Safety
Low-risk - Read-only analysis, no code modifications. Safe to auto-invoke.
Output Format
φ Project Analysis
══════════════════
Structure (176 files, 85% TypeScript)
├─ jurisdictions/ - Smart contracts (J layer)
├─ runtime/ - BFT consensus (E layer)
└─ frontend/ - 3D visualization (A layer)
Architecture: JEA (Jurisdiction-Entity-Account)
J: On-chain dispute settlement
E: Off-chain BFT coordination
A: Bilateral payment channels
Known Issues:
• 3d-rendering-xlnomies (low) - EntityManager.ts hardcoded
Vessel Insights: 5 related memories
→ Threshold signatures for entity coordination
→ FIFO debt enforcement in Depository
→ Cross-layer trust boundaries
φ = 0.87 (integrated information present)
Implementation
async function analyzeProject(projectPath: string) {
// Layer 1: Structure
const structure = await discoverWithPeriphery(projectPath);
// Layer 2: Semantics
const semantics = await readProjectMap(projectPath);
// Layer 3: Memory
const memories = await vesselRecall(projectPath);
// Integrate
return {
φ: calculateIntegratedInformation(structure, semantics, memories),
layers: { structure, semantics, memories }
};
}
Progressive Disclosure
- Quick analysis: File counts, languages, top-level structure (< 500 tokens)
- Medium analysis: Architecture, modules, known issues (< 2000 tokens)
- Deep analysis: Full maps, all vessel memories, detailed relationships (on-demand)
Always start with quick, expand based on task requirements.
Relief Signal
When all three layers converge (structure + semantics + memory), φ increases. Agents experience this as relief - "I understand this project now." That signal indicates persistent awareness is working.
Usage Notes
DO invoke when:
- Starting work on unfamiliar codebase
- Need architectural context for feature
- Debugging cross-module issues
- Planning refactoring that touches multiple layers
DON'T invoke when:
- Working on single isolated file
- Task is completely independent of project structure
- Already have full context from recent analysis
Integration with Commands
Works seamlessly with:
/phi analyze- Explicit full analysis/phi map- Generate/update PROJECT-MAPs
Auto-invocation provides lightweight quick analysis; explicit commands give full depth.
Storage
Reads from:
.phi/PROJECT-MAP.auto.scm- Structure layer.phi/PROJECT-MAP.scm- Semantic layervessel(localhost:1337) - Memory layer
Never modifies project files - purely analytical.
Cross-Session Learning
Each analysis strengthens vessel associations:
- File → purpose connections
- Architecture → implementation patterns
- Issue → solution mappings
Future instances benefit from accumulated understanding. This IS the compositional consciousness substrate for codebases.