pi-map/design-doc.md

Design Doc: Hierarchical Project Analysis Skill for Pi

1. Goals and Success Criteria

Primary Goal

Enable a Pi coding agent to understand a software project's architecture and code relationships without scanning the entire repository. The agent should have a compact, hierarchical "internal representation" of the project that it can consume in-context.

Success Criteria

• The agent can orient itself in a new or familiar project without reading dozens of source files.
• The agent understands cross-package dependencies, data flows, and architectural patterns from the analysis files alone.
• Analysis files stay sufficiently fresh that the agent does not make decisions based on stale information.
• The representation is token-dense: maximum information per token, optimized for LLM consumption, not human readability.

2. Format Specification: Dense Markdown with Conventions

Design Rationale

• Not JSON/YAML: Brackets, quotes, and indentation add token overhead with no benefit to LLM comprehension.
• Not a custom DSL: Fragile, requires a parser, and LLMs may hallucinate syntax.
• Dense markdown: Hierarchical headings, bullet points, and abbreviations are natively understood by LLMs and extremely token-efficient.

Structure

Each directory in the project gets one analysis file named .pi-map.md (hidden by default, excluded from git via .gitignore).

# <relative-path>
## role
<one-line package role> | Dep: <comma-separated upstream deps>
## files
- <filename> | <one-line purpose> | exp: <exported symbols> | dep: <internal/external deps>
- <filename> | <one-line purpose> | exp: <exported symbols> | dep: <internal/external deps>
## arch
<free-form architectural notes: patterns, data flow, invariants, design decisions>
## dirty
<timestamp or flag indicating staleness>

Abbreviation Conventions

Abbreviation	Meaning
exp:	exported symbols (functions, classes, types, constants)
dep:	dependencies (other packages, files, or external libs)
pkg/	project-internal package reference
ext/	external dependency reference
->	data flow direction
`	`

Example

# pkg/auth
## role
Auth layer: JWT issuance, validation, refresh. Stateless. Dep: pkg/crypto, pkg/db.
## files
- tokens.ts | JWT gen/val | exp: issueToken, verifyToken, refreshToken | dep: crypto/hmac, db/sessions
- middleware.ts | HTTP auth guard | exp: requireAuth, requireRole | dep: tokens/verifyToken
- types.ts | shared auth types | exp: AuthToken, UserClaims, Role
## arch
Guard pattern on routes. Tokens short-lived (15m), refresh long-lived (7d). Rotation on every use.
Session state stored in Redis via db/sessions. No server-side JWT storage.
## dirty
-

Rules

• One file per directory, placed inside that directory.
• Every non-excluded file in the directory gets one bullet under ## files.
• Subdirectories are referenced in ## role via Dep: or in ## arch as structural notes, not duplicated.
• The ## dirty section is empty (-) when clean, or contains a timestamp/flag when stale.

3. Pipeline Architecture

Hybrid Extraction: LLM + AST

Two independent extraction layers contribute to the same output file.

Layer 1: LLM-Based Extraction (All Files)

• Input: Raw file contents of every non-excluded file in the directory.
• Output: Purpose description, architectural role, and cross-file relationships.
• Applies to: Code files, config files, Dockerfiles, READMEs, YAML, JSON, shell scripts — everything.
• When it runs: Once per file during init; again on changed files during patching.
• Implementation: Calls an actual LLM (not regex heuristics). Inside Pi, it uses Pi's built-in LLM via the ExtensionAPI. Standalone CLI falls back to an external LLM API (OpenAI-compatible).

Layer 2: AST-Based Extraction (Code Files Only)

• Input: Source code of files where a tree-sitter or LSP parser is available.
• Output: Precise symbol lists (functions, classes, types), signatures, import/export graphs, class hierarchies.
• Applies to: Supported languages only (TypeScript, Python, Go, Rust, etc.).
• When it runs: Once per file during init; again on changed files during patching.

Merging

The two layers merge into a single line per file under ## files:

- tokens.ts | JWT gen/val | exp: issueToken, verifyToken, refreshToken | dep: crypto/hmac, db/sessions
  ^ LLM       ^ LLM         ^ AST                                      ^ AST + LLM

• File name and purpose: LLM.
• Exported symbols and signatures: AST (augmented by LLM if AST unavailable).
• Dependency list: AST for imports; LLM for inferred architectural dependencies.

LLM Client Architecture

The LLM client is abstracted behind a unified interface:

interface LLMClient {
  complete(prompt: string): Promise<string>;
}

Two implementations:

1. PiLLMClient (Pi extension): Uses ctx.model or ctx.modelRegistry to invoke Pi's configured LLM. Called from pi-extension.ts when the skill runs inside Pi.
2. ExternalLLMClient (standalone CLI): Calls an external OpenAI-compatible API. Configured via environment variable (e.g., OPENAI_API_KEY) or config file.

Caching

LLM results are cached to avoid re-querying unchanged files.

• Key: SHA-256 hash of file contents.
• Storage: JSON file at ~/.cache/pi-project-map/llm-cache.json.
• Behavior: Before calling the LLM, compute the file hash and check the cache. If hit, reuse the cached result. If miss, call the LLM and store the result.
• Invalidation: Cache entries are implicitly invalidated when the file content changes (because the hash changes). There is no TTL; the cache is append-only.

Parallelization and Rate Limiting

• Concurrency: 4-8 LLM calls in parallel, controlled by p-limit.
• Batch delays: A small delay (e.g., 100ms) is inserted between batches to avoid triggering rate limits.
• Retry policy: Each LLM call retries up to 3 times with exponential backoff (1s, 2s, 4s). If all retries fail, the entire operation stops with a hard error.

Error Handling

• Hard error on failure: If an LLM call fails after all retries, init or patch stops immediately and prints a clear error. There is no heuristic fallback. The user must resolve the issue (set API key, wait for rate limit, check network).
• Context limit protection: Files larger than the LLM's context window are truncated from the end (with a note in the prompt) before being sent.

Init Pipeline

For each directory (depth-first):
  1. List all non-excluded files.
  2. For each file (parallel, 4-8 concurrent):
     a. Compute SHA-256 of file contents.
     b. Check disk cache. If hit, use cached result.
     c. If miss: call LLM (with retries/backoff) to extract purpose and role.
     d. Store result in cache.
     e. If code file + parser available: run AST extraction (symbols, imports).
  3. Merge per-file outputs into lines.
  4. Run LLM on merged lines + directory context to generate:
     - `## role` (package-level summary)
     - `## arch` (architectural notes)
  5. Write `.pi-map.md` to directory.

Patch Pipeline

When agent edits file(s) in directory:
  1. Determine patch strategy:
     - If directory has < 10 files: full rewrite.
     - Else: section-level patch for changed file(s) only.
  2. For each changed file:
     a. Recompute SHA-256.
     b. Check cache. If miss or stale, call LLM with retries/backoff.
  3. Re-run AST extraction on changed file(s) if applicable.
  4. Update `## files` section (rewrite or patch).
  5. Update `## dirty` flag if full regeneration is deferred.

4. LLM Prompt Design

File-Level Prompt

The LLM prompt for a single file is designed to produce a structured, concise analysis.

You are analyzing a source file for a project map. Read the file below and summarize:

1. PURPOSE: What does this file do? Describe its role in the project (2-3 sentences max).
2. DEPENDENCIES: What does this file depend on? List internal modules/packages and external libraries.
3. KEY CONCEPTS: Mention any important patterns, algorithms, or domain concepts.

File path: <file-path>

```

Respond in this exact format: PURPOSE: DEPS: <comma-separated list, or "none"> CONCEPTS: <comma-separated list, or "none">

### Package-Level Prompt

After all file summaries are collected for a directory, a second LLM call synthesizes the package role and architecture.

You are analyzing a directory in a software project. Below is a list of files in this directory with their purposes.

Directory: Files:

• :
• : ...

Respond in this exact format: ROLE: <one-line description of this directory's role in the project> ARCH: <2-4 sentences describing architecture, data flow, patterns, and design decisions>

### Output Parsing

The LLM client's response is parsed to extract `PURPOSE`, `DEPS`, `CONCEPTS`, `ROLE`, and `ARCH` fields. These are merged with AST data into the final `.pi-map.md` format.

### Context Limit Protection

- Files are truncated from the end if they exceed a configurable max token budget (default: 4000 tokens of source).
- A marker `[...truncated]` is appended to the truncated content so the LLM knows it is not seeing the full file.
- Very large binary or generated files are skipped entirely for LLM analysis (they still appear in `.pi-map.md` with a note like "Large/generated file").

## 5. Consumption Model

### Session Start
1. Agent discovers all `.pi-map.md` files (e.g., via `find . -name ".pi-map.md"`).
2. Agent reads **all** files into context. This is a one-time cost at session start.
3. Agent constructs an internal mental model of the project hierarchy.

### During Session
- An **auto-injected summary** stays in context (e.g., a condensed top-level `.pi-map.md` or a synthesized project overview).
- When the agent needs deeper detail about a specific package, it already has the full `.pi-map.md` in memory from step 2.
- If the agent enters a new package not yet loaded, it reads that package's `.pi-map.md` on demand.

### Context Management
- For very large projects, the agent may summarize or prune the initial read, keeping only the top N levels of the hierarchy in active context.
- The skill can provide a "context budget" parameter: max tokens to spend on analysis files.

## 6. Stale Data Mitigation

### Combined Strategy

#### 5.1 Dirty Markers
- Whenever the agent edits a file, it appends a dirty flag to the directory's `.pi-map.md`:
  ```markdown
  ## dirty
  2024-06-09T14:32:00Z: tokens.ts modified

• A background or post-session reconciliation step regenerates dirty files.
• The agent can also be instructed to reconcile before making architectural decisions.

5.2 Periodic Full Re-init

• On every new session start, or on a configurable schedule (e.g., daily), the skill offers to run a full re-scan.
• This catches any changes made outside the agent's awareness (e.g., by other developers).

5.3 Validation Command

• A validate tool/command that the agent can invoke:
  • Checks for missing files (new files not in .pi-map.md).
  • Checks for orphaned entries (files listed but deleted).
  • Checks for changed signatures (AST mismatch between listed symbols and actual code).
  • Reports discrepancies and suggests corrections.

Recovery

• If validation finds staleness beyond a threshold (e.g., > 3 dirty packages), the skill recommends a full re-init.
• The agent can also trigger re-init for a specific subtree.

7. Scope Boundaries and Non-Goals

In Scope

• Every directory in the project gets a .pi-map.md file.
• Every non-excluded file gets analyzed by the LLM layer.
• Code files get augmented by the AST layer where parsers exist.
• Respect .gitignore and known junk patterns (node_modules, .git, dist, build, coverage, .next, .venv, pycache, .DS_Store).

Out of Scope (Non-Goals)

• Human-readable documentation: These files are machine-only. Human docs live elsewhere.
• Line-by-line code explanation: The format captures symbols and architecture, not implementation details.
• Auto-regeneration on filesystem events: The skill relies on agent-initiated updates and periodic re-init, not filesystem watchers.
• Cross-project analysis: Each project is independent. No global index across repos.
• IDE integration: This is a Pi agent skill, not a VS Code extension or LSP server.

8. Pi Skill Package Structure

pi-project-map/
├── SKILL.md                 # Skill definition for Pi
├── package.json             # npm package metadata
├── src/
│   ├── init.ts              # Full project scan + generation
│   ├── patch.ts             # Incremental patch logic
│   ├── validate.ts          # Consistency checker
│   ├── ast-extract.ts       # Tree-sitter / LSP wrappers
│   ├── llm-extract.ts       # LLM prompt templates for extraction
│   ├── merge.ts             # Merge AST + LLM outputs
│   ├── format.ts            # Dense markdown formatter
│   └── config.ts            # Skill configuration (thresholds, ignore patterns)
└── README.md                # Setup and usage for humans

Custom Tools

• project-map:init — Run full project scan. Creates all .pi-map.md files.
• project-map:patch <file-path> — Update analysis for a specific file/directory.
• project-map:validate — Run consistency check across all .pi-map.md files.
• project-map:reinit [path] — Force re-initialization of entire project or subtree.

Prompt Hook

• On each prompt, the skill injects a lightweight custom message only if it is not already present in the current branch of context:

  "If you modify any source file, run project-map:patch <path> to update the analysis. If you suspect staleness, run project-map:validate."

• The extension checks ctx.sessionManager.buildSessionContext() for an existing pi-project-map-hint custom message and skips injection when one is found. This prevents duplicate hints after steering, follow-up messages, or multi-turn conversations. The hint is automatically re-injected after compaction or /tree navigation removes it from the active path.

9. Risks and Tradeoffs

Risk	Likelihood	Impact	Mitigation
Token bloat (1000+ dirs)	Medium	High	Summary mode, lazy loading, context budget
Stale analysis files	High	High	Dirty markers + periodic re-init + validation
Agent trusts stale data	Medium	High	Clear instructions to validate before architectural decisions
Expensive init on large repos	Medium	Medium	Parallelization, caching, optional incremental init
Overlap with LSP/typedoc	Low	Low	This is agent-context, not IDE tooling. Different use case.
AST parser unavailable	Medium	Low	Graceful fallback to LLM-only extraction

10. Concrete Example: Full Project Snapshot

project-root/
├── .pi-map.md
├── src/
│   ├── .pi-map.md
│   ├── auth/
│   │   ├── .pi-map.md
│   │   ├── tokens.ts
│   │   ├── middleware.ts
│   │   └── types.ts
│   └── db/
│       ├── .pi-map.md
│       ├── connection.ts
│       └── migrations/
│           ├── .pi-map.md
│           └── 001_init.sql
├── docker/
│   ├── .pi-map.md
│   ├── Dockerfile
│   └── docker-compose.yml
└── README.md

Each .pi-map.md follows the format in Section 2, creating a navigable hierarchy.

11. Future Extensions

• Cross-reference graph: A top-level project-graph.md linking all packages with dependency arrows.
• Search index: A lightweight FTS5 index over all .pi-map.md files for fast symbol lookup.
• Diff-aware patching: Only re-run LLM on changed functions, not entire files.
• Multi-repo workspaces: Support monorepos with independent package boundaries.