lore-evolve

/evolve — Snapshot Compilation

When to Trigger

• User explicitly invokes this skill
• Stop hook detects 10+ rounds of accumulated knowledge (hard limit)
• Periodic maintenance (agent notices many uncompiled increments)
• After a major feature completion or PR merge

Purpose

Compile all accumulated increment files into a single, coherent .ai-context/snapshot.md — the agent's "long-term memory" of the project. This is the project's living architecture document that grows more accurate with each compilation.

Process

Step 0: Detect Modular Mode

Check if .ai-context/modules/ directory exists.

• If no → Check if this is the first compile with sufficient module-scoped knowledge. If snapshot.md has knowledge entries with file references that can be mapped to code directories, auto-trigger modular partitioning by executing /lore-modularize before proceeding. Then run legacy evolve if no modules were discovered.
• If yes → Run modular evolve path (Steps 1-8 below).

Step 1: Read Current State

Read:

1. .ai-context/snapshot.md — current snapshot (may not exist for first compile)
2. .ai-context/modules/_index.md — module registry (if modular mode)
3. For each known module, read modules/<name>/knowledge.md
4. All files in .ai-context/increments/ — sorted by date (oldest first)
5. For each module, read modules/<name>/increments/
6. .ai-context/config.yaml — project configuration

Step 2: Route Increments by Domain

For each uncompiled increment (global or per-module):

Determine target:

• Has domain: <module-name> meta field AND module exists in _index.md → target that module's knowledge.md
• No domain field but affected_files paths match a module's code path → infer domain, target that module
• No domain and no file path match → target global snapshot.md
• domain references unknown module → create warning, route to global snapshot.md

Step 3: Conflict Detection (per-target)

For each new increment, check against its target (snapshot.md or modules//knowledge.md):