Systematically populate the Forgetful knowledge base using Serena's LSP-powered symbol analysis for accurate, comprehensive codebase understanding.
Systematically encodes codebases into a searchable knowledge base using LSP-powered symbol analysis for comprehensive project understanding.
/plugin marketplace add rjmurillo/ai-agents/plugin install project-toolkit@ai-agentsThis skill inherits all available tools. When active, it can use any tool Claude has access to.
Transform an undocumented codebase into a rich, searchable knowledge repository using Serena's LSP-powered symbol analysis.
| Trigger Phrase | Operation |
|---|---|
encode this repository | Full 12-phase encoding pipeline |
populate forgetful with this codebase | Full encoding pipeline |
onboard to this repo | Discovery + foundation phases |
refresh project understanding | Re-run encoding on updated codebase |
Use this skill when:
Use research-and-incorporate instead when:
/encode-repo-serena
/encode-repo-serena ./my-project
"encode this repository"
"populate forgetful with this codebase"
| Input | Output | Duration |
|---|---|---|
| Codebase path | Forgetful memories + entities + docs | 30-60 min |
claude plugins list | grep serenaexecute_forgetful_tool("list_projects", {})/context-hub-setup first| Phase | Focus | Output |
|---|---|---|
| 0 | Discovery | Project assessment, structure map |
| 1 | Foundation | 5-10 project overview memories |
| 1B | Dependencies | 1-3 dependency memories |
| 2 | Symbols | 10-15 architecture memories |
| 2B | Entities | Component entities + relationships |
| 3 | Patterns | 8-12 pattern memories |
| 4 | Features | 1-2 per critical feature |
| 5 | Decisions | Design decision memories |
| 6 | Artifacts | Code artifact storage |
| 6B | Symbol Index | Document + entry memory |
| 7 | Documents | Long-form documentation |
| 7B | Architecture | Architecture reference doc |
See references/phases.md for full phase details.
| Profile | Total Memories | Documents | Entities |
|---|---|---|---|
| Small Simple | 17-31 | 2 | 3-5 |
| Small Complex | 28-46 | 2 | 5-10 |
| Medium | 38-66 | 2-3 | 10-20 |
| Large | 66-112 | 3-6 | 20-40 |
0 → 1 → 1B → 2 → 2B → 3 → 4 → 5 → 6 → 6B → 7 → 7B
Guidelines:
find_symbol and find_referencing_symbols| Principle | Description |
|---|---|
| Symbol-accurate | Use LSP data, not guesses |
| Atomic | One concept per memory |
| Size | 200-400 words ideal |
| Importance | Most should be 7-8 |
| Linking | Connect related memories |
After completion:
See references/validation.md for test commands.
| Avoid | Why | Instead |
|---|---|---|
| Skipping Phase 0 discovery | Wastes effort on wrong project scope | Always assess project size and complexity first |
| Creating non-atomic memories | Pollutes search results, hard to maintain | One concept per memory, 200-400 words |
| Duplicate entities | Bloats knowledge graph, inconsistent links | Deduplicate entities before creating |
| Skipping validation | No confidence in encoding quality | Run validation checklist after completion |
After encoding:
| Document | Content |
|---|---|
| phases.md | Detailed phase workflows |
| templates.md | Entity schemas, memory templates |
| validation.md | Validation test commands |
/context-hub-setup - Setup Forgetful MCP/using-forgetful-memory - Memory best practices/using-serena-symbols - Serena symbol analysisActivates when the user asks about AI prompts, needs prompt templates, wants to search for prompts, or mentions prompts.chat. Use for discovering, retrieving, and improving prompts.
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Creating algorithmic art using p5.js with seeded randomness and interactive parameter exploration. Use this when users request creating art using code, generative art, algorithmic art, flow fields, or particle systems. Create original algorithmic art rather than copying existing artists' work to avoid copyright violations.