# Encode Repo Serena > Systematically populate the Forgetful knowledge base using Serena's LSP-powered Use when this capability is needed. - Skill: `tomevault-io/encode-repo-serena` (Agent Skill, multi-file: 2 files) - Install (CLI): `npx skillmds@latest add tomevault-io/encode-repo-serena` - Raw SKILL.md: https://api.skillmd.com/api/skills/tomevault-io/encode-repo-serena/raw - Safety review: pending (external: skill-scanner PASS, skillspector PASS) - Works with: Claude Code, Claude.ai, OpenAI Codex - Category: Research & Search - Author: tomevault-io (https://skillmd.com/u/tomevault-io) - Updated: 2026-09-17 - Page: https://skillmd.com/skills/tomevault-io/encode-repo-serena --- # Encode Repository (Serena-Enhanced) Transform an undocumented codebase into a rich, searchable knowledge repository using Serena's LSP-powered symbol analysis. ## Triggers | 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 | | `build knowledge base for this project` | Full encoding pipeline | ## When to Use Use this skill when: - Onboarding to a new repository that lacks Forgetful knowledge - Repository structure has changed significantly since last encoding - Forgetful searches return sparse or outdated results for the project Use `research-and-incorporate` instead when: - Researching an external topic, not encoding a codebase - You need analysis of a single concept, not full repository encoding ## Quick Start ```text /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 | ## Prerequisites 1. **Serena plugin**: `claude plugins list | grep serena` 2. **Forgetful MCP**: Test with `execute_forgetful_tool("list_projects", {})` 3. If missing, run `/context-hub-setup` first ## Process ### Phase 0: Discovery Assess project size, complexity, and structure. Produce a structure map. ### Phase 1: Foundation Create 5-10 project overview memories covering purpose, tech stack, and entry points. ### Phase 1B: Dependencies Create 1-3 dependency memories documenting external libraries and internal references. ### Phase 2: Symbols Use Serena `find_symbol` and `find_referencing_symbols` to produce 10-15 architecture memories. ### Phase 2B: Entities Create component entities with relationships in Forgetful. Deduplicate before creating. ### Phase 3: Patterns Document 8-12 recurring code patterns, conventions, and idioms. ### Phase 4: Features Create 1-2 memories per critical feature describing behavior and implementation. ### Phase 5: Decisions Record design decisions with rationale and alternatives considered. ### Phase 6: Artifacts Store code artifacts (configs, schemas, key files) in Forgetful. ### Phase 6B: Symbol Index Create a symbol index document with an entry memory for navigation. ### Phase 7: Documents Produce long-form documentation summarizing the codebase. ### Phase 7B: Architecture Create an architecture reference document linking all prior phases. See [references/phases.md](references/phases.md) for full phase details. ## Execution Order ```text 0 → 1 → 1B → 2 → 2B → 3 → 4 → 5 → 6 → 6B → 7 → 7B ``` **Guidelines**: - Execute phases in order - Use Serena's `find_symbol` and `find_referencing_symbols` - Deduplicate entities before creating - Link entities to memories bidirectionally - Create entry memories for documents ## Memory Targets | 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 | ## Quality Principles | 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 | ## Validation After encoding, verify all outputs meet quality standards: - [ ] Test memory search: "How do I add a new API endpoint?" - [ ] Test dependency query: "What dependencies does this project use?" - [ ] List entities by project - [ ] Verify entity relationships - [ ] Check Symbol Index document exists - [ ] Check Architecture Reference document exists - [ ] Verify project.notes populated - [ ] All target components have Forgetful entities created - [ ] Entity relationships reflect actual code dependencies - [ ] Memories linked to corresponding entities - [ ] No duplicate entities in knowledge graph See [references/validation.md](references/validation.md) for test commands. ## Anti-Patterns | 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 | ## References | Document | Content | |----------|---------| | [phases.md](references/phases.md) | Detailed phase workflows | | [templates.md](references/templates.md) | Entity schemas, memory templates | | [validation.md](references/validation.md) | Validation test commands | ## Related Skills - `/context-hub-setup` - Setup Forgetful MCP - `/using-forgetful-memory` - Memory best practices - `/using-serena-symbols` - Serena symbol analysis --- > Converted and distributed by [TomeVault](https://tomevault.io/claim/rjmurillo) — claim your Tome and manage your conversions.