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

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Forgetful searches return sparse or outdated results for the project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

/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

Serena plugin: claude plugins list | grep serena
Forgetful MCP: Test with execute_forgetful_tool("list_projects", {})
If missing, run /context-hub-setup first

Process

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.

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

Execution Order

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

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 Checklist

After completion:

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

See 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

Verification

After encoding:

All target components have Forgetful entities created
Entity relationships reflect actual code dependencies
Memories linked to corresponding entities
No duplicate entities in knowledge graph
Validation checklist items pass

References

Document	Content
phases.md	Detailed phase workflows
templates.md	Entity schemas, memory templates
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

encode-repo-serena