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Repo Indexer

skill-jyshnkr-repo-indexer-repo-indexer · by jyshnkr

Indexes and documents a codebase for persistent Claude context with minimal token overhead. Use when asked to index a repo, understand a codebase, create CLAUDE.md, set up Claude memory, bootstrap context, onboard to a project, or document codebase for Claude. Triggers on phrases like "index this repo", "understand this codebase", "set up context", "create project memory", "help me onboard". Crea…

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Install

$ agentstack add skill-jyshnkr-repo-indexer-repo-indexer

✓ scanned · ✓ verified — works with Claude Code, Cursor, and more.

Security review

✓ Passed

No issues found. Passed automated security review. · v0.1.0 How review works →

  • Prompt-injection patterns
  • Secret / credential exfiltration
  • Dangerous shell & filesystem operations
  • Untrusted network calls
  • Known-malicious package signatures

What it can access

  • Network access No
  • Filesystem access No
  • Shell / process execution No
  • Environment & secrets No
  • Dynamic code execution No

From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.

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About

Repo Indexer

Indexes codebases with minimal context window overhead using tiered memory.

Getting Started

Prerequisites: Python 3.9+. Run from the project root directory.

Memory Architecture

L0: Claude Native Memory  → repo roster, patterns (~100 tokens, auto)
L1: CLAUDE.md             → boot loader only (<500 tokens, auto-load)
L2: .claude/memory/*.md   → deep context (on-demand, explicit load)
L3: Conversation History  → full analysis (searchable, 0 cost until used)

Token budgets: Native Memory ~100–300 | CLAUDE.md <500 | memory/*.md <10,000 total | Past chats: 0 until searched

L2 file loading guide: Architecture decisions → architecture.md | Code style → conventions.md | Unknown terms → glossary.md

Task Progress

Use TodoWrite to track each phase dynamically:

  • Phase 1: Detect repo type
  • Phase 2: Analyze codebase (9 areas)
  • Phase 3: Generate output files
  • Phase 4: Validate token budgets
  • Phase 5: Suggest memory update

Workflow

Phase 1: Detect Repo Type

python3 scripts/detect-repo-type.py "$ARGUMENTS"

Phase 2: Index

Analyze systematically:

  1. Config: package.json, pyproject.toml, Cargo.toml, go.mod
  2. Entry points: main files, CLI, server bootstrap
  3. Structure: directory layout to depth 3
  4. Core modules: business logic, services, models
  5. API surface: routes, endpoints, schemas
  6. Data layer: models, migrations, ORM
  7. External deps: third-party integrations
  8. Build/deploy: Dockerfile, CI/CD, Makefile
  9. Tests: structure, fixtures, patterns

Before generating files, present the proposed .claude/ structure to the user for confirmation.

Phase 3: Generate Output

Output to conversation (L3):

Full analysis using format in references/templates.md → "Indexing Output Format". Include ### SEARCH KEYWORDS for retrieval.

Select CLAUDE.md template by repo type:

Use the type-specific variant from references/templates.md:

  • Monorepo → "CLAUDE.md — Monorepo variant" (packages list, workspace commands)
  • Library → "CLAUDE.md — Library variant" (public API section, publish commands)
  • Microservices → "CLAUDE.md — Microservices variant" (services table, compose commands)
  • Single App → base "CLAUDE.md" template

Create files:

.claude/
├── memory/
│   ├── architecture.md   # From references/templates.md
│   ├── conventions.md
│   └── glossary.md
├── plans/                # Empty, user-managed
└── checkpoints/          # Empty, user-managed

CLAUDE.md                 # At repo root, <500 tokens

Phase 4: Validate

python3 scripts/estimate-tokens.py

Must pass: CLAUDE.md < 500 tokens, all memory files within budget.

If validation fails:

  1. Move content from CLAUDE.md to .claude/memory/ files
  2. Re-run scripts/estimate-tokens.py
  3. Repeat until all files pass their budget

Phase 5: Memory Update

python3 scripts/generate-memory-update.py

Suggest user add to Claude's native memory:

Repo: {name} | Type: {type} | Stack: {stack}
{name} indexed {date} | Key: {modules}

Examples

User: "Index this repo"

  1. Run detect-repo-type.py (Phase 1)
  2. Analyze all 9 areas (Phase 2)
  3. Output full analysis to conversation + create .claude/ structure (Phase 3)
  4. Validate token budgets (Phase 4)
  5. Suggest native memory update (Phase 5)

User: "Help me understand this codebase"

  1. Check Claude memory for prior indexing
  2. Search past chats: "{repo-name} architecture"
  3. If not found: run full indexing workflow

If .claude/ Exists

  1. Load existing files
  2. Compare with current codebase
  3. Flag inconsistencies
  4. Update incrementally
  5. Preserve `` sections

Error Handling

Common issues:

  • Python version error → requires Python 3.9+: python3 --version or which python3

Critical Rules

  • CLAUDE.md hard limit: 500 tokens
  • Full analysis goes in conversation, not files
  • Files are pointers, not stores
  • Always suggest native memory update
  • Include search keywords in output

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

Install and usage instructions live in the source repository linked above.

Reviews

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Versions

  • v0.1.0 Imported from the upstream source.