DejaVu

Your AI already wrote this. DejaVu gives your codebase a memory that every coding agent shares — and none can ignore.

⚠ duplicate  lib/helpers.ts:4
  makeUrlSlug() looks 98% like slugify() in utils/text.ts:2
  your AI already wrote this — reuse it instead

Every AI coding session starts fresh. The decision to use Supabase RLS instead of API-layer auth was made three weeks ago, in a different tool, and is now invisible — so today's session quietly contradicts it and rewrites slugify() for the fourth time. AI-assisted codebases accumulate duplication at up to 8x the rate of hand-written ones, and tech debt compounds until the Spaghetti Point at ~month 3, where adding features starts breaking existing ones.

Month 3 is where vibecoded projects go to die. DejaVu is how yours survives it.

What it does

1. Capture — mines decisions from your Claude Code / OpenClaw session transcripts (heuristics, no LLM needed), harvests #decision: code comments, and takes dejavu remember for everything else. Every candidate goes through your review queue — nothing lands without your approval.
2. Inject — projects active decisions into every agent's context via managed blocks in CLAUDE.md, AGENTS.md, .cursorrules, OpenClaw MEMORY.md — and serves them over MCP to any agent that asks. Decisions survive tool-switching.
3. Enforce — dejavu check flags code that contradicts a past decision or re-implements something that already exists. Runs as a CLI, a pre-commit hook, a GitHub Action, or a real-time agent hook. Warn-first; --strict when you mean it.

Mental model: git for code, DejaVu for the why.

Quick start

cd your-project
npx dejavu-dev init                # DECISIONS.md + .dejavu/ (+ optional pre-commit hook)
npx dejavu-dev mine                # harvest decisions from your past Claude Code sessions
npx dejavu-dev review              # approve / edit / reject each candidate
npx dejavu-dev project             # push decisions into CLAUDE.md, .cursorrules, ...
npx dejavu-dev check               # "did my last change contradict or duplicate anything?"
npx dejavu-dev score               # 0-100 repo health, letter grade, shareable badge

Try it on the included wreck: examples/spaghetti-app — a month-3 fixture with a planted contradiction and two AI-rewritten duplicates.

Why not …?

| | ADR tools (AgDR, adr-agent) | PR review bots (Qodo, CodeAnt) | Agent memory (Mem0, Cipher) | DejaVu | |---|---|---|---|---| | Automatic capture from sessions | ✗ (human discipline) | ✗ | ~ (facts, not decisions) | ✔ | | Works across every tool | ~ (docs only) | ✗ (their platform) | ✗ (per-framework) | ✔ (files + MCP) | | Enforcement against code | ✗ | ✔ (PR time, cloud) | ✗ | ✔ (local, pre-commit) | | Fully local | ✔ | ✗ | ~ | ✔ | | Free | ✔ | ✗ (enterprise seats) | ~ | ✔ (Apache-2.0) |

ADR tools validated the problem but require the discipline that vibecoding removed. Review bots catch drift — at PR time, in the cloud, per seat. Memory tools store preferences, not decisions, and check nothing. DejaVu is the unclaimed combination: capture + inject + enforce, local and free.

And the two-layer design is the part that travels: repo decisions live in DECISIONS.md committed to git — a collaborator's Cursor respects decisions your Claude Code made even if they never install DejaVu, because the repo itself is the export format. Your personal preferences live in ~/.dejavu/ and are never committed (enforced in code, proven by tests — including git check-ignore).

The decision format

## D-014: Use Supabase RLS for authorization (not API-layer checks)
- date: 2026-07-04 · source: claude-code session · status: active
- context: single-tenant app, auth bugs from duplicated API checks
- rule: all authorization goes through RLS policies; no manual user_id filtering in API routes
- applies_to: src/api/**
- detect: user_id\s*===?
- supersedes: D-006

Plain markdown, fully useful with zero tooling. applies_to: globs and detect: regexes make a decision enforceable. Changing your mind appends a superseding entry — history is the value. .dejavu/index.json is a derived cache, always regenerable; markdown is the source of truth.

Commands

| Command | What it does | |---|---| | dejavu init | Set up a repo (idempotent); offers the pre-commit hook | | dejavu remember "<title>" | Record a decision: --context, --rule, --applies-to, --detect, --supersedes, --queue, --global | | dejavu mine | Harvest sessions + #decision: comments into the queue (--source, --dry-run, --limit) | | dejavu review | Approve / edit / reject queued candidates (TUI, shows confidence + evidence) | | dejavu project | Update managed blocks in agent context files (--to, --all, --check, --remove) | | dejavu check [files] | Contradictions + duplication on changed files (--staged, --all, --strict) | | dejavu score | Repo health 0–100 + grade (--json, --badge → local SVG) | | dejavu hooks install | Pre-commit hook — warns by default, --strict blocks | | dejavu serve | MCP server: search_decisions, get_decision, check_against_decisions (docs/mcp.md) |

CI: the GitHub Action runs check + projection staleness on any repo — including ones built entirely on web platforms (Lovable, Replit, Bolt), since the repo carries the ledger.

Configuration

Repos with intentional duplication (scaffolding templates, fixtures) can exclude paths from check/score via .dejavu/config.json:

{ "exclude": ["cli/template/**", "fixtures/**"] }

Performance

dejavu check and dejavu score complete in under 1 second on a 50k-LOC repo (~2,400 functions) — measured, not aspirational. Pre-commit tolerance was the design budget (3s); heuristic extraction + normalized-token shingles with an inverted index get there without embeddings, AST parsers, or the network.

Non-goals (v0.1)

No cloud, no accounts, no telemetry, no embeddings/vector DB, no full AST analysis (heuristics that catch the common 80% beat perfect analysis that ships never), no PR review comments (that lane is taken), Windows via WSL.

Contributing

The highest-leverage PR is a ~40-line adapter for your tool: docs/adapters.md. Golden-file tests make adapter PRs trivially verifiable — add a fixture folder, run UPDATE_GOLDEN=1 npm test, review the diff. Mining heuristics PRs are gated by the precision table in tests/heuristics.test.ts: new patterns must not fire on the noise set.

npm install && npm test       # 200+ tests: golden files, generative round-trips, injected fs failures
npm run typecheck && npm run lint
npm run build                 # tsup → dist/cli.js (what npx runs)
npm run build:bin             # bun build --compile → single executable

License

Apache-2.0