The second brain for Claude Code. Now for every AI coding assistant.
Improved context management, optimized architecture scaffolding, and smarter token utilization,
delivered through 7 invisible lifecycle hooks. Zero workflow changes.
Quick Start · Supported Agents · Context Management · Token Intelligence · Security · Dashboard · Changelog
| Without OpenWolf | With OpenWolf |
|---|---|
| The agent rereads a file it already saw (~2,000 tokens) | It reads the one-line description first, or skips the read entirely |
| Whole-file reads just to find one function | Symbol-level hints give exact line ranges for offset/limit reads |
| Context compaction wipes what the session did | A PreCompact snapshot and restore keep the work in context |
| Every agent starts from a cold prompt | One shared .wolf/ brain across Codex, OpenCode, Claude Code, Cursor, and Antigravity |
| No idea where your tokens went | Usage measured from harness transcripts, plus a live local dashboard |
Saves you tokens? Star the repo, it helps other developers find OpenWolf.
Coding agents are powerful but they work blind. An agent does not know what a file contains until it opens it. It cannot tell a 50-token config from a 2,000-token module. It rereads the same file in one session without noticing, forgets your corrections between sessions, and loses everything when its context window compacts.
OpenWolf gives your agent a second brain that fixes all of that:
- Context management. A budget-capped digest of your project's most valuable state (current goals, known mistakes, fixed bugs, the project map) is injected at every session start. A PreCompact hook plus a compaction-aware restart mean context compaction no longer erases what the session already did.
- Architecture scaffolding. A durable, self-healing project index maps every file with a description, a token estimate, and (for large files) its functions and classes with exact line ranges. Agents navigate your codebase instead of rediscovering it.
- Token utilization. Repeated reads are caught, whole-file reads become targeted slice reads, and real usage is measured from harness transcripts so you can verify the savings instead of trusting an estimate.
npm install -g openwolf
cd your-project
openwolf initThat is it. init auto-detects the coding agents installed on your machine
and wires each of them to the same .wolf/ brain. Use your agents normally;
OpenWolf works underneath.
One .wolf/ brain, many agents:
| Agent | Integration | Depth |
|---|---|---|
| Codex CLI | .codex/hooks.json lifecycle hooks + AGENTS.md |
Full (hooks + context) |
| OpenCode | Native plugin + AGENTS.md |
Full (hooks + context) |
| Claude Code | 7 lifecycle hooks + CLAUDE.md |
Full (hooks + context) |
| Cursor | .cursor/rules/openwolf.mdc (always applied) |
Beta (context) |
| Antigravity | AGENTS.md protocol block |
Beta (context) |
| Gemini CLI | GEMINI.md protocol block |
Beta (context) |
openwolf init # auto-detect installed agents (recommended)
openwolf init --agent codex opencode # wire exactly these
openwolf init --agent all # wire every detected agent
openwolf init --agent claude # Claude Code onlyProtocol blocks are marker-fenced: your own content in AGENTS.md or
GEMINI.md is never touched, and re-running init never duplicates anything.
openwolf init creates a .wolf/ directory in your project:
| File | Purpose |
|---|---|
anatomy-index.json |
Durable project index: descriptions, token estimates, content hashes, symbols |
anatomy.md |
Human-readable render of the index, kept in sync automatically |
cerebrum.md |
Learned preferences, corrections, Do-Not-Repeat list |
memory.md |
Chronological action log with token estimates |
STATUS.md |
Session handoff: resume any session in one small read |
buglog.json |
Bug fix memory, searchable, prevents rediscovery |
token-ledger.json |
Estimated and measured token usage, per session and per agent |
hooks/ |
7 lifecycle hooks (pure Node.js, zero dependencies) |
config.json |
Configuration, including per-agent context budgets |
OPENWOLF.md |
The operating protocol your agents follow |
Session starts
|
OpenWolf injects a token-budgeted digest: current goals, known mistakes,
recent bug fixes, project map pointer
|
Agent decides to read a big file
|
OpenWolf: "auth.ts (~2,900 tok). Symbols: validateToken L82-140 ~450 tok.
Read with offset/limit to fetch just the part you need."
|
Agent edits files
|
OpenWolf updates the index under a cross-process lock, logs the action,
estimates the cost
|
Context compacts mid-session
|
OpenWolf snapshots state before compaction and re-injects a digest of the
files already modified, so the agent does not redo finished work
|
Session ends
|
OpenWolf reads the real token usage from the transcript into the ledger
- Session digest. The highest-value state is pushed into the model's context at session start, capped to a configurable token budget per agent. The model gets what it needs without reading six files.
- Compaction survival. The PreCompact hook snapshots in-flight session state; after compaction the digest lists the files already modified with a pointer to the action log. Resume and compaction no longer reset tracking.
- Staleness detection. Scans pin the git HEAD. If the HEAD moves or the scan ages out, the agent is told to rescan before trusting the map. A wrong index is never silently trusted.
- STATUS.md handoff. End-of-phase state lives in one small document, so a fresh session reaches productive context in a single read.
The index is a durable store (anatomy-index.json) with a rendered,
human-readable view (anatomy.md). Writers coordinate through a
cross-process lock, so concurrent hook fires cannot lose entries. Edits made
to the markdown by hand or by older hook versions are detected by content
hash and absorbed additively.
Files above 500 estimated tokens also index their top-level symbols:
- `shared.ts` (~3,200 tok)
- fn `parseAnatomy` L82-104 (~180 tok)
- fn `serializeAnatomy` L106-129 (~200 tok)
Before the agent reads a large file, the hint lists the biggest symbols with line ranges so it can fetch one function with offset/limit instead of the whole file. Hints are suppressed automatically if the file changed since indexing; a stale range is never allowed to misdirect a read. Languages with symbol support today: TypeScript, JavaScript, Python, Go, Rust.
Estimates are useful; measurements are trustworthy. At session end OpenWolf reads the real usage from the harness transcript: input tokens, output tokens, cache reads, cache writes, and API calls, attributed to the agent that ran the session.
openwolf report Estimated (char-ratio heuristic)
Total tokens: 1,549,658
Est. savings vs bare: 1,772,690
Measured (from harness transcripts)
API calls: 29
Input tokens: 57,489
Cache reads: 309,141
Field results from 1.x deployments (20 projects, 132+ sessions) averaged a 65.8% estimated token reduction, with 71% of repeated file reads caught and blocked. Those figures are heuristic estimates; 2.0 exists so your own numbers are measured, not modeled.
- Dashboard binds to 127.0.0.1 and requires a per-project token (timing-safe comparison) for all API and WebSocket access.
- Every dynamic process invocation uses argument arrays; no shell interpolation anywhere.
- Path traversal guards on all cron file access, realpath-based and symlink-safe.
- Secret-bearing files (keys, keystores, credential files,
.npmrc,.envand friends) never enter the index or the memory log. - A security regression suite runs with
pnpm test.
openwolf init installs two slash commands into every configured agent
(Claude Code, Codex, OpenCode):
/security-audit [scope]: layered audit covering dependencies, secrets, injection surfaces, and authorization, ending in a severity-ranked report wired into.wolf/buglog.json./reframe [migrate | audit | fix]: the design brain. Pick or migrate a UI framework using a curated knowledge base of 13 frameworks (shadcn/ui, Aceternity, Magic UI, DaisyUI, HeroUI, Chakra, Flowbite, Preline, Park UI, Origin UI, Headless UI, Cult UI, Astryx), or audit and fix existing UI against an anti-generic design mandate: distinctiveness is an acceptance criterion, and the recognizable AI-generated look is a failure state.
openwolf daemon start
openwolf dashboardA local, token-authenticated dashboard rendered in a dot-matrix design
system: measured vs estimated tokens, cache economics, per-agent usage,
context health (scan freshness, pinned git HEAD, digest budget), session
handoff, live activity, cron control, and the full anatomy browser with
per-file symbols. Panels are deep-linkable (/#tokens).
openwolf init Initialize .wolf/ and wire detected agents
openwolf status Health, stats, file integrity
openwolf scan Rebuild the project index
openwolf scan --check Verify the index matches the filesystem (CI-friendly)
openwolf report Token report: estimated vs measured
openwolf dashboard Open the web dashboard
openwolf daemon start Start the background daemon
openwolf daemon stop Stop the daemon
openwolf cron list Scheduled tasks
openwolf cron run <id> Trigger a task
openwolf bug search <term> Search the bug memory
openwolf update Update every registered project (with backup)
openwolf restore [backup] Roll back .wolf/ from a timestamped backup
There is also a standalone inspector that needs nothing installed:
node scripts/openwolf-check.mjs [projectDir] # read-only usage report- Node.js 20+
- At least one supported coding agent
- Windows, macOS, or Linux
- Optional: PM2 for a persistent background daemon
- Estimated figures use a character-ratio heuristic (accurate to roughly 15%); measured figures come from harness transcripts and are exact.
- Hook coverage varies by agent: Claude Code and Codex have full lifecycle hooks, OpenCode uses its plugin events, Gemini CLI and Cursor are context-only integrations.
- Protocol compliance (updating cerebrum, logging bugs) depends on the model following instructions; the hooks enforce what can be enforced and remind about the rest.
- Found something broken? File an issue.
OpenWolf is better because people fixed it. Every merged contribution is credited here. Kindly let us know if we have missed a contribution.
 fsener |
 albertomenache |
 whydoyouwork |
 mann1x |
 GordongWang |
 WeathermanTony |
 goashem |
 bryandent |
 levnikmyskin |
 svanack404 |
 riverwolf67 |
 nottyjay |
 alfasin |
 ChasLui |
 JarrodAI |
 meketreve |
Built by Farhan Palathinkal, Cytostack