Step-by-step cookbook for setting up cryptographically signed audit trails on Claude Code tool calls. Use when explaining, evaluating, or demonstrating the pattern before committing to the protect-mcp runtime hooks. Covers Cedar policy, Ed25519 receipts, offline verification, tamper detection, CI/CD integration, and SLSA composition.
npx skills add https://github.com/wshobson/agents --skill signed-audit-trails-recipe
Cookbook-style walkthrough for cryptographically signed receipts on every
Claude Code tool call. This is the teaching skill. For the runtime
implementation, install the protect-mcp plugin.
Every tool call (Bash, Edit, Write, WebFetch) is:
the call, the tool does not run.
JCS-canonical, hash-chained, and verifiable offline by anyone with the
public key.
An auditor, regulator, or counterparty can verify the full chain later with a
single CLI command (npx @veritasacta/verify receipts/*.json). No network
call, no vendor lookup, no trust in the operator.
where you need tamper-evident evidence of agent behavior
every automated build step
agent's behavior without trusting your operator
agent-built software) where standard logging is not sufficient
Create .claude/settings.json in your project root:
{
"hooks": {
"PreToolUse": [
{
"matcher": ".*",
"hook": {
"type": "command",
"command": "npx protect-mcp@latest evaluate --policy ./protect.cedar --tool \"$TOOL_NAME\" --input \"$TOOL_INPUT\" --fail-on-missing-policy false"
}
}
],
"PostToolUse": [
{
"matcher": ".*",
"hook": {
"type": "command",
"command": "npx protect-mcp@latest sign --tool \"$TOOL_NAME\" --input \"$TOOL_INPUT\" --output \"$TOOL_OUTPUT\" --receipts ./receipts/ --key ./protect-mcp.key"
}
}
]
}
}
The first run of protect-mcp sign generates ./protect-mcp.key (Ed25519
private key) if one does not exist. Commit the public key fingerprint
(visible in any receipt's public_key field); do not commit the private
key.
Add the private key and receipt directory to .gitignore:
echo "./protect-mcp.key" >> .gitignore
echo "./receipts/" >> .gitignore
Create ./protect.cedar:
// Allow all read-oriented tools by default.
permit (
principal,
action in [Action::"Read", Action::"Glob", Action::"Grep", Action::"WebSearch"],
resource
);
// Allow Bash commands from a safe list only.
permit (
principal,
action == Action::"Bash",
resource
) when {
context.command_pattern in [
"git", "npm", "pnpm", "yarn", "ls", "cat", "pwd",
"echo", "test", "node", "python", "make"
]
};
// Explicit deny on destructive commands. Cedar deny is authoritative.
forbid (
principal,
action == Action::"Bash",
resource
) when {
context.command_pattern in ["rm -rf", "dd", "mkfs", "shred"]
};
// Restrict writes to the project directory.
permit (
principal,
action in [Action::"Write", Action::"Edit"],
resource
) when {
context.path_starts_with == "./"
};
Four rules:
Bash allowed for safe command patterns (git, npm, etc.)Bash rm -rf and similar destructive commands explicitly denied./ prefix)Cedar forbid rules take precedence over permit rules, so destructive
commands cannot be bypassed by a later permissive rule.
Start Claude Code. Every tool call goes through both hooks:
You: Please read the README and summarize it.
Claude: I will read README.md.
[PreToolUse: Read ./README.md -> allow]
[Tool: Read executes]
[PostToolUse: receipt rcpt-a8f3c9d2 signed to ./receipts/]
... summary of README ...
A session of 20 tool calls produces 20 receipts, each hash-chained to its
predecessor.
cat ./receipts/$(ls -t ./receipts/ | head -1)
{
"receipt_id": "rcpt-a8f3c9d2",
"receipt_version": "1.0",
"issuer_id": "claude-code-protect-mcp",
"event_time": "2026-04-17T12:34:56.123Z",
"tool_name": "Read",
"input_hash": "sha256:a3f8c9d2e1b7465f...",
"decision": "allow",
"policy_id": "protect.cedar",
"policy_digest": "sha256:b7e2f4a6c8d0e1f3...",
"parent_receipt_id": "rcpt-3d1ab7c2",
"public_key": "4437ca56815c0516...",
"signature": "4cde814b7889e987..."
}
Every field except signature and public_key is covered by the Ed25519
signature. Modifying any field after signing invalidates the signature.
npx @veritasacta/verify ./receipts/*.json
Exit codes:
| Code | Meaning |
|------|---------|
| 0 | All receipts verified; chain intact |
| 1 | A receipt failed signature verification (tampered, or wrong key) |
| 2 | A receipt was malformed |
Modify any receipt's decision field from allow to deny:
python3 -c "
import json, os
path = './receipts/' + sorted(os.listdir('./receipts'))[-1]
r = json.loads(open(path).read())
r['decision'] = 'deny'
open(path, 'w').write(json.dumps(r))
"
npx @veritasacta/verify ./receipts/*.json
The verifier exits with code 1 and reports which receipt failed. The
Ed25519 signature no longer matches the JCS-canonical bytes of the
tampered payload.
Restore the field and verification passes again.
Three invariants make receipts verifiable offline across any conformant
implementation:
whitespace minimized, strings NFC-normalized. Two independent
implementations produce byte-identical signing payloads for the same
receipt content.
Deterministic, fixed-size, no nonce dependency.
parent_receipt_hash is theSHA-256 of the predecessor's canonical form. Insertions, deletions, and
reorderings break later receipts.
For the formal wire format see
draft-farley-acta-signed-receipts.
The receipt format has four independent implementations today:
| Implementation | Language | Use case |
|----------------|----------|----------|
| protect-mcp | TypeScript | Claude Code, Cursor, MCP hosts |
| protect-mcp-adk | Python | Google Agent Development Kit |
| sb-runtime | Rust | OS-level sandbox (Landlock + seccomp) |
| APS governance hook | Python | CrewAI, LangChain |
A receipt produced by any of them verifies against
The auditor does not need to trust the operator's tooling choice: the format
is the contract.
Gate merges on receipt chain verification so no build lands with a broken
evidence chain:
# .github/workflows/verify-receipts.yml
name: Verify Decision Receipts
on: [push, pull_request]
jobs:
verify:
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v4
- uses: actions/setup-node@v4
with: { node-version: '20' }
- name: Run governed agent
run: python scripts/run_agent.py > receipts.jsonl
- name: Verify receipt chain
run: npx @veritasacta/verify receipts.jsonl
Archive the receipts as an artifact so the chain survives beyond the job run:
- name: Upload receipts
if: always()
uses: actions/upload-artifact@v4
with:
name: decision-receipts
path: receipts/
When Claude Code builds and releases software (running npm install,
npm build, npm publish as tool calls), the receipt chain is the
per-step build log. SLSA Provenance v1 has an extension point for this: the
byproducts field can reference the receipt chain alongside the build
attestation.
documents the pattern using the ResourceDescriptor shape:
{
"name": "decision-receipts",
"digest": { "sha256": "..." },
"uri": "oci://registry/org/build-xyz/receipts:sha256-...",
"annotations": {
"predicateType": "https://veritasacta.com/attestation/decision-receipt/v0.1",
"signerRole": "supervisor-hook"
}
}
The SLSA provenance is signed by the builder identity; the receipt
attestation is signed by the supervisor-hook identity. Two trust domains,
cross-referenced at the byproduct layer. See
for the composition discussion.
Private key in version control. The generated ./protect-mcp.key must
not be committed. The examples above add it to .gitignore. If a key is
accidentally committed, rotate immediately (delete the key file and let the
hook regenerate on next run).
Hook command quoting. The hooks receive $TOOL_NAME and $TOOL_INPUT
as environment variables. Keep the quoting "$TOOL_INPUT" so inputs with
spaces or special characters pass through intact.
Receipts directory in CI. If Claude Code runs in CI, upload receipts as
an artifact at the end of the job or the chain is lost at job end.
Policy is missing. The example PreToolUse hook uses
--fail-on-missing-policy false so an absent ./protect.cedar does not
break Claude Code out of the box. Remove this flag in production so a
missing policy is treated as a hard failure.
protect-mcp — the runtime hook implementation(use this plugin in production)
review-agent-governance — requirehuman approval before review-surface actions; composes with protect-mcp
draft-farley-acta-signed-receipts — IETF draft, receipt wire formatexamples/protect-mcp-governed/)Assess Kubernetes workloads and cluster configuration for AKS Automatic compatibility. Identifies incompatibilities, generates fixes, and guides migration from AKS Standard to AKS Automatic. WHEN: migrate to AKS Automatic, check AKS Automatic readiness, validate manifests for Automatic, assess cluster for Automatic compatibility, fix deployment for Automatic compatibility, identify AKS Automatic migration blockers, is my cluster ready for AKS Automatic.
Discovers available Azure OpenAI model capacity across regions and projects. Analyzes quota limits, compares availability, and recommends optimal deployment locations based on capacity requirements. USE FOR: find capacity, check quota, where can I deploy, capacity discovery, best region for capacity, multi-project capacity search, quota analysis, model availability, region comparison, check TPM availability. DO NOT USE FOR: actual deployment (hand off to preset or customize after discovery), quota increase requests (direct user to Azure Portal), listing existing deployments.
Interactive guided deployment flow for Azure OpenAI models with full customization control. Step-by-step selection of model version, SKU (GlobalStandard/Standard/ProvisionedManaged), capacity, RAI policy (content filter), and advanced options (dynamic quota, priority processing, spillover). USE FOR: custom deployment, customize model deployment, choose version, select SKU, set capacity, configure content filter, RAI policy, deployment options, detailed deployment, advanced deployment, PTU deployment, provisioned throughput. DO NOT USE FOR: quick deployment to optimal region (use preset).
Unified Azure OpenAI model deployment skill with intelligent intent-based routing. Handles quick preset deployments, fully customized deployments (version/SKU/capacity/RAI policy), and capacity discovery across regions and projects. USE FOR: deploy model, deploy gpt, create deployment, model deployment, deploy openai model, set up model, provision model, find capacity, check model availability, where can I deploy, best region for model, capacity analysis. DO NOT USE FOR: listing existing deployments (use foundry_models_deployments_list MCP tool), deleting deployments, agent creation (use agent/create), project creation (use project/create).
Intelligently deploys Azure OpenAI models to optimal regions by analyzing capacity across all available regions. Automatically checks current region first and shows alternatives if needed. USE FOR: quick deployment, optimal region, best region, automatic region selection, fast setup, multi-region capacity check, high availability deployment, deploy to best location. DO NOT USE FOR: custom SKU selection (use customize), specific version selection (use customize), custom capacity configuration (use customize), PTU deployments (use customize).
This skill should be used when working with LaminDB, an open-source data framework for biology that makes data queryable, traceable, reproducible, and FAIR. Use when managing biological datasets (scRNA-seq, spatial, flow cytometry, etc.), tracking computational workflows, curating and validating data with biological ontologies, building data lakehouses, or ensuring data lineage and reproducibility in biological research. Covers data management, annotation, ontologies (genes, cell types, diseases, tissues), schema validation, integrations with workflow managers (Nextflow, Snakemake) and MLOps platforms (W&B, MLflow), and deployment strategies.
Latch platform for bioinformatics workflows. Build pipelines with Latch SDK, @workflow/@task decorators, deploy serverless workflows, LatchFile/LatchDir, Nextflow/Snakemake integration.
Run Python code in the cloud with serverless containers, GPUs, and autoscaling. Use when deploying ML models, running batch processing jobs, scheduling compute-intensive tasks, or serving APIs that require GPU acceleration or dynamic scaling.
Take wshobson/signed-audit-trails-recipe from the repository into ~/.claude/skills for personal
use, or into .claude/skills inside a project.
The agent identifies a skill by the name field in its header. Two skills with the
same name cannot sit side by side — one of them will be ignored.
The instructions reference npm, npx.
Without those the skill loads but fails at the first command.