Best for
- Use when an autonomous agent takes a side-effecting action that may need to be proven later, or when satisfying EU AI Act Article 12 record-keeping.
alirezarezvani/claude-skills/ra-qm-team/skills/agent-decision-receipts/SKILL.md
Mint a tamper-evident, post-quantum-signed receipt for a consequential agent action (deploy, delete, pay, grant-access, model decision) so it can be verified later from the certificate alone. Use when an autonomous agent takes a side-effecting action that may need to be proven later, or when satisfying EU AI Act Article 12 record-keeping. Three decisions: whether an action needs a receipt, minting it, verifying it. Signing is delegated to the open-source OpenAgentOntology package. Not after-the-
Decision brief
Mint a tamper-evident, post-quantum-signed receipt for a consequential agent action (deploy, delete, pay, grant-access, model decision) so it can be verified later from the certificate alone. Three decisions: whether an action needs a receipt, minting it, verifying it.
Compatibility matrix
| Platform | Status | Evidence | What to check |
|---|---|---|---|
| Codex | Not declared | No explicit evidence | Portability before use |
| Claude Code | Not declared | No explicit evidence | Portability before use |
| Cursor | Not declared | No explicit evidence | Portability before use |
| Gemini CLI | Not declared | No explicit evidence | Portability before use |
Installation
The source command is displayed only when detected. A safe inspection prompt is always available so your agent can explain every action before execution.
npx skills add https://github.com/alirezarezvani/claude-skills --skill "ra-qm-team/skills/agent-decision-receipts"Inspect the Agent Skill "agent-decision-receipts" from https://github.com/alirezarezvani/claude-skills/blob/aa8d778811a557a2c28ccadda4cf3d0bd028a4cc/ra-qm-team/skills/agent-decision-receipts/SKILL.md at commit aa8d778811a557a2c28ccadda4cf3d0bd028a4cc. List every install step, command, network request, credential, file read/write, external action, and rollback step. Explain whether it fits my task. Do not install or execute anything until I approve.
Workflow
Review the “Quick Start” section in the pinned source before continuing.
The three decisions below are the skill: decide whether to receipt, mint, then verify.
pip install "openagentontology[pq]"
python scripts/buildactionmanifest.py --agent my-deploy-agent --operation deploy \ --target prod/api --policy "EU AI Act Art 12" --out action.json
python -c "import json,openagentontology.receipt as r; \ print(json.dumps(r.mintreceipt(json.load(open('action.json')), decision='ACTIONGOVERNED')))" receipt.json
Permission review
The documentation asks the agent to run terminal commands or scripts.
python scripts/build_action_manifest.py --agent my-deploy-agent --operation deploy \The documentation asks the agent to run terminal commands or scripts.
python -c "import json,openagentontology.receipt as r; \Evidence record
| Signal | Value | Evidence type | Meaning |
|---|---|---|---|
| Quality score | 84/100 | Computed | Documentation, specificity, maintenance, and trust rules |
| Repository stars | 23,781 | Source | Repository attention, not individual Skill quality |
| Compatibility | 0 platforms | Source | Declared in the catalog source record |
| Usage guide | automated source guide | Editorial | Generated or reviewed according to the visible evidence level |
Pinned source
A log says an action happened. A receipt is tamper-evident: it records who, what, and under which policy, and it is signed, so any later edit breaks the signature. This skill mints one for a consequential agent action and verifies it later from the certificate alone: no database, no network, no trusting the issuer.
The crypto is not in this skill. It is the open-source OpenAgentOntology receipt primitive (Apache-2.0), which signs every receipt with Ed25519 and the post-quantum legs ML-DSA-65 (FIPS 204) + SLH-DSA (FIPS 205) when the post-quantum backend is installed. This skill is the decision layer: when to mint, what to put in, how to verify. One install, no per-skill crypto.
Three decisions, nothing else:
This skill is NOT log analysis. Logs describe what happened and can be silently edited. A receipt is minted before/at execution and breaks if edited. Use logs for debugging; use receipts for evidence.
This skill is NOT a hosted notary. It mints a LOCAL, self-signed receipt anyone can verify offline. Cross-organization verification (one org proving to another) is a separate hosted service, out of scope here.
This skill is NOT a legal opinion. It produces evidence shaped to support FRE 902(13)/(14)-style certification and EU AI Act Article 12 record-keeping. Whether a given receipt is admitted is a question for counsel.
# Install the open-source receipt primitive (Apache-2.0). Add [pq] for the post-quantum legs.
pip install "openagentontology[pq]"
# 1. Build + validate an action manifest (stdlib only, no crypto, no network)
python scripts/build_action_manifest.py --agent my-deploy-agent --operation deploy \
--target prod/api --policy "EU AI Act Art 12" --out action.json
# 2. Mint the receipt over it (Ed25519 + post-quantum legs)
python -c "import json,openagentontology.receipt as r; \
print(json.dumps(r.mint_receipt(json.load(open('action.json')), decision='ACTION_GOVERNED')))" > receipt.json
# 3. Verify from the cert alone (no DB, no network)
python -c "import json,openagentontology.receipt as r; \
print(r.verify_receipt(json.load(open('receipt.json'))))"
# -> {'ok': True, 'sig_ok': True, ... 'reason': 'verified from the cert alone via: ed25519, ml_dsa, slh_dsa'}
Dependency note. This skill delegates the signing to
openagentontology(Apache-2.0, opt-inpip install). The script shipped here is stdlib-only and adds no repo dependency; the package is installed by the operator (BYO-library pattern). If it is not installed, the build step still works — only minting/verifying require it.
The three decisions below are the skill: decide whether to receipt, mint, then verify.
Mint a receipt when the action is all three of:
| Test | Mint if... |
|---|---|
| Side-effecting | it writes, sends, deploys, deletes, pays, grants access, or changes external state |
| Consequential | a wrong call costs money, breaks compliance, or harms a person |
| Later-provable | someone (auditor, insurer, regulator, court, counterparty) may ask "what did the agent do and why?" |
Read-only, reversible, trivial actions do not need a receipt. Receipt everything and the signal drowns; receipt nothing and the one call that mattered cannot be proven.
High-signal triggers (mint by default): deploy, delete, pay/wire/refund, grant_access, export/egress, approve/deny a claim, any model decision that affects a person under a high-risk AI system.
The action manifest is any ASCII-safe dict describing what the agent did. Four keys are required — build_action_manifest.py rejects the manifest (exit 2) if any is missing. Two more are added automatically:
| Key | Required? | What it carries |
|---|---|---|
agent_id | required | the acting agent |
operation | required | the verb (deploy / delete / pay / decide / ...) |
target | required | what it acted on |
policy | required | the rule that governs it (e.g. "EU AI Act Art 12", "internal change-control") |
inputs_hash | auto-added | a hash of --inputs, so the full payload need not be stored in the clear (defaults to the hash of empty when --inputs is omitted) |
decision_label | auto-added | the receipt decision label (defaults to ACTION_GOVERNED) |
mint_receipt(manifest, decision=...) hashes the full manifest into the receipt evidence, signs the canonical body, and returns a receipt that carries: evidence_hash, signature_b64 (Ed25519), and — when [pq] is installed — ml_dsa_signature_b64 + slh_dsa_signature_b64. Each leg signs the same bytes; any one verifying proves authenticity.
See references/receipt-fields.md for the full receipt schema and the post-quantum rationale.
verify_receipt(receipt) recomputes sha256(canonical(evidence)), compares it to evidence_hash, then checks every signature leg it has a backend for. It returns {ok, hash_ok, sig_ok, legs, reason}. A single edited byte anywhere in the action breaks hash_ok; a forged signature breaks the leg. Verification needs only the receipt — no call back to the issuer.
This is the property that makes it evidence: a reviewer who distrusts the issuer can still confirm the receipt is intact and authentic, entirely offline.
[pq].inputs_hash), not the cleartext.unsigned flag instead. Never present an unsigned receipt as signed.ra-qm-team/skills/eu-ai-act-specialist/ — decide the AI system's risk tier and Article 12 obligations; this skill mints the per-action record those obligations require.ra-qm-team/skills/iso42001-specialist/ — the AI management-system controls; receipts are the per-decision evidence those controls call for.pip install "openagentontology[pq]".Alternatives
wanshuiyin/Auto-claude-code-research-in-sleep
Use it for deployment and design tasks; the detail page covers purpose, installation, and practical steps.
K-Dense-AI/scientific-agent-skills
Build, inspect, test, and analyze bounded process-based discrete-event simulations with SimPy, including events, resources, interrupts, monitoring, replications, warm-up, and reproducible output analysis.
wanshuiyin/Auto-claude-code-research-in-sleep
Use it for deployment and design tasks; the detail page covers purpose, installation, and practical steps.
wanshuiyin/Auto-claude-code-research-in-sleep
Use it for deployment and design tasks; the detail page covers purpose, installation, and practical steps.