agent-decision-receipts

Tinjau · 66
Diindeks di Registry

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 la

Verified installs0
Star24.8K
Versi1.0.0
Kualitas91/100 · Sangat baik
Kepercayaan66/100 · Hanya sandbox
Audit83/100 · Perlu ditinjau

Profil aset

Riset dan pekerjaan pengetahuan

Deep research, source comparison, literature review, RAG, knowledge search, and reports.

Lihat kategori

Skenario

Agent riset

I need my agent to research a topic, compare sources, and produce a concise report.

Kecocokan Agent

Claude Code + CLI + Codex

Cocok untuk Codex, Claude Code, Cursor, CLI, atau Agent khusus.

Pasang

Siap

npx skills add alirezarezvani/claude-skills --skill agent-decision-receipts

Pemeliharaan

Terkini

Diperbarui hari ini

Risiko

Perlu ditinjau

Dependency or permission surface needs review

Kualitas GitHub

25K

91/100 Kualitas · 74/100 Kepercayaan

Tag cakupan

RisetAgent risetagent-skill

Catatan ulasan

Dependency or permission surface needs review · Permission surface may require sandboxing

Kartu adopsi Agent

Kepercayaan, audit, dan kesiapan pemasangan dalam sekali lihat

Skor ini menggabungkan metadata repositori publik, sinyal ulasan OpenAgentSkill, kebaruan pemeliharaan, dan kesiapan pemasangan. Ini adalah sinyal shortlist, bukan pengganti peninjauan manusia.

Kualitas

Sangat baik
91

High-confidence pick with strong adoption and healthy maintenance signals.

Kepercayaan

Hanya sandbox
66

Kandidat berguna dengan sinyal kepercayaan yang kurang atau bercampur. Gunakan di ruang kerja terisolasi hingga loop hasil membuktikan kecocokan tugas.

Audit

Perlu ditinjau
83

Tinjauan yang dapat dibaca mesin tentang kesiapan pemasangan, metadata keamanan, pemeliharaan, dan risiko adopsi.

Trust Score OpenAgentSkill v5

Tinjauan manusia sebelum pemasangan

Jalankan hanya dalam sandbox dan bandingkan alternatif terdekat sebelum digunakan untuk kerja nyata.

CodexClaude CodeCursorOpenAgentSkill CLI

Star

25K star GitHub

Aktivitas repositori

25K star dan 3.5K fork

Pemeliharaan

Diperbarui hari ini

Lisensi

MIT

Pasang

npx skills add alirezarezvani/claude-skills --skill agent-decision-receipts

Keamanan pemasangan

Jalur pemasangan paket atau runtime standar

Cakupan izin

secrets or environment access, shell or command execution

Hasil Agent

Belum ada data hasil Agent

Dokumentasi

Konteks README/SKILL.md kuat

Ringkasan risiko

Tinjau sebelum produksi

  • The skill relies on an external package (openagentontology) for cryptographic operations; while this is clearly documented, the package's security posture is not independently verified by this review.
  • Financial research output is not financial advice; require human review before any live investment decision.
  • Quality score needs review
  • Permission surface needs review: secrets or environment access, shell or command execution

Kesiapan pemasangan

Jalur pemasangan tersedia

  • Jalur pemasangan tersedia
  • Bukti repositori tersedia
  • Lisensi dinyatakan
  • Belum ada bukti hasil Agent-Proven

Metadata yang dapat dibaca Agent

Data keputusan yang dapat dibaca mesin untuk skill ini.

Gunakan blok ini atau JSON tersemat untuk memutuskan apakah Agent perlu memasang skill ini, memilih alternatif, atau meminta tinjauan manusia terlebih dahulu.

Buka JSON

Tugas yang sesuai

  • Alur kerja Agent riset
  • Tim Claude Code
  • Tim yang menghargai sinyal adopsi GitHub
  • Sumber pencarian

Agent yang sesuai

CodexClaude CodeCursorOpenAgentSkill CLICLI

Keputusan pemasangan

Perintah
npx skills add alirezarezvani/claude-skills --skill agent-decision-receipts
Kebijakan
Tinjau
Tinjauan manusia
Ya

Kepercayaan dan risiko

Kepercayaan
66/100
Audit
83/100
Tingkat risiko
Perlu ditinjau

Lingkar hasil

Endpoint
/api/agent/outcome
ID event
resolve
Hasil
5

Perintah pemasangan

npx skills add alirezarezvani/claude-skills --skill agent-decision-receipts

Jangan gunakan ketika

  • Tim yang membutuhkan SLA dengan dukungan vendor
  • production agents without a repository review
  • The skill relies on an external package (openagentontology) for cryptographic operations; while this is clearly documented, the package's security posture is not independently verified by this review.
  • No OpenAgentSkill engagement data yet
  • Petunjuk izin berisiko tinggi: Shell or command execution, Secrets or environment access

Keamanan Agent v2

39/100 · Hindari pemasangan otomatis

EksperimentalTinjau

Sparse or mixed signals. Useful for discovery, but not for autonomous installation.

Test manually in an isolated workspace and compare against safer alternatives.

Selesaikan via API

Tinggi

Eksekusi shell atau perintah

Metadata skill merujuk terminal, CLI, shell, subprocess, atau alur kerja eksekusi perintah.

Sedang

Akses jaringan

Skill kemungkinan mengambil halaman jarak jauh, API, repositori, atau layanan eksternal.

Sedang

Akses sistem file

Skill dapat membaca atau menulis file proyek, dokumen, artefak yang dihasilkan, atau status workspace lokal.

Tinggi

Secrets or environment access

Skill metadata references credentials, tokens, environment variables, or secret-bearing workflows.

  • Petunjuk izin berisiko tinggi: Shell or command execution, Secrets or environment access
  • Dependency or permission surface needs review

Target pemasangan

Pasang skill ini di alur Agent Anda

Gunakan endpoint publik untuk mengambil perintah, checklist keamanan, prompt target, dan tautan kanonis.

skill install

OpenAgentSkill CLI

Resolve policy, run the source installer safely, and report a verified install receipt.

$ npx --yes https://github.com/Leon-Drq/openagentskill/releases/download/cli-v0.2.1/openagentskill-0.2.1.tgz install alirezarezvani-agent-decision-receipts

Rencana resolusi Agent

Biarkan Agent memverifikasi kecocokan sebelum memasang.

API Resolve mengembalikan skill utama, alternatif, kebijakan keamanan, catatan audit, target pemasangan, dan prompt siap pakai.

Buka rencana teks

Agent harus memeriksa

  • Task fit and alternatives from Resolve API.
  • Audit score, trust score, and safety policy warnings.
  • Install target compatibility for Codex, Claude Code, Cursor, or CLI.

Salin prompt

Task: Use agent-decision-receipts in this workspace.
Resolve first: https://www.openagentskill.com/api/agent/resolve?task=Use%20agent-decision-receipts%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Review install handoff: https://www.openagentskill.com/api/skills/alirezarezvani-agent-decision-receipts/install
Install command: npx skills add alirezarezvani/claude-skills --skill agent-decision-receipts
Before running it, summarize audit warnings, required permissions, and the fallback skill if install is risky.

Serah-terima Agent

Berikan jalur pemasangan kepada Agent, bukan direktori lain.

Gunakan endpoint publik untuk mengambil perintah, checklist keamanan, prompt target, dan tautan kanonis.

Buka API pemasangan

Prompt Agent

Use agent-decision-receipts for this task. Review https://www.openagentskill.com/api/skills/alirezarezvani-agent-decision-receipts/install, then install with: npx skills add alirezarezvani/claude-skills --skill agent-decision-receipts

Metadata Registry

Profil yang dapat dibaca Agent untuk pemilihan skill otomatis.

API Registry menyediakan sinyal keputusan, kepercayaan, audit, use case, dan pemasangan tanpa mengikis UI.

Buka Manifest

Kecocokan Agent

100/100

Agent riset

Platform

Claude Code

Laporan audit

Perlu ditinjau · 83/100

Tinjauan yang dapat dibaca mesin tentang kesiapan pemasangan, metadata keamanan, pemeliharaan, dan risiko adopsi.

Lihat laporan auditLihat laporan evaluasi

Panel keputusan Agent

Pilihan utama untuk Agent riset

Use this as a leading candidate, then validate the README and install path in your own agent stack.

100
Kesiapan
Adopsi
Tahap

Peran di stack

Pilihan utama

Kecocokan utama

Agent riset

Label kepercayaan

Siap produksi

Jalur pemasangan

Perintah siap

Gunakan saat

  • Alur kerja Agent riset
  • Tim Claude Code
  • Tim yang menghargai sinyal adopsi GitHub

Bukti

  • 24,795 star GitHub
  • recent repository activity
  • install command or GitHub repo available
  • profil kualitas 91/100

tinjau dulu

  • The skill relies on an external package (openagentontology) for cryptographic operations; while this is clearly documented, the package's security posture is not independently verified by this review.
  • No OpenAgentSkill engagement data yet

Jalur implementasi

  1. 1Pasang di Agent sandbox dan jalankan satu tugas Agent riset dari awal hingga akhir.
  2. 2Compare output quality, latency, and failure behavior against at least one alternative.
  3. 3Promote it into production only after reviewing repository permissions, license, and maintenance signals.

Profil kepercayaan

Hanya sandbox

Kandidat berguna dengan sinyal kepercayaan yang kurang atau bercampur. Gunakan di ruang kerja terisolasi hingga loop hasil membuktikan kecocokan tugas.

66
Trust Score OpenAgentSkill

Adopsi GitHub

Lulus

25K star GitHub

Aktivitas star/fork

Lulus

25K star dan 3.5K fork; aktivitas issue tidak tersedia dalam metadata saat ini

Pemeliharaan terbaru

Lulus

Diperbarui hari ini

Kejelasan lisensi

Lulus

MIT

Sinyal positif

  • Tinjauan AI disetujui
  • Jalur pemasangan tersedia
  • Bukti repositori tersedia
  • Repositori yang baru dipelihara
  • Large GitHub adoption signal
  • Perintah pemasangan tidak memiliki pola berisiko tinggi yang jelas
  • Loop hasil siap tetapi membutuhkan eksekusi Agent nyata pertama

Tinjau sebelum memasang

  • The skill relies on an external package (openagentontology) for cryptographic operations; while this is clearly documented, the package's security posture is not independently verified by this review.
  • Financial research output is not financial advice; require human review before any live investment decision.
  • Quality score needs review
  • Permission surface needs review: secrets or environment access, shell or command execution
  • Dependency/runtime risk: command execution surface, credential or environment access
  • Permission surface: secrets or environment access, shell or command execution
  • Belum ada laporan hasil Agent nyata
  • Tinjauan manusia diperlukan sebelum pemasangan tanpa pengawasan

Tindakan yang disarankan

Jalankan hanya dalam sandbox dan bandingkan alternatif terdekat sebelum digunakan untuk kerja nyata.

Profil kualitas

Sangat baik kandidat untuk alur kerja Agent

High-confidence pick with strong adoption and healthy maintenance signals.

91
Star GitHub
25K
Keterkinian
Hari ini
Siap dipasang
Ya
Lisensi
MIT
Tinjau sebelum memasang: The skill relies on an external package (openagentontology) for cryptographic operations; while this is clearly documented, the package's security posture is not independently verified by this review.

Kecocokan alur kerja

Gunakan skill ini pada skenario berikut

Kecocokan alur kerja

Tambahkan ke alur kerja lengkap

Daftar alternatif

Bandingkan sebelum memasang

Similar skills that may fit this task.

Bandingkan semua

Ringkasan

--- name: "agent-decision-receipts" description: "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-fact log analysis; not a hosted notary; not a legal opinion." ---

# Agent Decision Receipts

## Overview

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:**

1. **Does this action need a receipt?** — side-effecting + consequential + later-provable = yes. 2. **Mint the receipt** — build the action manifest, sign it with the OAO primitive. 3. **Verify it** — recompute the hash, check each signature leg, from the cert alone.

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.

## Quick Start

```bash # 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-in `pip 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.

## Core Workflow

The three decisions below are the skill: decide whether to receipt, mint, then verify.

## Decision 1: Does this action need a receipt?

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.

## Decision 2: Mint the receipt

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](references/receipt-fields.md) for the full receipt schema and the post-quantum rationale.

## Decision 3: Verify it

`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.

## Anti-Patterns

- **Receipt the log, not the decision.** Minting a receipt over a log line written after the fact proves nothing. Mint at the point of action, over the action. - **Storing the signing key next to the receipts.** If the key is compromised, signatures mean nothing. Treat the key like any signing secret; never commit it. - **Ed25519-only when the post-quantum legs are available.** A receipt is long-lived evidence. Sign it once with the post-quantum legs (ML-DSA-65 + SLH-DSA) so it stays verifiable if a future quantum computer could break Ed25519. Install `[pq]`. - **Putting raw secrets or PII in the manifest.** The manifest is hashed into evidence and is recoverable from the receipt. Carry hashes (`inputs_hash`), not the cleartext. - **Calling it "admissible."** It is evidence shaped to *support* FRE 902(13)/(14)-style certification. Admissibility is a court's decision, not the tool's claim. - **Faking a signature when crypto is missing.** The primitive emits an explicit `unsigned` flag instead. Never present an unsigned receipt as signed.

## Cross-References

- `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. - OpenAgentOntology (Apache-2.0): the open receipt primitive this skill drives — `pip install "openagentontology[pq]"`.

Detail teknis

Versi
1.0.0
Lisensi
MIT
Pembaruan terakhir
22 Agu 2026
Diterbitkan
22 Agu 2026

Ringkasan keputusan

Pilihan utama

100
Siap
Adopsi
Tahap

24,795 star GitHub

Audit

Tinjauan pemasangan

Tinjauan pemasangan dan adopsi

83
Perlu ditinjau
Keamanan
69/100
Pemeliharaan
100/100
Pasang
92/100
Buka audit lengkapLihat laporan evaluasi

Bukti tervalidasi Agent

Bukti tervalidasi Agent

Laporan hasil setelah resolve, tinjau, pasang, dan satu eksekusi terbatas.

0
Terbukti
Needs first agent runPasang otomatis: tinjau duluTerakhir: Tidak diketahui
Tingkat sukses
Kegagalan terbaru
Hasil
0
Kualitas output
Gagal
0
Tidak relevan
0
Pemasangan
0
Diblokir risiko
0
Perlu penyiapan
0
Produksi
0

Belum ada data hasil Agent. Eksekusi pertama dapat melaporkan keberhasilan, kebutuhan setup, blok risiko, kegagalan, atau tidak relevan melalui /api/agent/outcome.

Pasang

Tambahkan ke alur Agent

Gratis dan sumber terbuka. Tinjau laporan sebelum memasang pada Agent produksi.

Siklus pertumbuhan

Kit berbagi

X

Draf berbasis skenario untuk agent-decision-receipts, siap untuk posting manual di X.

Catatan kurator
agent-decision-receipts: Mint a tamper-evident, post-quantum-signed receipt for a consequential agent action (deploy,...

24.8K stars

https://www.openagentskill.com/skills/alirezarezvani-agent-decision-receipts?ref=x
Buka draf X
Balasan opsional dengan perintah pemasangan
Listing + install path for agent-decision-receipts:
https://www.openagentskill.com/skills/alirezarezvani-agent-decision-receipts?ref=x

Install: npx skills add alirezarezvani/claude-skills --skill agent-decision-receipts
Buka draf balasan

Sumber listing

Diindeks Registry

Dapat diklaim

Listing ini diindeks dari sumber publik dan belum ditandai resmi hingga klaim pemelihara disetujui.

Diindeks oleh
Indeks komunitas OpenAgentSkill

Atribusi menautkan ke repositori publik atau profil kreator. Kreator dapat mengklaim listing untuk memperbarui sinyal kepemilikan.

Klaim skill ini

Klaim pemilik

Klaim listing skill ini

Listing Diindeks Registry ini dikaitkan dengan alirezarezvani, tetapi belum ditandai resmi. Klaim untuk menambahkan sinyal pemilik terverifikasi dan membuat pembaruan peluncuran, pemasangan, serta audit berikutnya lebih tepercaya.

Kit backlink kreator

Tambahkan badge bukti ke README Anda

Tampilkan listing kanonis, sinyal kepercayaan dan audit saat ini, serta bukti Agent-Proven nyata di tempat pengembang mengevaluasi repositori.

[![Listed on OpenAgentSkill](https://www.openagentskill.com/api/badge/alirezarezvani-agent-decision-receipts?metric=listed&label=Listed)](https://www.openagentskill.com/skills/alirezarezvani-agent-decision-receipts)
[![OpenAgentSkill Trust](https://www.openagentskill.com/api/badge/alirezarezvani-agent-decision-receipts?metric=trust&label=Trust)](https://www.openagentskill.com/skills/alirezarezvani-agent-decision-receipts)
[![OpenAgentSkill Audit](https://www.openagentskill.com/api/badge/alirezarezvani-agent-decision-receipts?metric=audit&label=Audit)](https://www.openagentskill.com/skills/alirezarezvani-agent-decision-receipts/audit)
[![Agent Proven](https://www.openagentskill.com/api/badge/alirezarezvani-agent-decision-receipts?metric=proven&label=Agent%20Proven)](https://www.openagentskill.com/skills/alirezarezvani-agent-decision-receipts)

Penulis

A

alirezarezvani

@alirezarezvani

Kecocokan platform

Sinyal kesehatan

Star GitHub
24.8K
Skor kualitas
54/100
Push GitHub terakhir
22 Agu 2026
Petunjuk framework
Tidak diketahui
Tampilan OpenAgentSkill
0
Salinan pemasangan
0
Klik keluar
0

Sinyal komunitas

Bagikan apakah skill ini bermanfaat untuk alur kerja Agent Anda. Masukan gabungan meningkatkan peringkat dari waktu ke waktu.

Kepercayaan & keamanan

Hanya sandbox

66
  • Adopsi GitHub25K star GitHubLulus
  • Aktivitas star/fork25K star dan 3.5K fork; aktivitas issue tidak tersedia dalam metadata saat iniLulus
  • Pemeliharaan terbaruDiperbarui hari iniLulus
  • Kejelasan lisensiMITLulus
  • Kelengkapan README/SKILL.mdMetadata memuat konteks penggunaan dan alur kerja yang cukupLulus
  • Risiko dependensi/runtimecommand execution surface, credential or environment accessPerbaiki