agent-decision-receipts
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
Profil aset
Riset dan pekerjaan pengetahuan
Deep research, source comparison, literature review, RAG, knowledge search, and reports.
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
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 baikHigh-confidence pick with strong adoption and healthy maintenance signals.
Kepercayaan
Hanya sandboxKandidat berguna dengan sinyal kepercayaan yang kurang atau bercampur. Gunakan di ruang kerja terisolasi hingga loop hasil membuktikan kecocokan tugas.
Audit
Perlu ditinjauTinjauan 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.
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.
Tugas yang sesuai
- Alur kerja Agent riset
- Tim Claude Code
- Tim yang menghargai sinyal adopsi GitHub
- Sumber pencarian
Agent yang sesuai
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-receiptsJangan 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
Skill alternatif
Last30days Skill
53.5K Star
npx skills add mvanhorn/last30days-skill -g
Skill alternatif
Academic Research Skills
38.4K Star
npx skills add Imbad0202/academic-research-skills
Skill alternatif
GPT Researcher
28.0K Star
npx skills add assafelovic/gpt-researcher
Skill alternatif
DeepResearch
19.8K Star
npx skills add Alibaba-NLP/DeepResearch
Keamanan Agent v2
39/100 · Hindari pemasangan otomatis
Sparse or mixed signals. Useful for discovery, but not for autonomous installation.
Test manually in an isolated workspace and compare against safer alternatives.
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.
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-receiptsRencana 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 JSON
/api/agent/resolve?task=Use%20agent-decision-receipts%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Teks Resolve
/api/agent/resolve?task=Use%20agent-decision-receipts%20for%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text
Serah-terima pemasangan
/api/skills/alirezarezvani-agent-decision-receipts/install
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.
Serah-terima pemasangan
/api/skills/alirezarezvani-agent-decision-receipts/install
Format teks LLM
/api/skills/alirezarezvani-agent-decision-receipts/install?format=text
Cari alternatif
/api/skills/search?q=agent-decision-receipts&limit=3
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-receiptsMetadata Registry
Profil yang dapat dibaca Agent untuk pemilihan skill otomatis.
API Registry menyediakan sinyal keputusan, kepercayaan, audit, use case, dan pemasangan tanpa mengikis UI.
Manifest
/api/registry/manifest/alirezarezvani-agent-decision-receipts
Teks LLM
/api/registry/manifest/alirezarezvani-agent-decision-receipts?format=text
Alias pemasangan
/api/registry/install/alirezarezvani-agent-decision-receipts
Rekomendasikan
/api/registry/recommend?task=Use%20agent-decision-receipts%20in%20an%20agent%20workflow&limit=3
Kecocokan Agent
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.
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.
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
- 1Pasang di Agent sandbox dan jalankan satu tugas Agent riset dari awal hingga akhir.
- 2Compare output quality, latency, and failure behavior against at least one alternative.
- 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.
Adopsi GitHub
Lulus25K star GitHub
Aktivitas star/fork
Lulus25K star dan 3.5K fork; aktivitas issue tidak tersedia dalam metadata saat ini
Pemeliharaan terbaru
LulusDiperbarui hari ini
Kejelasan lisensi
LulusMIT
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.
Kecocokan alur kerja
Gunakan skill ini pada skenario berikut
Investigate faster
Research agents
I need my agent to research a topic, compare sources, and produce a concise report.
Reduce risk
Security and compliance
I need my agent to scan a project for security risks and summarize what needs attention.
Manage repositories
GitHub automation
I need my agent to triage GitHub issues, review pull requests, and summarize repository changes.
Kecocokan alur kerja
Tambahkan ke alur kerja lengkap
Find, compare, and synthesize
Research report agent
A workflow for agents that gather sources, compare claims, summarize long material, and draft useful research briefs.
Inspect, patch, and verify code
Coding review agent
A workflow for software agents that inspect repositories, review pull requests, generate tests, and turn findings into shippable patches.
Operate and verify web apps
Browser QA agent
A workflow for agents that navigate products, fill forms, take screenshots, and verify real user flows across web applications.
Daftar alternatif
Bandingkan sebelum memasang
Similar skills that may fit this task.
Last30days Skill
Research the last 30 days across Reddit, X, YouTube, Hacker News, Polymarket, GitHub, and the web, then synthesize a grounded brief for an AI agent.
Academic Research Skills
Academic Research Skills for Claude Code: research → write → review → revise → finalize
GPT Researcher
Run autonomous deep research over web and local sources
DeepResearch
Tongyi Deep Research, the Leading Open-source Deep Research Agent
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
24,795 star GitHub
Audit
Tinjauan pemasangan
Tinjauan pemasangan dan adopsi
- Keamanan
- 69/100
- Pemeliharaan
- 100/100
- Pasang
- 92/100
Bukti tervalidasi Agent
Bukti tervalidasi Agent
Laporan hasil setelah resolve, tinjau, pasang, dan satu eksekusi terbatas.
- 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
Draf berbasis skenario untuk agent-decision-receipts, siap untuk posting manual di X.
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
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
Sumber listing
Diindeks Registry
Listing ini diindeks dari sumber publik dan belum ditandai resmi hingga klaim pemelihara disetujui.
- Kreator
- alirezarezvani
- Diindeks oleh
- Indeks komunitas OpenAgentSkill
Atribusi menautkan ke repositori publik atau profil kreator. Kreator dapat mengklaim listing untuk memperbarui sinyal kepemilikan.
Klaim skill iniKlaim 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.
[](https://www.openagentskill.com/skills/alirezarezvani-agent-decision-receipts)
[](https://www.openagentskill.com/skills/alirezarezvani-agent-decision-receipts)
[](https://www.openagentskill.com/skills/alirezarezvani-agent-decision-receipts/audit)
[](https://www.openagentskill.com/skills/alirezarezvani-agent-decision-receipts)Penulis
alirezarezvani
@alirezarezvani
Tag
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
- 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
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