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
Perfil del activo
Investigación y trabajo de conocimiento
Deep research, source comparison, literature review, RAG, knowledge search, and reports.
Escenario
Agents de investigación
I need my agent to research a topic, compare sources, and produce a concise report.
Afinidad con Agent
Claude Code + CLI + Codex
Funciona con Codex, Claude Code, Cursor, CLI o Agents personalizados.
Instalar
Listo
npx skills add alirezarezvani/claude-skills --skill agent-decision-receipts
Mantenimiento
Actual
1 días desde el último push
Riesgo
Requiere revisión
Dependency or permission surface needs review
Calidad de GitHub
25K
91/100 Calidad · 74/100 Confianza
Etiquetas de cobertura
Notas de revisión
Dependency or permission surface needs review · Permission surface may require sandboxing
Tarjeta de adopción del Agent
Confianza, auditoría y preparación de instalación de un vistazo
Estas puntuaciones combinan metadatos públicos del repositorio, señales de revisión de OpenAgentSkill, actualidad de mantenimiento y preparación de instalación. Sirven para preseleccionar; no sustituyen la revisión humana.
Calidad
ExcelenteHigh-confidence pick with strong adoption and healthy maintenance signals.
Confianza
Solo sandboxCandidata útil con señales de confianza incompletas o mixtas. Manténgala en un espacio aislado hasta que el ciclo de resultados demuestre el ajuste.
Auditoría
Requiere revisiónRevisión legible por máquina de la preparación de instalación, los metadatos de seguridad, el mantenimiento y el riesgo de adopción.
Trust Score de OpenAgentSkill v5
Revisión humana antes de instalar
Ejecute solo en un sandbox y compare alternativas cercanas antes de usarla en trabajo real.
Estrellas
25K estrellas de GitHub
Actividad del repositorio
25K estrellas y 3.5K forks
Mantenimiento
1 días desde el último push
Licencia
MIT
Instalar
npx skills add alirezarezvani/claude-skills --skill agent-decision-receipts
Seguridad de instalación
Ruta estándar de paquete o instalación en tiempo de ejecución
Superficie de permisos
secrets or environment access, shell or command execution
Resultados del Agent
Aún no hay datos de resultados del Agent
Documentación
Contexto sólido de README/SKILL.md
Resumen de riesgo
Revisar antes de producción
- 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
Preparación de instalación
Ruta de instalación disponible
- La ruta de instalación está disponible
- La evidencia del repositorio está disponible
- La licencia está declarada
- Aún no hay evidencia de resultados Agent-Proven
Metadatos legibles por Agent
Datos de decisión legibles por máquina para este skill.
Usa este bloque o el JSON integrado para decidir si un Agent debe instalar este skill, elegir una alternativa o pedir revisión humana primero.
Tareas adecuadas
- Flujos de Agents de investigación
- Equipos de Claude Code
- Equipos que valoran señales de adopción de GitHub
- Fuentes de búsqueda
Agents adecuados
Decisión de instalación
- Comando
- npx skills add alirezarezvani/claude-skills --skill agent-decision-receipts
- Política
- Revisar
- Revisión humana
- Sí
Confianza y riesgo
- Confianza
- 66/100
- Auditoría
- 83/100
- Nivel de riesgo
- Requiere revisión
Ciclo de resultados
- Endpoint
- /api/agent/outcome
- ID del evento
- resolve
- Resultados
- 5
Comando de instalación
npx skills add alirezarezvani/claude-skills --skill agent-decision-receiptsNo usar cuando
- Equipos que necesitan un SLA con soporte del proveedor
- 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.
- Indicios de permisos de alto riesgo: Shell or command execution, Secrets or environment access
- Dependency or permission surface needs review
Skill alternativo
Last30days Skill
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28.0K Estrellas
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Skill alternativo
DeepResearch
19.8K Estrellas
npx skills add Alibaba-NLP/DeepResearch
Seguridad de Agent v2
39/100 · Evitar instalación automática
Sparse or mixed signals. Useful for discovery, but not for autonomous installation.
Test manually in an isolated workspace and compare against safer alternatives.
Alto
Ejecución de shell o comandos
Los metadatos del skill hacen referencia a terminal, CLI, shell, subprocesos o flujos de ejecución de comandos.
Medio
Acceso a red
El skill probablemente consulta páginas remotas, API, repositorios o servicios externos.
Medio
Acceso al sistema de archivos
El skill puede leer o escribir archivos de proyecto, documentos, artefactos generados o estado local.
Alto
Secrets or environment access
Skill metadata references credentials, tokens, environment variables, or secret-bearing workflows.
- Indicios de permisos de alto riesgo: Shell or command execution, Secrets or environment access
- Dependency or permission surface needs review
Destinos de instalación
Instala este skill en tu flujo de Agent
Usa el endpoint público para obtener el comando, la lista de seguridad, prompts y enlaces canónicos.
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-receiptsPlan de resolución de Agent
Deja que un Agent valide el ajuste antes de instalar.
La API Resolve devuelve la skill elegida, alternativas, política de seguridad, notas de auditoría, destino de instalación y un prompt listo para usar.
Abrir JSON
/api/agent/resolve?task=Use%20agent-decision-receipts%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Texto de Resolve
/api/agent/resolve?task=Use%20agent-decision-receipts%20for%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text
Traspaso de instalación
/api/skills/alirezarezvani-agent-decision-receipts/install
Agent debe revisar
- 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.
Copiar 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.Traspaso de Agent
Da al Agent la ruta de instalación, no otro directorio.
Usa el endpoint público para obtener el comando, la lista de seguridad, prompts y enlaces canónicos.
Traspaso de instalación
/api/skills/alirezarezvani-agent-decision-receipts/install
Formato de texto LLM
/api/skills/alirezarezvani-agent-decision-receipts/install?format=text
Buscar alternativas
/api/skills/search?q=agent-decision-receipts&limit=3
Prompt de 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-receiptsMetadatos del Registry
Perfil legible por Agent para seleccionar skills automáticamente.
La API Registry expone señales de decisión, confianza, auditoría, casos de uso e instalación sin raspar la interfaz.
Manifest
/api/registry/manifest/alirezarezvani-agent-decision-receipts
Texto LLM
/api/registry/manifest/alirezarezvani-agent-decision-receipts?format=text
Alias de instalación
/api/registry/install/alirezarezvani-agent-decision-receipts
Recomendar
/api/registry/recommend?task=Use%20agent-decision-receipts%20in%20an%20agent%20workflow&limit=3
Afinidad con Agent
Agents de investigación
Etiquetas de uso
Plataformas
Claude Code
Informe de auditoría
Requiere revisión · 83/100
Revisión legible por máquina de la preparación de instalación, los metadatos de seguridad, el mantenimiento y el riesgo de adopción.
Panel de decisión de Agent
Elección principal para Agents de investigación
Use this as a leading candidate, then validate the README and install path in your own agent stack.
Rol en la pila
Elección principal
Ajuste principal
Agents de investigación
Etiqueta de confianza
Listo para producción
Ruta de instalación
Comando listo
Úsalo cuando
- Flujos de Agents de investigación
- Equipos de Claude Code
- Equipos que valoran señales de adopción de GitHub
Evidencia
- 24,795 estrellas de GitHub
- recent repository activity
- install command or GitHub repo available
- perfil de calidad 91/100
- 3 eventos de interacción de OpenAgentSkill
revisar primero
- 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.
Ruta de implementación
- 1Instálalo en un Agent de sandbox y ejecuta una tarea de Agents de investigación de principio a fin.
- 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.
Perfil de confianza
Solo sandbox
Candidata útil con señales de confianza incompletas o mixtas. Manténgala en un espacio aislado hasta que el ciclo de resultados demuestre el ajuste.
Adopción en GitHub
Aprobado25K estrellas de GitHub
Actividad de stars/forks
Aprobado25K estrellas y 3.5K forks; la actividad de issues no está disponible en los metadatos actuales
Mantenimiento reciente
Aprobado1 días desde el último push
Claridad de licencia
AprobadoMIT
Señales positivas
- Revisión de IA aprobada
- La ruta de instalación está disponible
- La evidencia del repositorio está disponible
- Repositorio mantenido recientemente
- Large GitHub adoption signal
- El comando de instalación no muestra un patrón de alto riesgo evidente
- El ciclo de resultados está listo, pero necesita la primera ejecución real de Agent
Revisar antes de instalar
- 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
- Aún no hay informes reales de resultados del Agent
- Se requiere revisión humana antes de una instalación desatendida
Acción recomendada
Ejecute solo en un sandbox y compare alternativas cercanas antes de usarla en trabajo real.
Perfil de calidad
Excelente candidato para flujos de Agent
High-confidence pick with strong adoption and healthy maintenance signals.
Ajuste de flujo
Usa esta skill en estos escenarios
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.
Ajuste de flujo
Añadir a un flujo completo
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.
Lista de alternativas
Compara antes de instalar
Similar skills that may fit this task.
Last30days Skill
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GPT Researcher
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DeepResearch
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Resumen
--- 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]"`.
Detalles técnicos
- Versión
- 1.0.0
- Licencia
- MIT
- Última actualización
- 22 ago 2026
- Publicado
- 22 ago 2026
Resumen de decisión
Elección principal
24,795 estrellas de GitHub
Auditoría
Revisión de instalación
Revisión de instalación y adopción
- Seguridad
- 69/100
- Mantenimiento
- 100/100
- Instalar
- 92/100
Evidencia probada por Agent
Evidencia probada por Agent
Informes de resultados tras resolver, revisar, instalar y una ejecución limitada.
- Tasa de éxito
- —
- Fallo reciente
- —
- Resultados
- 0
- Calidad de salida
- —
- Fallidos
- 0
- No relevante
- 0
- Instalaciones
- 0
- Bloqueado por riesgo
- 0
- Configuración necesaria
- 0
- Producción
- 0
Aún no hay datos de resultados de Agent. La primera ejecución puede informar éxito, configuración necesaria, bloqueos de riesgo, fallo o irrelevancia mediante /api/agent/outcome.
Instalar
Añadir al flujo de Agent
Gratis y de código abierto. Revisa el informe antes de instalar en Agents de producción.
Bucle de crecimiento
Kit para compartir
Borrador basado en un caso para agent-decision-receipts, listo para publicar manualmente en 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
Respuesta opcional con comando de instalación
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
Fuente de la ficha
Indexado por Registry
Esta ficha se indexó desde fuentes públicas y no está marcada como oficial hasta que se apruebe una reclamación de mantenedor.
- Creador
- alirezarezvani
- Indexado por
- Índice comunitario de OpenAgentSkill
La atribución enlaza al repositorio público o al perfil del creador. Los creadores pueden reclamar la ficha para actualizar las señales de propiedad.
Reclamar este skillReclamación del propietario
Reclamar esta ficha de skill
Esta ficha Indexado por Registry se atribuye a alirezarezvani, pero aún no está marcada como oficial. Reclámala para añadir una señal de propietario verificado y hacer más fiables futuras actualizaciones de lanzamiento, instalación y auditoría.
Kit de enlaces para creadores
Añade las insignias de evidencia a tu README
Muestra la ficha canónica, las señales actuales de confianza y auditoría, y evidencia real de Agent-Proven donde los desarrolladores evalúan el repositorio.
[](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)Autor
alirezarezvani
@alirezarezvani
Etiquetas
Afinidad con plataforma
Señales de salud
- Estrellas de GitHub
- 24.8K
- Puntuación de calidad
- 54/100
- Último push de GitHub
- 22 ago 2026
- Pistas del framework
- Desconocido
- Vistas de OpenAgentSkill
- 3
- Copias de instalación
- 0
- Clics externos
- 0
Señal de comunidad
Comparte si este skill resulta útil para tu flujo de Agent. Los comentarios agregados mejoran la clasificación con el tiempo.
Confianza y seguridad
Solo sandbox
- Adopción en GitHub25K estrellas de GitHubAprobado
- Actividad de stars/forks25K estrellas y 3.5K forks; la actividad de issues no está disponible en los metadatos actualesAprobado
- Mantenimiento reciente1 días desde el último pushAprobado
- Claridad de licenciaMITAprobado
- Completitud de README/SKILL.mdLos metadatos incluyen suficiente contexto de uso y flujo de trabajoAprobado
- Riesgo de dependencias/runtimecommand execution surface, credential or environment accessCorregir
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