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
Asset-Profil
Recherche und Wissensarbeit
Deep research, source comparison, literature review, RAG, knowledge search, and reports.
Szenario
Recherche-Agents
I need my agent to research a topic, compare sources, and produce a concise report.
Agent-Fit
Claude Code + CLI + Codex
Geeignet für Codex, Claude Code, Cursor, CLI oder benutzerdefinierte Agents.
Installieren
Bereit
npx skills add alirezarezvani/claude-skills --skill agent-decision-receipts
Wartung
Aktuell
Heute gepusht
Risiko
Prüfung nötig
Dependency or permission surface needs review
GitHub-Qualität
25K
91/100 Qualität · 74/100 Vertrauen
Abdeckungs-Tags
Review-Notizen
Dependency or permission surface needs review · Permission surface may require sandboxing
Agent-Adoptionskarte
Vertrauen, Audit und Installationsbereitschaft auf einen Blick
Diese Werte kombinieren öffentliche Repository-Metadaten, OpenAgentSkill-Reviewsignale, Wartungsaktualität und Installationsbereitschaft. Sie helfen bei der Vorauswahl, ersetzen aber keine menschliche Prüfung.
Qualität
AusgezeichnetHigh-confidence pick with strong adoption and healthy maintenance signals.
Vertrauen
Nur SandboxNützlicher Kandidat mit fehlenden oder gemischten Vertrauenssignalen. Bis der Ergebniszyklus die Passung belegt, in einem isolierten Arbeitsbereich verwenden.
Audit
Prüfung nötigMaschinenlesbare Prüfung von Installationsbereitschaft, Sicherheitsmetadaten, Wartung und Akzeptanzrisiko.
OpenAgentSkill Trust Score v5
Menschliche Prüfung vor Installation
Nur in einer Sandbox ausführen und nahe Alternativen vergleichen, bevor sie produktiv eingesetzt wird.
Stars
25K GitHub-Stars
Repository-Aktivität
25K Stars und 3.5K Forks
Wartung
Heute gepusht
Lizenz
MIT
Installieren
npx skills add alirezarezvani/claude-skills --skill agent-decision-receipts
Installationssicherheit
Standard-Paket- oder Laufzeit-Installationspfad
Berechtigungsfläche
secrets or environment access, shell or command execution
Agent-Ergebnisse
Noch keine Agent-Ergebnisdaten
Dokumentation
Starker README/SKILL.md-Kontext
Risikoübersicht
Vor Produktion prüfen
- 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
Installationsbereitschaft
Installationspfad verfügbar
- Installationspfad ist verfügbar
- Repository-Belege sind verfügbar
- Lizenz ist angegeben
- Noch keine Agent-Proven-Ergebnisbelege
Agent-lesbare Metadaten
Maschinenlesbare Entscheidungsdaten für diesen Skill.
Nutze diesen Block oder das eingebettete JSON, um zu entscheiden, ob ein Agent diesen Skill installieren, eine Alternative wählen oder zuerst menschliche Prüfung anfordern soll.
Geeignete Aufgaben
- Research-Agent-Workflows
- Claude-Code-Teams
- Teams, die GitHub-Adoptionssignale schätzen
- Suchquellen
Geeignete Agents
Installationsentscheidung
- Befehl
- npx skills add alirezarezvani/claude-skills --skill agent-decision-receipts
- Richtlinie
- Prüfen
- Menschliche Prüfung
- Ja
Vertrauen und Risiko
- Vertrauen
- 66/100
- Audit
- 83/100
- Risikoebene
- Prüfung nötig
Ergebnis-Loop
- Endpoint
- /api/agent/outcome
- Event-ID
- resolve
- Ergebnisse
- 5
Installationsbefehl
npx skills add alirezarezvani/claude-skills --skill agent-decision-receiptsNicht verwenden, wenn
- Teams, die ein vom Anbieter unterstütztes SLA benötigen
- 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
- Hinweise auf Hochrisiko-Berechtigungen: Shell or command execution, Secrets or environment access
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Agent-Sicherheit v2
39/100 · Automatische Installation vermeiden
Sparse or mixed signals. Useful for discovery, but not for autonomous installation.
Test manually in an isolated workspace and compare against safer alternatives.
Hoch
Shell- oder Befehlsausführung
Die Skill-Metadaten verweisen auf Terminal-, CLI-, Shell-, Subprozess- oder Befehlsausführungs-Workflows.
Mittel
Netzwerkzugriff
Die Skill ruft wahrscheinlich Remote-Seiten, APIs, Repositories oder externe Dienste ab.
Mittel
Dateisystemzugriff
Die Skill kann Projektdateien, Dokumente, generierte Artefakte oder den lokalen Arbeitsbereich lesen oder schreiben.
Hoch
Secrets or environment access
Skill metadata references credentials, tokens, environment variables, or secret-bearing workflows.
- Hinweise auf Hochrisiko-Berechtigungen: Shell or command execution, Secrets or environment access
- Dependency or permission surface needs review
Installationsziele
Diesen Skill im Agent-Workflow installieren
Über den öffentlichen Endpunkt erhältst du Befehl, Sicherheitscheckliste, Ziel-Prompts und kanonische Links.
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-receiptsAgent-Auflösungsplan
Lass einen Agent die Eignung vor der Installation prüfen.
Die Resolve API liefert die beste Skill, Alternativen, Sicherheitsrichtlinien, Auditnotizen, Installationsziel und einen direkt nutzbaren Prompt.
JSON öffnen
/api/agent/resolve?task=Use%20agent-decision-receipts%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Resolve-Text
/api/agent/resolve?task=Use%20agent-decision-receipts%20for%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text
Installationsübergabe
/api/skills/alirezarezvani-agent-decision-receipts/install
Agent sollte prüfen
- 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.
Prompt kopieren
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.Agent-Übergabe
Gib dem Agent den Installationspfad, nicht noch ein Verzeichnis.
Über den öffentlichen Endpunkt erhältst du Befehl, Sicherheitscheckliste, Ziel-Prompts und kanonische Links.
Installationsübergabe
/api/skills/alirezarezvani-agent-decision-receipts/install
LLM-Textformat
/api/skills/alirezarezvani-agent-decision-receipts/install?format=text
Alternativen finden
/api/skills/search?q=agent-decision-receipts&limit=3
Agent-Prompt
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-receiptsRegistry-Metadaten
Agent-lesbares Profil für die automatische Skill-Auswahl.
Die Registry API stellt Entscheidungs-, Vertrauens-, Audit-, Use-Case- und Installationssignale ohne UI-Scraping bereit.
Manifest
/api/registry/manifest/alirezarezvani-agent-decision-receipts
LLM-Text
/api/registry/manifest/alirezarezvani-agent-decision-receipts?format=text
Installationsalias
/api/registry/install/alirezarezvani-agent-decision-receipts
Empfehlen
/api/registry/recommend?task=Use%20agent-decision-receipts%20in%20an%20agent%20workflow&limit=3
Agent-Fit
Recherche-Agents
Plattformen
Claude Code
Audit-Bericht
Prüfung nötig · 83/100
Maschinenlesbare Prüfung von Installationsbereitschaft, Sicherheitsmetadaten, Wartung und Akzeptanzrisiko.
Agent-Entscheidungspanel
Primäre Wahl für Recherche-Agents
Use this as a leading candidate, then validate the README and install path in your own agent stack.
Rolle im Stack
Primäre Wahl
Primäre Eignung
Recherche-Agents
Vertrauenslabel
Produktionsbereit
Installationspfad
Befehl bereit
Verwenden wenn
- Research-Agent-Workflows
- Claude-Code-Teams
- Teams, die GitHub-Adoptionssignale schätzen
Evidenz
- 24,795 GitHub-Stars
- recent repository activity
- install command or GitHub repo available
- Qualitätsprofil 91/100
zuerst prüfen
- 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
Implementierungspfad
- 1Installieren Sie es in einem Sandbox-Agent und führen Sie eine Recherche-Agents-Aufgabe vollständig aus.
- 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.
Vertrauensprofil
Nur Sandbox
Nützlicher Kandidat mit fehlenden oder gemischten Vertrauenssignalen. Bis der Ergebniszyklus die Passung belegt, in einem isolierten Arbeitsbereich verwenden.
GitHub-Akzeptanz
Bestanden25K GitHub-Stars
Star-/Fork-Aktivität
Bestanden25K Stars und 3.5K Forks; Issue-Aktivität ist in den aktuellen Metadaten nicht verfügbar
Aktuelle Wartung
BestandenHeute gepusht
Lizenzklarheit
BestandenMIT
Positive Signale
- KI-Prüfung genehmigt
- Installationspfad ist verfügbar
- Repository-Belege sind verfügbar
- Kürzlich gewartetes Repository
- Large GitHub adoption signal
- Der Installationsbefehl weist kein offensichtliches Hochrisikomuster auf
- Ergebniszyklus ist bereit, benötigt aber den ersten echten Agent-Lauf
Vor Installation prüfen
- 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
- Noch keine echten Agent-Ergebnisberichte
- Vor unbeaufsichtigter Installation ist menschliche Prüfung erforderlich
Empfohlene Aktion
Nur in einer Sandbox ausführen und nahe Alternativen vergleichen, bevor sie produktiv eingesetzt wird.
Qualitätsprofil
Ausgezeichnet Kandidat für Agent-Workflows
High-confidence pick with strong adoption and healthy maintenance signals.
Workflow-Eignung
Diese Skill in diesen Szenarien nutzen
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.
Workflow-Eignung
Zum vollständigen Workflow hinzufügen
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.
Alternativen-Shortlist
Vor Installation vergleichen
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
Übersicht
--- 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]"`.
Technische Details
- Version
- 1.0.0
- Lizenz
- MIT
- Letzte Aktualisierung
- 22. Aug. 2026
- Veröffentlicht
- 22. Aug. 2026
Entscheidungsübersicht
Primäre Wahl
24,795 GitHub-Stars
Audit
Installationsprüfung
Installations- und Adoptionsprüfung
- Sicherheit
- 69/100
- Wartung
- 100/100
- Installieren
- 92/100
Von Agent belegte Evidenz
Von Agent belegte Evidenz
Ergebnisberichte nach Resolve, Prüfung, Installation und einem begrenzten Lauf.
- Erfolgsrate
- —
- Letzter Fehler
- —
- Ergebnisse
- 0
- Ausgabequalität
- —
- Fehlgeschlagen
- 0
- Nicht relevant
- 0
- Installationen
- 0
- Durch Risiko blockiert
- 0
- Einrichtung erforderlich
- 0
- Produktion
- 0
Noch keine Agent-Ergebnisdaten. Der erste Lauf kann Erfolg, Einrichtungsbedarf, Risikoblockaden, Fehler oder Irrelevanz über /api/agent/outcome melden.
Installieren
Zum Agent-Workflow hinzufügen
Kostenlos und Open Source. Bericht vor der Installation in Produktions-Agents prüfen.
Wachstums-Loop
Share-Kit
Szenariobasierter Entwurf für agent-decision-receipts, bereit für einen manuellen X-Post.
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
Optionale Antwort mit Installationsbefehl
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
Quelle des Eintrags
Registry-indexiert
Dieser Eintrag wurde aus öffentlichen Quellen indexiert und ist erst nach Genehmigung eines Maintainer-Anspruchs offiziell.
- Ersteller
- alirezarezvani
- Indexiert von
- OpenAgentSkill Community-Index
Die Zuordnung verlinkt auf das öffentliche Repository oder Creator-Profil. Creator können den Eintrag beanspruchen, um Eigentümersignale zu aktualisieren.
Diesen Skill beanspruchenEigentümeranspruch
Diesen Skill-Eintrag beanspruchen
Dieser Registry-indexiert-Eintrag wird alirezarezvani zugeschrieben, ist aber noch nicht offiziell markiert. Beanspruche ihn, um ein verifiziertes Eigentümersignal hinzuzufügen und künftige Launch-, Installations- und Audit-Updates vertrauenswürdiger zu machen.
Creator-Backlink-Kit
Evidenz-Badges in deine README einfügen
Zeige den kanonischen Eintrag, aktuelle Vertrauens- und Audit-Signale sowie echte Agent-Proven-Evidenz dort, wo Entwickler das Repository bewerten.
[](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
Tags
Plattform-Fit
Gesundheitssignale
- GitHub-Stars
- 24.8K
- Qualitätswert
- 54/100
- Letzter GitHub-Push
- 22. Aug. 2026
- Framework-Hinweise
- Unbekannt
- OpenAgentSkill-Aufrufe
- 0
- Installationskopien
- 0
- Externe Klicks
- 0
Community-Signal
Teile mit, ob dieser Skill für deinen Agent-Workflow nützlich ist. Zusammengefasstes Feedback verbessert das Ranking im Laufe der Zeit.
Vertrauen & Sicherheit
Nur Sandbox
- GitHub-Akzeptanz25K GitHub-StarsBestanden
- Star-/Fork-Aktivität25K Stars und 3.5K Forks; Issue-Aktivität ist in den aktuellen Metadaten nicht verfügbarBestanden
- Aktuelle WartungHeute gepushtBestanden
- LizenzklarheitMITBestanden
- README/SKILL.md-VollständigkeitMetadaten enthalten ausreichend Nutzungs- und Workflow-KontextBestanden
- Abhängigkeits-/Laufzeitrisikocommand execution surface, credential or environment accessBeheben
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