Agent Output Evidence and Citation Verifier
Verify agent outputs against supplied evidence using claim extraction, source matching, contradiction checks, confidence, unsupported-claim handling, and review gates.
Agent Output Evidence and Citation Verifier is a free AI skill for agent systems & llm workflows. Verify agent outputs against supplied evidence using claim extraction, source matching, contradiction checks, confidence, unsupported-claim handling, and review gates. It works with Claude, ChatGPT and is ready to use out of the box.
About this skill
Verify agent outputs against supplied evidence using claim extraction, source matching, contradiction checks, confidence, unsupported-claim handling, and review gates. It applies a structured workflow, labels assumptions, and produces implementation-ready guidance with ownership, controls, edge cases, and validation.
What it does
The skill analyzes goals, evidence, stakeholders, workflows, dependencies, constraints, and risks; converts them into a practical operating model; and produces explicit rules, responsibilities, exceptions, controls, tests, and rollout guidance.
What is included
- Verification context
- Claim inventory
- Risk classification
- Source mapping
- Citation quality
- Contradictions and unsupported claims
- Calculation checks
- Corrected wording
How to use it
1. Download the agent-output-evidence-and-citation-verifier-SKILL.md file 2. Upload it to your AI, operational, or project workspace 3. Provide the current process, users, goals, evidence, and constraints 4. Add ownership, approval, risk, and implementation requirements 5. Use the output for design, review, testing, or rollout
Examples
Verify an AI research agent report against uploaded documents and web sources before the report is published or used for a decision.
A complete professional deliverable with context, decisions, ownership, workflows, edge cases, risks, controls, validation criteria, and an implementation roadmap.
FAQ
What is this skill for?
Will it invent facts or results?
Can it improve an existing process?
Does it include edge cases?
Can it assign ownership?
How is this different from generic advice?
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