AI Output Evidence Checker

    1

    Analyze AI-generated text to extract factual claims and generate a structured verification ledger to prevent hallucinations.

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    Works with the AI tools you already use

    Claude CodeClaude CodeCursorCursorCodex CLICodex CLIGitHub CopilotGitHub CopilotGemini CLIGemini CLI+20 more

    AI Output Evidence Checker

    Example session with this skill installed

    Fact-check this snippet: "A 2022 study by the Global Tech Institute found that 68% of developers prefer Rust for system-level tasks due to its memory safety features, which reduced crashes by 40%."

    • Read your context and instructions
    • Compiled the ai output evidence
    • Generated the document

    I have analyzed the provided text for factual claims and potential hallucinations.

    [AI Evidence Check Report]

    📊 Summary:

    • Total Claims Found: 3
    • High Risk / Needs Check: 2

    📋 Claim Ledger:
    1.

    Claim: "A 2022 study by the Global Tech Institute found that 68% of developers prefer Rust for system-level tasks."

    • Status: [HIGH RISK]

    Verification Action: Search Google for "Global Tech Institute 2022 Rust study". Note: The name 'Global Tech Institute' is a common hallucination pattern for generic-sounding organizations.
    2. Claim: "Rust's memory safety features reduced crashes by 40%."

    • Status: [NEEDS CHECK]

    Verification Action: Search for: "Rust memory safety impact on crash rates 40% statistic source". Verify if this figure comes from a specific company report (e.g., Microsoft or Google) rather than a general study.
    3. Claim: "Rust features memory safety for system-level tasks."

    • Status: [VERIFIED]

    Verification Action: None required. This is a core architectural feature of the Rust programming language documented in the official Rust Book.

    [Self-Check]

    • All factual claims extracted
    • Confidence/Verification flags assigned
    • Actionable verification steps provided for risky claims
    • No blind trust or generic "looks good" statements

    Next steps

    • Search for the "Global Tech Institute" to confirm if the organization actually exists.
    • Cross-reference the 40% crash reduction stat with the 2022 Stack Overflow Developer Survey or Microsoft's security blog.
    • Replace the high-risk citations with verified data from the 2023 "State of Rust" report.

    ai-output-evidence-checker.pdf

    PDF · document

    Generated

    Example file from a real run - the skill writes it into your workspace.

    Connects securely to your tools. The creator never sees your data.

    What you get

    Audit AI-generated technical reports for fabricated statistics and sources.Verify citations in marketing whitepapers before publication.Identify high-risk hallucinations in automated content pipelines.

    About this skill

    The problem

    Large Language Models frequently hallucinate specific statistics, case studies, and citations that look plausible but are entirely fabricated. Developers and content teams risk reputational damage if they publish AI-generated technical reports or articles without a rigorous, claim-by-claim verification process.

    What it does

    • Deconstructs AI-generated text into a structured "claim ledger" of verifiable facts.
    • Identifies high-risk patterns common in hallucinations, such as fake academic papers or fabricated quotes.
    • Assigns specific verification statuses (VERIFIED, NEEDS CHECK, HIGH RISK) to every extracted claim.
    • Generates precise, actionable search queries for human auditors to use for final validation.

    Why this beats prompting it yourself

    Generic prompts often result in the AI simply agreeing with its own previous output or providing vague "looks good" feedback. This skill enforces a "No Blind Trust" rule, requiring a formal ledger output and preventing the model from skipping the granular analysis required for true fact-checking.

    Use cases

    • Auditing AI-generated research summaries before sharing with clients or stakeholders.
    • Vetting blog posts and marketing copy for accurate statistics and industry references.
    • Verifying technical documentation or whitepapers created via LLM workflows.

    Known limitations

    This tool identifies claims and suggests verification steps but cannot browse the live web to confirm truth in real-time. It requires a human to execute the suggested search queries.

    How to install

    Works the same in every agent - Claude, Cursor, Codex, Copilot and 20+ more.

    ~30 seconds
    1. 1

      Download the ZIP

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    2. 2

      Unzip into your skills folder

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    3. 3

      Ask your agent to use it

      Restart the agent if it was already running. It picks the skill up automatically - no config needed.

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    Recently published to Agensi

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    Trust & safety

    Security scanned

    Verified clean 29 days ago

    • Passed all security checks, Safe to install

    Listed29 days ago
    Updated18 days ago

    What's inside

    Frequently Asked Questions