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    📚 Reference Grounding Checker

    1

    It eliminates "hallucinated" refactoring plans before they break your build.

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    See it in action

    You say

    I've drafted a plan to refactor the auth logic. Check this plan against the repo to make sure I haven't referenced any nonexistent functions or files.

    Your agent does

    Grounding Report

    • Files Checked: 4
    • References Verified: 12
    • Findings:
      • [High] utils/token-helper.ts not found. (Line 12)
      • [Med] Function verifySession() is exported from auth/core.ts, not auth/session.ts as suggested.
    • Suggestion: Update plan lines 12 and 15.

    What you get

    Verify file paths and function names in a refactoring plan before executionCatch hallucinated environment variables in deployment scriptsEnsure AI-suggested imports are resolving to existing local modulesAudit automated documentation for accuracy against the live codebase

    About this skill

    What it does

    The Reference Grounding Checker acts as a pre-execution safety layer for AI agents. It scans proposed implementation plans to verify that every file path, function name, import statement, and environment variable mentioned actually exists within your local codebase. It eliminates "hallucinated" refactoring plans before they break your build.

    Why use this skill

    Even advanced LLMs frequently reference non-existent utility functions or assume the presence of configuration variables that aren't there. This skill provides a deterministic check against the ground truth of your file system and source code. It is significantly more reliable than standard prompting because it uses a specialized static analysis scanner to perform hard lookups, rather than relying on the model's memory of the repo.

    Supported tools

    • Languages: Python, JavaScript, TypeScript.
    • Environments: Local repositories, CI/CD pipelines, and agentic workflows like Claude Code or Cursor.
    • Inputs: Markdown plans, text files, or direct chat history.

    Expected Output

    You receive a structured report detailing every reference checked, categorized findings by severity (e.g., Missing File, Unresolved Import), and specific remediation snippets to fix the plan's logic.

    ai-agents
    static-analysis
    plan-validation
    python
    typescript
    safety
    debugging

    How to install

    Drop the file into your AI Agent. Works with Claude, Cursor, ChatGPT, and 20+ more.

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