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    📚 Reference Grounding Checker

    📚 Reference Grounding Checker

    by JustHandled Labs

    Before an agent acts on a plan, verify that the things it named actually exist. Checks each referenced file path, function or method, import or package, environment variable, and CLI command against your repo, and flags the ones that do not resolve. Catches the hallucinated function and the phantom package before the edit, not after the build breaks. Resolves Python and JavaScript/TypeScript.

    Updated Jun 2026
    Security scanned
    Cursor

    $15

    · or 75 credits

    30-day refund guarantee

    Secure checkout via Stripe

    Included in download

    • Verify file paths and function names in a refactoring plan before execution
    • Catch hallucinated environment variables in deployment scripts
    • file_read, terminal, env_vars automation included
    • Ready for Cursor
    • Instant install

    Sample input

    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.

    Sample output

    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.

    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.

    Use Cases

    • Verify file paths and function names in a refactoring plan before execution
    • Catch hallucinated environment variables in deployment scripts
    • Ensure AI-suggested imports are resolving to existing local modules
    • Audit automated documentation for accuracy against the live codebase

    Reviews

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    Only users who have downloaded or purchased this skill can leave a review.

    Security Scanned

    Passed automated security review

    Permissions

    Read Files
    Terminal / Shell
    Environment Variables

    File Scopes

    reference-grounding-checker/**
    **/*.py
    **/*.js
    **/*.ts
    **/*.jsx
    **/*.tsx
    package.json
    requirements.txt
    pyproject.toml
    .env
    .env.example

    Notes: Read-only. Extracts referenced tokens from the plan and resolves them against the repo using the standard-library ast module. Reads no environment variables and writes nothing.

    Tags

    static-analysis
    plan-validation
    python
    typescript
    safety
    debugging

    Works with any agent that can read a repo and run a local Python script (Claude Code, Cursor, Codex CLI, and other SKILL.md-compatible agents). Standard library only (uses the built-in ast module), no install step. Read-only, no network.

    Creator

    JustHandled Labs

    JustHandled Labs builds focused agent skills for the work nobody wants to do by hand. Each one is a single repeatable job done well: catching the security and data mistakes that quietly ship, keeping docs and tests honest, gating the commands an agent is about to run, sharpening writing, and handling the founder chores around launches, outreach, and brand setup. Not generic AI productivity. Specific workflows that are easy to run, review, and repeat. Maintained by H.J. Westerfield, with a background in communications, editing, project coordination, customer support, and practical AI systems. Tools for people who want useful automation without theatrical complexity.

    Frequently Asked Questions

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