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    🧪 AI Build Sanity Check

    by JustHandled Labs

    Check an AI-built app for work that looks finished but is not: leftover TODOs and stubs, fake or mock data returned as real, errors quietly swallowed, placeholder content, and endpoints that fake success. Read-only, every finding explained in plain English for non-coders.

    Updated Jul 2026
    Security scanned
    Cursor

    $13

    · or 65 credits

    30-day refund guarantee

    Secure checkout via Stripe

    Included in download

    • Identify hardcoded mock data in API responses
    • Find silently swallowed exceptions and empty catch blocks
    • file_read automation included
    • Ready for Cursor
    • Instant install

    Media gallery

    See it in action

    You say

    Scan the current repo. Did the AI actually finish this or are there still mocks and placeholders?

    Your agent does

    Findings:

    • ABS002 (High): src/api/user.ts returns static user object.
    • ABS005 (Medium): /api/payment returns 200 OK without calling Stripe SDK.
    • ABS003 (Low): auth.py line 42 swallows ConnectionError.

    Review remediation-snippets.md to fix these stubs.

    About This Skill

    The problem

    AI coding tools often generate boilerplate that looks complete but contains stubs, mock data, or swallowed errors. Developers lose time manually hunting for placeholders and fake endpoints before a production push.

    What it does

    • Identifies hardcoded mock data being returned as production results.
    • Locates empty error handlers and silently swallowed exceptions.
    • Detects API endpoints that return hardcoded success responses without execution.
    • Flags placeholder text, leftover build markers, and throwing handlers in named features.
    • Provides remediation snippets for fixing identified gaps.

    Frameworks & tools

    Works with Python, JavaScript, TypeScript, React (JSX/TSX), HTML, and JSON configuration files.

    Why this beats prompting it yourself

    General prompts often miss subtle "lazy" code patterns like 200 OK responses with no logic. This skill uses specific rule IDs to ensure consistent auditing across your entire codebase without the hallucinations of a standard review prompt.

    Use cases

    • Auditing an AI-generated MVP before showing it to a client.
    • Checking a fresh pull request for hidden TODOs or stubbed logic.
    • Validating that a refactor didn't leave behind mock data used for testing.

    Known limitations

    This is a heuristic scanner, not a formal verification tool. It identifies patterns of incomplete work but does not guarantee the logical correctness or security of the remaining code.

    Use Cases

    • Identify hardcoded mock data in API responses
    • Find silently swallowed exceptions and empty catch blocks
    • Locate placeholder UI text and build markers
    • Audit endpoints that return success without executing work

    Reviews

    No reviews yet - be the first to share your experience.

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

    Security Scanned

    Passed automated security review

    Permissions

    Read Files

    Allowed Hosts

    www.agensi.io

    File Scopes

    ai-build-sanity-check/**
    **/*.py
    **/*.js
    **/*.ts
    **/*.jsx
    **/*.tsx
    **/*.html
    **/*.json
    **/*.env

    This skill needs Read Files only. It reads your source files to scan for unfinished or fake work, and reads its own references/sanity-rules.json for the patterns it looks for. That includes reading .env files as plain text to catch leftover placeholders, but it does not read the live environment, use any secret values, or send anything anywhere. Findings are returned as text in the conversation. It does not write to disk, run shell commands, or make network calls.

    Tags

    code-review
    quality-assurance
    python
    typescript
    static-analysis

    Runs anywhere a coding agent can execute a Python 3 script. Tested with Claude Code, Cursor, Codex CLI, Windsurf, and Cline. Python 3 standard library only: no third-party packages, no network calls, and it never runs your code. Scans Python, JavaScript, TypeScript, JSX/TSX, HTML, JSON, and .env files. The markers, placeholder strings, and mock-data cues it looks for live in references/sanity-rules.json, which you can edit.

    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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