Done-Check: Tests, Leftovers & Junk Files

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    Stops "done" without evidence: runs the tests and flags debug prints, skipped tests and junk files in one call.

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    Done-Check: Tests, Leftovers & Junk Files

    Example session with this skill installed

    I've updated slugify to handle punctuation. Verify everything before I commit.

    • Read your context and instructions
    • Compiled the done-check

    Real session on a small Python repo. The script output is pasted as-is.

    Summary

    The first check found 3 problems: a debug print, a skipped test and a .orig backup file. After fixing them, the second check passes with 2 tests run and nothing skipped. The behavior the request asked for is confirmed by running it.

    1. First check

    $ python3 scripts/verify.py
[PASS] tests: PASS (exit 0) 1 passed, 1 skipped in 0.07s
[info] changed files (3): tests/test_text.py, text.py, text.py.orig
[FAIL] no leftovers in the diff (3 found)
    tests/test_text.py: test skipped: @unittest.skip("fix later")
    text.py: debug print added: print("DEBUG slugify input:", s)
    text.py.orig: debug print added: print("DEBUG slugify input:", s)
[FAIL] no junk files: text.py.orig
VERDICT: NOT ready — fix the FAIL items first

    The tests "passed" only because the new punctuation test was skipped.

    2. Fixes

    ItemFix
    print("DEBUG slugify input:", s) in text.pyRemoved
    @unittest.skip("fix later") on test_punctuationRemoved, so the test now runs
    text.py.origDeleted

    3. Second check

    $ python3 scripts/verify.py
[PASS] tests: PASS (exit 0) 2 passed in 0.05s
[info] changed files (2): tests/test_text.py, text.py
[PASS] no leftovers in the diff
[PASS] no junk files
VERDICT: ready — re-read the request once more, then finish

    4. Request vs. evidence

    RequirementEvidence
    slugify handles punctuationtest_punctuation runs and passes
    Existing behavior unchangedtest_basic passes
    $ python3 -c 'from text import slugify; print(slugify("Hi, there!"))'
hi-there

    Ready to commit: 2 files changed (text.py, tests/test_text.py), 2 of 2 tests passing, no leftovers.

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    About this skill

    Code quality often suffers from "ready to ship" assumptions that ignore side effects. This skill forces a systematic pre-flight check to ensure the work actually meets the original requirements without leaving behind technical debt. It stops the common habit of reporting success before verifying the entire suite or cleaning up the workspace.

    What it does

    • Automated Scanning Identifies debug prints, breakpoints, and merge conflict markers in the diff.
    • Requirement Mapping Has the agent re-read the request and point each requirement to a file or test.
    • Environment Cleanup Detects junk files like .orig or scratch files that shouldn't be committed.
    • Test Run Runs the detected test command and summarizes failures and asserts.
    • CLI Validation Has the agent run the commands the request mentions and compare the output.

    How it works

    1. Run scripts/verify.py to scan for leftovers and execute the project's test command.
    2. Address every FAIL item in the generated checklist, including skipped tests and junk files.
    3. Map every requirement from the original prompt to a line of code or a specific test case.
    4. Execute any CLI examples provided in the request to ensure the output matches expected results exactly.

    Frameworks & tools

    This tool uses Python 3 standard library scripts for environment-agnostic verification. It integrates with existing test runners like pytest or unittest.

    Why this beats prompting it yourself

    Generic prompts often fail to catch "invisible" issues like .orig files or leftover print() statements. This skill provides a structured Python-backed checklist that ensures every claim of success is backed by empirical evidence rather than a guess.

    Use cases

    • Preventing debug code from reaching production branches.
    • Ensuring refactored code doesn't break existing features in the suite.
    • Verifying CLI tool outputs against strict formatting requirements.
    • Catching .orig, backup and scratch files before a commit.

    Known limitations

    Requires a local Python 3 environment. Test commands must be provided manually if the project uses non-standard test runners.

    Free and open source (Apache-2.0), by the author of rosetta-js, a terminal coding agent for open-weight models.

    How to use

    Skills on Agensi run inside your AI agent. Copy the prompt, paste it into your agent, and it connects to Agensi and installs this skill for you. If a payment is needed, your agent shows it to you first.

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    Listed2 days ago

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