git regression hunter

    1

    Find the source of regressions using advanced git forensics, bisect automation, and pickaxe search strategies.

    $5

    Secure checkout via Stripe

    30-day refund guarantee

    Converts to your local currency at checkout

    Security scanned

    Works with the AI tools you already use

    Claude CodeClaude CodeCursorCursorCodex CLICodex CLIMuseMuseDotsDots+22 more

    git regression hunter

    Example session with this skill installed

    The login bug started happening between v2.1.0 and v2.4.5 (about 800 commits). I have a script 'test_auth.sh' that exits 1 on failure. Give me a bisect plan.

    • Read your context and instructions
    • Compiled the git regression hunter

    I have analyzed the range between v2.1.0 and v2.4.5. With approximately 800 commits, a standard binary search will take ~10 steps (log2(800) ≈ 9.64).

    Regression Hunting Plan: Login Bug

    Facts

    • Bad Ref: v2.4.5
    • Good Ref: v2.1.0
    • Test Script: test_auth.sh
    • Commit Distance: ~800 commits

    Analysis

    We will use an automated bisect to minimize manual effort. Since this spans several minor versions, we should verify if any squash-merges exist that might obscure the history. The automated approach is preferred here to avoid human error during the 10 expected iterations.

    Actions

    Run the following commands in your terminal:

    
    # Start the bisect process
    git bisect start v2.4.5 v2.1.0
    
    # Run the automated test script
    git bisect run ./test_auth.sh
    

    If you prefer to run this manually to inspect state at each step, use:

    git bisect start
    git bisect bad v2.4.5
    git bisect good v2.1.0
    
    # Git will now check out the midpoint. Run your test, then:
    # git bisect good OR git bisect bad
    

    Assumptions

    • Assumes test_auth.sh is executable (chmod +x test_auth.sh).
    • Assumes the bug is 100% reproducible and not flaky.
    • Assumes no "broken" (unbuildable) commits exist in this range; if encountered, use git bisect skip.

    Next steps

    1. Run the git bisect run command provided above.
    2. Once git identifies the culprit SHA, paste the output of git show <SHA> and git log -1 --stat <SHA> for intent analysis.
    3. Verify if the culprit is a merge commit, which may require exploring the side-branch history.

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

    What you get

    Create automated git bisect scripts to find bugs in large commit ranges.Trace logic changes through file renames and massive style refactors.Recover deleted functions or files using diff-filters and reflog forensics.Audit suspect commits to find mismatches between PR descriptions and diffs.

    About this skill

    The problem

    Regressions in large codebases are often buried under thousands of commits, squash-merges, and style refactors. Standard git blame often points to a formatter or a rename rather than the commit that actually introduced the logic error.

    What it does

    • Generates optimized git bisect plans with log2 step calculations and automated test scripts.
    • Traces code history through renames and formatting changes using -S and -G pickaxe searches.
    • Identifies original intent by reconstructing the narrative behind suspect commits and PR references.
    • Locates and recovers deleted code using --diff-filter=D and reflog forensics.

    Why this beats prompting it yourself

    General LLMs often suggest destructive git commands or hallucinate flag availability. This skill enforces an evidence-based framework that separates facts from assumptions and prioritizes merge-boundary strategies to resolve regressions in the fewest possible steps.

    Use cases

    • Automating a bisect run for a bug that appeared between two distant releases.
    • Finding the original author of a logic block after a massive codebase reformatting.
    • Recovering a lost feature that was accidentally dropped during a complex merge conflict.

    Known limitations

    Cannot execute git commands directly. Requires users to paste command output for analysis. Assumes a standard git CLI environment.

    How to install

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

    ~30 seconds
    1. 1

      Download the ZIP

      Free skills download straight away. Paid skills unlock right after purchase.

    2. 2

      Unzip into your skills folder

      Every agent reads skills from one folder on your machine. Drop the unzipped folder in there.

    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.

    Skills folder by agent

    Click the path to copy it. Create the folder if it does not exist yet.

    Reviews

    No reviews yet

    Be one of the first to try it. Every listed skill passes our trust checks below.

    Security scanned

    Passed our 8-point scan before listing

    Fresh listing

    Recently published to Agensi

    30-day refund

    Not a fit? Get your money back

    Trust & safety

    Security scanned

    Verified clean 18 days ago

    • Passed all security checks, Safe to install

    Listed18 days ago

    What's inside

    Frequently Asked Questions