agentic-verify
Check that a Python change is caught by tests: run every mutant of the changed lines and write tests until they catch them. Reports evidence instead of a diff to read.
Install / Use
npx skills add sickn33/agentic-awesome-skills --skill agentic-verifyInstalls into whichever agent you are using.
SKILL.md
Installable skill definition
Quality Score
Category
Development & EngineeringSupported Platforms
Our assessment of agentic-verify
agentic-verify scores 97/100 on our quality scale, 130th of 4,597 Development & Engineering skills we index (top 3%).
Its SKILL.md is 8.3 KB long, well organised into 13 sections with 3 code examples: a thorough specification that gives an agent plenty to work with.
With 47,908 GitHub stars, it is one of the more widely adopted skills in the catalogue.
Maintenance, license and trust
- The repository was last updated today, so agentic-verify is actively maintained.
- It is released under the MIT license, a permissive license that allows use, modification and commercial use with attribution.
- Its trust signals score 100/100, with no cautions. These come from repository metadata, not a code audit — read the skill file before letting an agent act on it.
agentic-verify compared with similar skills
All 4 of these similar skills score higher than agentic-verify; compare them before choosing.
| Skill | Score | Stars | Updated | Format |
|---|---|---|---|---|
| agentic-verify (this skill)by sickn33 | 97 | 47.9k | today | SKILL.md |
| Agent-Reachby Panniantong | 100 | 99.2k | 4d ago | CLAUDE.md |
| taste-skillby Leonxlnx | 100 | 98.9k | today | CLAUDE.md |
| headroomby headroomlabs-ai | 100 | 75.9k | 1d ago | CLAUDE.md |
| ai-job-searchby MadsLorentzen | 100 | 53.9k | today | CLAUDE.md |
Frequently asked questions
- How do I install agentic-verify?
- Run
npx skills add sickn33/agentic-awesome-skills --skill agentic-verify. The install tabs above show the steps for each supported agent. - Which AI agents does agentic-verify work with?
- It is written for Claude Code, as a SKILL.md file. Other agents that read the same format can often use it too.
- Is agentic-verify safe to use?
- It is MIT-licensed and scores 100/100 on trust signals. Skills are instructions an agent will follow, so read the file before installing it and do not approve commands you do not understand.
- Is agentic-verify still maintained?
- The repository was last updated today, so agentic-verify is actively maintained.
Skill content
View source on GitHubname: agentic-verify description: "Check that a Python change is caught by tests: run every mutant of the changed lines and write tests until they catch them. Reports evidence instead of a diff to read." category: testing risk: safe source: community source_repo: timini/agentic-verification source_type: community date_added: "2026-10-16" author: Tim Richardson license: MIT license_source: "https://github.com/timini/agentic-verification/blob/v0.3.0/LICENSE" tags: [testing, pytest, mutation-testing, python, verification] tools: [claude] argument-hint: "[--base REV] [--budget-minutes N] [path]"
Verify a change
Overview
This skill checks that code Claude wrote or changed is actually tested. It defines the check before coding, runs every mutant of the changed lines with a pinned runner, and writes tests until the tests catch them. It reports which mutants were killed and which new tests fail on the old code, so the user can trust the change from evidence. Upstream source: timini/agentic-verification.
When to Use This Skill
- Use after implementing a feature or fix in a Python/pytest project, before saying the work is done.
- Use when the user asks whether a change is tested.
- Use
@agentic-test-auditinstead to review a whole test suite rather than one change.
How It Works
Arguments: $ARGUMENTS. --base is the git revision to compare with: HEAD (default) checks
uncommitted work, a branch such as main checks a whole branch. Other options go to the runner.
The goal is that the user can trust the change from evidence, without reading every line. A change is verified when the tests fail if any part of it is wrong. Passing tests alone do not show that: our study found 71% of the calls that could be deleted unnoticed sat in functions that looked well tested.
Runner
AV='uvx --from git+https://github.com/timini/agentic-verification@v0.3.0#subdirectory=runner agentic-verification'
$AV verify <project-root> --base <rev> [--budget-minutes N]
$AV replay --run <run-dir> --mutant <id> --all
$AV base-check <project-root> --base <rev> [tests...]
Pass the project root (the directory pytest runs in), not a package directory or a file.
base-check runs tests against the production source as it was at --base, in a disposable
copy, and lists the tests that pass now and fail there: those detect the change.
The runner works in a disposable copy and writes only to .test-suite-audit/ in the project.
It needs Python 3.12+ and pytest-cov in the project's environment, plus pytest-randomly for
the order check. Use a Bash timeout of the budget plus 2 minutes. The last stdout line is JSON
with the verdict and report paths.
Rules
- Never weaken, skip or delete an existing test to get a verified verdict, and never edit a test so it matches wrong behaviour. If an existing test fails, the change or the test is wrong: find out which and tell the user.
- A new test must assert behaviour a user of the code depends on: a result, an effect, an error. Do not assert on private helpers or mock the code under change. A test that mocks the thing it checks passes when the feature is broken.
- Only the runner decides that a mutant is killed. Do not call a mutant equivalent yourself; list it for the user with your reasoning.
- Do not retry a failing or flaky test until it passes. Report it; it hides real failures.
- Never stash, revert or edit production files to see a test fail on the old code. Use
base-check, which does it in a copy; an interrupted stash leaves the user's code broken.
Steps
- Define the check first. Before writing code (or, if the code exists, before testing it),
restate the success criteria in one to three lines, and pick the strongest oracle available:
- an end-to-end or public-API test of the user-visible behaviour, if there is a flow to drive;
- a property, for pure logic: round trip, invariant, idempotence, or agreement with a simple reference implementation (Hypothesis, if the project has it or the user agrees to add it);
- a differential test, for a refactor or migration: the old version (
git show <base>:<file>) is the oracle; compare on generated inputs and list intentional differences with a reason; - example tests otherwise, including the edge cases the criteria name.
Write that test and see it fail before the change. If the change already exists, run
base-checkto confirm the test fails on the old code.
- Keep the loop fast. While iterating, run only the tests for the area you are changing. The verify report lists the tests covering the changed lines and how long they take.
- Run verify once the change and its tests are written. Read the verdict:
verified: every changed line runs under a test and every mutant of the changed lines was killed. Go to step 5.gaps: changed lines no test runs, surviving mutants, or a suite that is not green and deterministic. Go to step 4.incomplete: the budget ended first (rerun with a larger--budget-minutes), or no mutant applies to the changed lines, for example a decorated function. Then the mutants give no evidence: rely onbase-checkand say so.no change: nothing under the source packages changed since--base; check the base.
- Close each gap, then rerun verify (step 3). Stop after three rounds and report what is left.
- Surviving mutant: read its patch in
mutants/<id>.patch. It shows a wrong version of your code that the tests accept. Write a test that passes on the real code and fails on that version, then confirm it withreplay --all(killed_now: true). If the mutant changes nothing a caller could observe, leave it and say why. - Uncovered changed line: test it, or remove it if it is dead code.
- New test that catches none of the change's mutants (
change-weak-tests): strengthen its assertions, or explain what it checks instead. - Failing, intermittent or order-dependent test: report it; do not work around it. Tests
that already fail on the base revision are listed as a caveat and do not cause
gaps.
- Surviving mutant: read its patch in
- Optional, for larger changes: review in a fresh context. If you can start a subagent, give it only the success criteria, the diff and the test files, and ask it to write one test that should pass and might not. Run it. A failure is a bug or a missing requirement.
- Report evidence, not a diff. Lead with the verdict, then:
- the success criteria and which tests check each one;
- mutants killed out of mutants run on the changed lines, and changed lines not covered;
- which new tests
base-checkshows failing on the old code; - tests you added, and gaps closed this way;
- what is left: surviving mutants with your reason, and anything not assessed;
- the fast check command from the report, and the path to
report.md. Do not say the change is correct. Say what the tests now catch.
For the meaning of statuses and labels, see reading the report.
Examples
Example 1: Check uncommitted work
AV='uvx --from git+https://github.com/timini/agentic-verification@v0.3.0#subdirectory=runner agentic-verification'
$AV verify . --base HEAD --budget-minutes 10
Example 2: Confirm a new test kills a surviving mutant
$AV replay --run .test-suite-audit/<run-dir> --mutant <id> --all
Limitations
- Python and pytest only. Needs Python 3.12+ and
pytest-cov; the order check needspytest-randomly. - A killed mutant shows the tests notice that change, not that the code is correct.
- Some changes get no mutants (for example a decorated function); the verdict is then
incomplete. - The runner decides kills; possibly equivalent mutants are left for human review.
Security & Safety Notes
- The runner is fetched with
uvxfrom GitHub at tagv0.3.0(commit07608b3b9e4e359bc0b93b3eca94bb78d67e369e). Review it before first use. - It copies the project to a temporary directory and writes only to
.test-suite-audit/in the project. It does not stash, revert or edit production files. - The agent adds test files; it must not weaken, skip or delete existing tests.
Related Skills
@agentic-test-audit- audit a whole pytest suite for gaps, flaky and slow tests, and removal candidates.
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Trust signals
From repository metadata: license, adoption, age and documentation. Not a code audit — see the Safety scan above for what the skill file itself contains.
