AI DevKit · Enforce evidence-based completion claims — require fresh command output before reporting success. Use when completing any task, fixing a bug, finishing a phase, running tests, building, deploying, or making any "it works" claim.
npx skills add https://github.com/codeaholicguy/ai-devkit --skill verify
Prove it works before saying it works.
Every completion claim must pass all 5 steps in order:
If any step fails, stop. Fix the issue and restart from step 1.
If no verification command exists (e.g., no test suite), tell the user and ask them how to verify before claiming done.
| Claim | Required Evidence | Not Sufficient |
|---|---|---|
| Tests pass | Test output: 0 failures, exit 0 | Previous run, "should pass now" |
| Build succeeds | Build output: exit 0 | Linter passing, partial build |
| Bug is fixed | Reproduce symptom → now passes | "Changed code, should be fixed" |
| Linter clean | Linter output: 0 errors | Single file check |
| Phase complete | Each criterion verified individually | "Tests pass, so done" |
| Feature works | E2E test or manual walkthrough | Unit tests alone |
For bug fixes, a single pass is not enough:
If step 4 passes, the test is wrong. Rewrite it.
| Rationalization | Why It's Wrong | Do Instead |
|---|---|---|
| "This change is trivial" | Trivial changes break things constantly | Run the check |
| "I ran it earlier" | Code changed since then | Run it again now |
| "The test is flaky" | Flaky ≠ ignorable | Fix the flake first |
| "It compiles, so it works" | Compilation ≠ correctness | Run the tests |
| "The CI will catch it" | CI is a safety net, not a substitute | Verify locally first |
| "The agent said it's done" | Agent claims need verification too | Check diff and run tests |
After a failed verification, store the failure pattern: npx ai-devkit@latest memory store --title "<failure pattern>" --content "<what failed and how to avoid>" --tags "verify,failure-pattern"
If a task name is known and tracing is usable, record task evidence after
the verification report per task. If tracing was not probed, run the real read
probe first. If probe or evidence recording fails, report the failed task command
and continue verification; never block verification on optional task logging.
Comprehensive healthcare AI toolkit for developing, testing, and deploying machine learning models with clinical data. This skill should be used when working with electronic health records (EHR), clinical prediction tasks (mortality, readmission, drug recommendation), medical coding systems (ICD, NDC, ATC), physiological signals (EEG, ECG), healthcare datasets (MIMIC-III/IV, eICU, OMOP), or implementing deep learning models for healthcare applications (RETAIN, SafeDrug, Transformer, GNN).
Comprehensive healthcare AI toolkit for developing, testing, and deploying machine learning models with clinical data. This skill should be used when working with electronic health records (EHR), clinical prediction tasks (mortality, readmission, drug recommendation), medical coding systems (ICD, NDC, ATC), physiological signals (EEG, ECG), healthcare datasets (MIMIC-III/IV, eICU, OMOP), or implementing deep learning models for healthcare applications (RETAIN, SafeDrug, Transformer, GNN).
Expert performance engineer specializing in modern observability, application optimization, and scalable system performance. Masters OpenTelemetry, distributed tracing, load testing, multi-tier caching, Core Web Vitals, and performance monitoring. Handles end-to-end optimization, real user monitoring, and scalability patterns. Use PROACTIVELY for performance optimization, observability, or scalability challenges.
Master AI-powered test automation with modern frameworks, self-healing tests, and comprehensive quality engineering. Build scalable testing strategies with advanced CI/CD integration. Use PROACTIVELY for testing automation or quality assurance.
Internet Court adapter for GenLayer Intelligent Contract supervision. Use to specify agent-performance rubrics, evidence schemas, decision outputs, and ERC-7710 connector expectations, while delegating actual GenLayer contract writing, linting, testing, deployment, and CLI interaction to the official GenLayer skills at https://skills.genlayer.com/.
> Suggests using Microsoft Testing Platform (MTP) hot reload to iterate fixes on failing tests without rebuilding. Use when user says "hot reload tests", "iterate on test fix", "run tests without rebuilding", "speed up test loop", "fix test faster", or needs to set up MTP hot reload to rapidly iterate on test failures. Covers setup (NuGet package, environment variable, launchSettings.json) and the iterative workflow for fixing tests. normally with dotnet test (use run-tests), applying test filters, producing TRX reports, CI/CD pipeline configuration, or Visual Studio Test Explorer hot reload (which is a different feature).
Build production Apache Airflow DAGs with best practices for operators, sensors, testing, and deployment. Use when creating data pipelines, orchestrating workflows, or scheduling batch jobs.
Build production-grade Azure Cosmos DB NoSQL services following clean code, security best practices, and TDD principles.
Take codeaholicguy/verify from the repository into ~/.claude/skills for personal
use, or into .claude/skills inside a project.
The agent identifies a skill by the name field in its header. Two skills with the
same name cannot sit side by side — one of them will be ignored.
The instructions reference npx.
Without those the skill loads but fails at the first command.