Fix Tests (Grade A) logo

Fix Tests (Grade A)Security-tested development skill for Claude AI. Grade A. Systematic workflow for diagnosing and fixing failing tests. Use when the user reports failing tests or asks to fix test failures.

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Daniel NikulshynReviewed by Daniel Nikulshyn·Updated July 2026

Overview

Fix Tests (Grade A) is a systematic workflow for diagnosing and fixing failing tests. It guides users through a step-by-step process to identify failing tests, analyze each failure, apply common fix patterns, and verify the fixes. This skill is designed for use when a user reports failing tests or asks to fix test failures. It emphasizes fixing one test at a time, verifying each fix, and ensuring that no new test failures are introduced. The workflow includes prerequisites such as having a working test command and type check. It categorizes failures by type (assertion, timeout, mock, type) and provides strategies for common issues like mock problems and assertion errors. The process involves running test suites, checking error messages, and updating tests or code as needed. The goal is to ensure all previously failing tests pass, with no new failures, and coverage remains at or above a specified minimum.

Key features

  • Identify failing tests with error messages
  • Categorize failures by type (assertion, timeout, mock, type)
  • Apply common fix patterns for mock and assertion issues
  • Fix one test at a time with verification
  • Verify full test suite and coverage

Pricing

Model
Free
Category
Skills
Rating
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Use cases

Diagnosing Failing Tests

Use when a user reports failing tests to systematically identify and categorize failures.

Fixing Test Failures

Apply common fix patterns for issues like mock not returning expected values or wrong matchers.

Pros & Cons

Pros

  • Systematic approach to fixing test failures
  • Emphasizes verification to prevent introducing new failures
  • Covers common issues like mock and assertion problems

Cons

  • Relies on accurate test command and type check configuration
  • May not cover all possible test failure scenarios
  • Requires manual effort to analyze and fix each test

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Q&A

Why You Should Use This?

| Audience | Key Benefits | | -------------------- | ------------------------------------------------------------------------------------------------- | | Individual | 30%+ token savings, stop repeating standards, security guardrails, instant scaffolding | | Teams | Consistent AI behavior, day-one onboarding, codified patterns, compounding cost savings | | Organizations | Always-on compliance, same standards across 1,000 projects, central governance, measurable ROI |

Asked by Jana Krejčí · May 28, 2026

What You Can Customize?

| Section | What It Controls | Example | | ------------- | -------------------------- | ---------------------------------------------- | | project | Project identity | Name, description, repo URL | | techStack | Language, framework, tools | TypeScript + Express or Python + FastAPI | | paths | Directory structure | Where handlers, services, and common code live | | domain | Business entities | Order, Product, Customer + lifecycle states | | patterns | Code patterns | 7-step handler flow, error handling strategy | | testing | Quality gates | 90% coverage, test/lint/type-check commands | | database | DB conventions | Soft delete field, timestamp columns, naming | | packages | Internal packages | @your-org scope, registry URL | | conventions | Git and workflow | Branch prefixes, commit format, PR templates |

Asked by Naomi Suzuki · May 1, 2026

What it detects?

| Category | Signals | | ------------------ | ------------------------------------------------------------------------------------------ | | Language | tsconfig.json, go.mod, Cargo.toml, requirements.txt, pom.xml, file extensions | | Framework | Dependencies in package.json / requirements.txt (React, Express, Django, Spring, etc.) | | Database | ORM configs (prisma/, sequelize, typeorm), .sql files, migration folders | | Testing | jest.config., vitest, pytest, cypress/, playwright.config. | | Infrastructure | Dockerfile, terraform/, cdk.json, serverless.yml, cloud SDK deps | | CI/CD | .github/workflows/, .gitlab-ci.yml, Jenkinsfile |

Asked by Vasyl Kovalenko · Apr 12, 2026

What's Inside?

| Layer | Count | What It Does | How It's Triggered | | ------------- | ----- | ------------------------------------------------- | ----------------------------------- | | Rules | 47 | Enforces coding standards on every AI interaction | Automatically — always on | | Agents | 62 | Specialized assistants for complex tasks | On demand — /agent-name | | Skills | 50 | Step-by-step guided workflows with checklists | Contextually — when patterns match | | Commands | 37 | Lightweight, token-efficient quick actions | On demand — /command | | Hooks | 12 | Automation scripts in the AI loop | Event-driven — before/after actions | | Templates | 9 | Scaffolding for handlers, components, tests, etc. | Referenced by skills and agents |

Asked by Wolfgang Krause · Mar 24, 2026

How It Works?

Layer 1 — Pre-Processing: Hooks inject project context and block dangerous commands before your prompt reaches the AI. Layer 2 — Rules Engine: 47 always-on rules enforce token efficiency, security, architecture, code standards, database conventions, and testing thresholds. Layer 3 — Specialized Processing: The right component activates — an agent, skill, or command — based on your prompt. Layer 4 — Post-Processing: Hooks validate output, auto-format, scan for secrets, and verify coverage.

Asked by Xiomara Delgado · Mar 15, 2026

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