New: 97,000+ skills indexed from GitHub repos with 100+ stars · every skill safety-checkedBrowse top skillsTop skills
Esc to closeBrowse all skills
Submit a skillBrowse skills
Submit a skillBrowse skills

Agent skill

Moai Workflow Testing

by modu-ai in modu-ai/moai-adk

A skill your agent uses when writing tests, measuring coverage, or running characterization, performance, or PR-review QA.

Apache-2.0Auto-check passedDevelopment

Install Moai Workflow Testing

skills CLI
$ npx skills add modu-ai/moai-adk --skill moai-workflow-testing -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install modu-ai/moai-adk moai-workflow-testing --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/modu-ai/moai-adk.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.claude/skills/moai-workflow-testing .claude/skills/moai-workflow-testing && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
moai-workflow-testing
GitHub stars
1.2k
Token cost
~2.7k tokens
SKILL.md length
1,024 words
Files
50 (incl. references)
Skills in repo
48
Repo updated
First seen
Licence
Apache-2.0

At a glance

A skill your agent uses when writing tests, measuring coverage, or running characterization, performance, or PR-review QA.

  • Works in 6 steps: Write characterization tests documenting… → Organize tests by domain concepts to… → Use behavior snapshots as regression… → …
  • Measuring coverage
  • SKILL.md covers Quick Reference, Implementation Guide, Advanced Features and Modules, plus 4 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Moai Workflow Testing is an agent skill from modu-ai/moai-adk. Use when writing tests, measuring coverage, or running characterization, performance, or PR-review QA. Comprehensive specialist combining DDD testing, characterization tests, performance profiling, and TRUST 5 quality-assurance validation.

Its SKILL.md is about 2.7k tokens, which your agent loads only when the skill is triggered. The skill folder holds 53 other files, including reference files (for example `modules/INDEX.md`, `modules/advanced-patterns.md` and `modules/ai-debugging.md`). Compatibility notes: Designed for Claude Code

It sits in Development, covering Domain-driven design, QA and bug reports and Pull requests. The repository describes itself as: Agentic development harness for Claude Code — SPEC-driven plan/run/sync, TRUST 5 quality gates, model+effort routing, and Claude×GLM multi-LLM cost control. Single Go binary, 16… The licence is Apache-2.0.

When your agent uses it

  • Measuring coverage
  • Running characterization

Example prompts

  • “/moai-workflow-testing”

Requirements

  • Python 3
  • Docker
  • Compatibility (from SKILL.md): Designed for Claude Code
  • Pre-approved tools (allowed-tools): Read, Write, Edit, Bash(pytest:*), Bash(ruff:*), Bash(npm:*), Bash(npx:*), Bash(node:*), Bash(jest:*), Bash(vitest:*), Bash(go:*), Bash(cargo:*), Bash(mix:*), Bash(uv:*), Bash(bundle:*), Bash(php:*), Bash(phpunit:*), Grep, Glob

Workflow steps

6 steps, taken from the first numbered list in SKILL.md.

  1. Write characterization tests documenting current behavior (not aspirational)
  2. Organize tests by domain concepts to surface domain boundaries
  3. Use behavior snapshots as regression safeguards for complex scenarios
  4. Verify baseline: all characterization tests PASS before any change
  5. Apply refactoring with continuous test execution
  6. Run TRUST 5 validation post-refactor

What it can do on your machine

Read from SKILL.md and the folder at commit 6c55321. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves these tools, so the agent can use them without asking each time:

    • Read
    • Write
    • Edit
    • Bash(pytest:*)
    • Bash(ruff:*)
    • Bash(npm:*)
    • Bash(npx:*)
    • Bash(node:*)
    • Bash(jest:*)
    • Bash(vitest:*)

    …and 9 more on the same allowed-tools line.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md.

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

  • Compatibility

    Designed for Claude Code

    From compatibility in the SKILL.md frontmatter.

Context cost

Moai Workflow Testing loads about 2.7k tokens when it runs, and up to ~16k if it reads all its reference files. Until then it costs about 65 tokens; SKILL.md has 1,024 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~65
When it runs · the whole SKILL.md, loaded when a task matches
~2.7k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~16k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from modu-ai/moai-adk at commit 6c55321, republished under its Apache-2.0 licence (© modu-ai). 1,024 words, ~2,684 tokens.

Download SKILL.mdSave it as .claude/skills/moai-workflow-testing/SKILL.md (or your agent's skills folder). This skill also uses 49 other files; get the full folder from GitHub.
name
moai-workflow-testing
description
Use when writing tests, measuring coverage, or running characterization, performance, or PR-review QA. Comprehensive specialist combining DDD testing, characterization tests, performance profiling, and TRUST 5 quality-assurance validation.
allowed-tools
Read, Write, Edit, Bash(pytest:*), Bash(ruff:*), Bash(npm:*), Bash(npx:*), Bash(node:*), Bash(jest:*), Bash(vitest:*), Bash(go:*), Bash(cargo:*), Bash(mix:*), Bash(uv:*), Bash(bundle:*), Bash(php:*), Bash(phpunit:*), Grep, Glob
compatibility
Designed for Claude Code
when_to_use
Use for comprehensive testing and QA: DDD domain-driven testing, characterization tests, behavior preservation, performance profiling, code and PR review…
license
Apache-2.0
user-invocable
false
metadata.version
2.4.0
metadata.category
workflow
metadata.status
active
metadata.updated
2026-07-10
metadata.modularized
true
metadata.tags
workflow, ddd, testing, debugging, performance, quality, review, pr-review
metadata.author
MoAI-ADK Team

Development Workflow Specialist

Quick Reference

Unified development workflow combining DDD (domain-driven development) testing, debugging guidance, performance optimization, automated code review, and CI/CD quality gates. Emphasizes behavior preservation during refactoring through characterization tests.

Core Capabilities:

  • DDD Testing: Characterization tests (legacy) + specification tests (greenfield) + behavior snapshots
  • AI-Powered Debugging: Error analysis, classification, solution candidates
  • Performance Optimization: Profiling, bottleneck detection, optimization recommendations
  • Automated Code Review: TRUST 5 framework validation
  • PR Code Review: Multi-agent pattern (Haiku eligibility + 5 Sonnet parallel reviewers)
  • Quality Assurance: CI/CD integration with quality gates

Workflow Progression: Debug → Refactor → Optimize → Review → Test → Profile

When to Use:

  • Complete development lifecycle management
  • Quality assurance and CI/CD integration
  • Multi-language and performance-critical projects
  • Technical debt reduction
  • PR code review automation

Implementation Guide

Core Concepts

Five integrated components form the workflow:

  • AI-Powered Debugging: Error classification (syntax/runtime/logic/integration/performance) and solution candidates ranked by likelihood
  • Smart Refactoring: Technical debt analysis with complexity metrics and risk assessment
  • Performance Optimization: CPU/memory/IO/network profiling with optimization strategies
  • DDD Testing Management: Characterization tests (PRESERVE phase) for legacy + specification tests for greenfield + TRUST 5 validation
  • Automated Code Review: TRUST 5 framework with actionable recommendations
TRUST 5 Framework

Quality assessment model with five dimensions:

  • Testability: pure functions, injectable dependencies, modular design
  • Readability: descriptive names, logical structure, documented complexity
  • Understandability: clear business logic, appropriate abstractions, conceptual clarity
  • Security: input validation, secret management, OWASP compliance (injection/XSS/CSRF)
  • Transparency: comprehensive error handling, structured logs, traceable issues

Overall score: weighted average with critical-dimension override (security/testability cannot be masked).

See TRUST 5 detailed dimensions and scoring for full assessment rubric.

DDD Testing Process

Legacy Code (PRESERVE phase):

  1. Write characterization tests documenting current behavior (not aspirational)
  2. Organize tests by domain concepts to surface domain boundaries
  3. Use behavior snapshots as regression safeguards for complex scenarios
  4. Verify baseline: all characterization tests PASS before any change
  5. Apply refactoring with continuous test execution
  6. Run TRUST 5 validation post-refactor

Greenfield Development:

  1. Derive specification tests from domain requirements (each test = business rule)
  2. Organize tests by aggregates, entities, value objects (DDD ubiquitous language)
  3. Specify behavior in business language, not implementation details
  4. Implement to satisfy specifications
  5. Verify with integration tests (domain interactions + invariants)
  6. Apply TRUST 5 validation
Debugging, Refactoring, Performance Workflows

All three follow a 6-step pattern: capture/analyze → classify → identify candidates → apply → verify → document.

See debugging/refactoring/performance step-by-step walkthroughs for detailed process tables.

Code Review Process
  1. Scan codebase for review targets
  2. Apply TRUST 5 framework per file
  3. Identify critical issues
  4. Calculate per-file + aggregate scores
  5. Generate prioritized recommendations
  6. Create summary report with improvement roadmap
PR Code Review (Multi-Agent Pattern)

5-step multi-agent pipeline:

  1. Eligibility Check (Haiku): skip closed/draft/already-reviewed/trivial PRs
  2. Context Gathering: find CLAUDE.md per modified dir + summarize PR
  3. Parallel Review (5 Sonnet agents): CLAUDE.md compliance / obvious bugs / git blame / previous comments / code comment compliance
  4. Confidence Scoring (0-100): 0=false positive, 25=somewhat, 50=moderate, 75=high, 100=certain
  5. Filter & Report: drop issues <80 confidence, post via gh CLI with file/line/commit links

See PR review multi-agent architecture and output format for agent role detail and example output.

Multi-Language Support

Per-language toolchain mappings (Python pytest+ruff+bandit, JS/TS Jest+ESLint+npm audit, Go go test+staticcheck+gosec, Rust cargo test+clippy+gosec equivalents).

See multi-language toolchain reference for per-language testing/lint/security/perf tool inventory.

Advanced Features

Quality Gate Configuration

Three strictness modes:

  • Strict: all TRUST dimensions ≥ threshold, zero critical issues, full coverage
  • Standard: average score ≥ threshold, no critical issues blocking, warnings allowed
  • Lenient: only critical blockers prevent progression

Gate config: per-dimension thresholds, max issues by severity, coverage targets, perf benchmarks.

CI/CD Integration

Four-stage pipeline: Code Quality → Testing → Performance → Security. Each stage terminates pipeline on failure with stage-specific failure report.

See CI/CD integration patterns (GitHub Actions + Docker) for job configuration walkthroughs.

E2E / Browser Testing

Playwright patterns (Page Object Model, cross-browser, visual regression) and documentation-lookup integration. See Playwright best practices.

Show full SKILL.md (414 more words)Show less

Modules

Deep-dive modules for each workflow stage. These describe conceptual workflows (not an importable SDK) — apply each with your project's own toolchain. Start at the modules index, or jump to a stage:

Works Well With

  • moai-domain-backend: Backend testing patterns
  • moai-domain-frontend: Frontend UI testing
  • moai-foundation-core: SPEC system integration
  • moai-domain-database / moai-domain-frontend / moai-domain-backend: Platform-specific testing
  • moai-workflow-project: Project management workflows

Status: Production Ready Maintained by: MoAI-ADK Development Workflow Team Version: 2.5.0 (audit remediation: language-neutrality + module re-linking)

<!-- moai:evolvable-start id="rationalizations" -->

Common Rationalizations

RationalizationReality
"This code is already covered by integration tests"Integration tests catch different bugs than unit tests. The testing pyramid exists for a reason.
"Mocking the database is too hard, I will skip that test"If the test is hard to write because of coupling, the code needs a better abstraction boundary.
"80% coverage is good enough"Coverage targets are floors, not ceilings. The missing 20% often contains the error handling paths.
"These are just utility functions, they do not need tests"Utility functions are the most reused code. A bug in a utility propagates everywhere.
"I ran the tests locally, CI will pass"Environment differences cause CI-only failures. Trust CI output, not local runs.
"Flaky tests are normal, just re-run"Flaky tests hide real failures. Fix the flakiness or quarantine the test explicitly.

Shift Left: Find and fix defects as early as possible. Every test that runs in CI instead of locally adds latency. Every test that could have been a unit test but is an E2E test adds fragility.

Beyonce Rule: If you liked it, you should have put a test on it. Untested behavior is unspecified behavior.

<!-- moai:evolvable-end -->
<!-- moai:evolvable-start id="red-flags" -->

Red Flags

  • Coverage report shows decreased coverage after a feature addition
  • Test file contains t.Skip() or skip without an accompanying issue tracker link
  • Test names are auto-generated (test_1, test_2) instead of behavior-descriptive
  • No test touches the error/failure branch of a new function
  • Test file imports the concrete implementation instead of the interface
<!-- moai:evolvable-end -->
<!-- moai:evolvable-start id="verification" -->

Verification

  • Test suite passes with zero failures (paste command output)
  • Coverage report generated and meets the 85% threshold for changed packages
  • Error paths have dedicated test cases (not just happy path)
  • No flaky tests introduced (run with -count=3 to verify stability)
  • Test isolation confirmed: each test uses its own fixtures or t.TempDir()
  • Race detector passed for concurrent code (go test -race or equivalent)
<!-- moai:evolvable-end -->

© modu-ai, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 49 other files (references) in .claude/skills/moai-workflow-testing of modu-ai/moai-adk.

  • SKILL.md
  • modules/INDEX.md
  • modules/advanced-patterns.md
  • modules/ai-debugging.md
  • modules/automated-code-review.md
  • modules/automated-code-review/review-workflows.md
  • modules/automated-code-review/trust5-framework.md
  • modules/automated-code-review/trust5-framework/relevance-analysis.md
  • modules/automated-code-review/trust5-framework/safety-analysis.md
  • modules/automated-code-review/trust5-framework/scoring-algorithms.md
  • modules/automated-code-review/trust5-framework/timeliness-analysis.md
  • modules/automated-code-review/trust5-framework/truthfulness-analysis.md
  • modules/automated-code-review/trust5-framework/usability-analysis.md
  • modules/code-review/analysis-patterns.md
  • modules/code-review/core-classes.md
  • modules/code-review/tool-integration.md
  • modules/ddd
  • … and 33 more

Open the folder on GitHubat commit 6c55321

Compare with similar skills

Moai Workflow Testing next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Moai Workflow Testing compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Moai Workflow Testing this skillmodu-ai/moai-adk1.2k—~2.7kAutomated safety check: PassApache-2.0
Simple Issue Descriptionevery-app/open-seo23k1 repos~1.2kAutomated safety check: PassMIT
Issue Fixmono/SkiaSharp5.6k—~5.1kAutomated safety check: PassMIT
MAUI PR Performance Analysisdotnet/maui23k—~2.4kAutomated safety check: PassMIT
Community Triageroryeckel/wyoming_openai218—~2.9kAutomated safety check: PassApache-2.0
Handsontable Demo Page Generatorhandsontable/handsontable22k—~1.8kAutomated safety check: PassCustom licence

Similar skills

  • Simple Issue Description

    every-app/open-seo

    Turn a rough bug report, feature request, support note, or pull request into a short, plain-language issue focused on the problem and desired behavior.

    23k GitHub starsUsed in 1 repo~1.2k tokens
    DevelopmentAuto-check passed

  • Issue Fix

    mono/SkiaSharp

    Fix bugs in SkiaSharp C bindings. An agent skill from mono/SkiaSharp.

    5.6k GitHub stars~5.1k tokensUpdated today
    DevelopmentAuto-check passed

  • MAUI PR Performance Analysis

    dotnet/maui

    Official

    Interprets pinned managed benchmark evidence for a dotnet/maui pull request and writes a narrative for the performance review workflow, without running or publishing anything.

    23k GitHub stars~2.4k tokensUpdated today
    DevelopmentAuto-check passed

  • Community Triage

    roryeckel/wyoming_openai

    GitHub issues, pull requests, bug reports, scope questions, and support threads.

    218 GitHub stars~2.9k tokensUpdated 2 days ago
    DevelopmentAuto-check passed

  • Handsontable Demo Page Generator

    handsontable/handsontable

    Builds two throwaway HTML test pages for a Handsontable pull request, one on the released CDN version and one on the local build, to compare behavior side by side.

    22k GitHub stars~1.8k tokensUpdated today
    DevelopmentAuto-check passed

  • Opensource Contributions

    magnus919/hermes-profiles

    Make good open source contributions — check CONTRIBUTING.md first, follow project norms, be a good citizen.

    278 GitHub stars~1.4k tokensUpdated 3 mo ago
    DevelopmentAuto-check passed

More from modu-ai/moai-adk

All 48 skills in this repo

  • SVG Technical Infographic Author

    modu-ai/moai-adk

    Builds hand-editable SVG diagrams from computed layout coordinates, lints the source and renders a 2x PNG, with rules for when mermaid is the better choice.

    1.2k GitHub stars~5.2k tokensUpdated today
    Auto-check: notes

  • MoAI Foundation Core

    modu-ai/moai-adk

    Reference for MoAI-ADK's core development principles: TRUST 5 quality gates, SPEC-first domain-driven workflow, agent delegation and token budgeting.

    1.2k GitHub stars~5k tokensUpdated today
    Auto-check passed

  • MoAI SPEC Workflow

    modu-ai/moai-adk

    Manages SPEC documents for MoAI-ADK development, with GEARS or EARS requirement notation, acceptance criteria and a link into the Plan-Run-Sync workflow.

    1.2k GitHub stars~5.1k tokensUpdated today
    Auto-check passed

  • MoAI TDD Workflow

    modu-ai/moai-adk

    Drives test-first development through the RED, GREEN, REFACTOR cycle, with a config switch that selects between TDD and a DDD workflow for existing code.

    1.2k GitHub stars~3.1k tokensUpdated today
    Auto-check passed

  • MoAI Worktree Management

    modu-ai/moai-adk

    Gives each SPEC its own Git worktree with a registry of active workspaces, base-branch sync and cleanup of merged ones, inside the MoAI-ADK workflow.

    1.2k GitHub stars~3.9k tokensUpdated today
    Auto-check passed

  • CI Watch and Auto-Fix Loop

    modu-ai/moai-adk

    Watches a pull request's CI checks after creation, separates required from auxiliary failures, applies limited safe fixes and escalates anything semantic to you.

    1.2k GitHub stars~2.4k tokensUpdated today
    Auto-check: notes

Categories

Questions about Moai Workflow Testing

What does Moai Workflow Testing do?

A skill your agent uses when writing tests, measuring coverage, or running characterization, performance, or PR-review QA. Moai Workflow Testing is an agent skill from modu-ai/moai-adk. Use when writing tests, measuring coverage, or running characterization, performance, or PR-review QA.

When should I use Moai Workflow Testing?

Moai Workflow Testing fits situations like: measuring coverage; running characterization.

How do I install Moai Workflow Testing in Claude Code?

Run `npx skills add modu-ai/moai-adk --skill moai-workflow-testing -a claude-code`. Or copy the skill folder (.claude/skills/moai-workflow-testing in modu-ai/moai-adk) into .claude/skills/moai-workflow-testing in your project. Claude Code loads it when a task matches its description.

How do I install Moai Workflow Testing in Codex?

Run `npx skills add modu-ai/moai-adk --skill moai-workflow-testing -a codex`. Or copy the skill folder (.claude/skills/moai-workflow-testing in modu-ai/moai-adk) into .agents/skills/moai-workflow-testing in your project. Codex loads it when a task matches its description.

Can I use Moai Workflow Testing in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add modu-ai/moai-adk --skill moai-workflow-testing -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/moai-workflow-testing, .gemini/skills/moai-workflow-testing, .github/skills/moai-workflow-testing and .opencode/skills/moai-workflow-testing in your project.

What does Moai Workflow Testing need to run?

SKILL.md names no scripts, command-line tools or credentials: Moai Workflow Testing is instructions for the agent only. Our summary lists: Python 3; Docker. Its frontmatter pre-approves these tools: Read, Write, Edit, Bash(pytest:*), Bash(ruff:*), Bash(npm:*), Bash(npx:*), Bash(node:*), Bash(jest:*), Bash(vitest:*), Bash(go:*), Bash(cargo:*), Bash(mix:*), Bash(uv:*), Bash(bundle:*), Bash(php:*), Bash(phpunit:*), Grep, Glob. Compatibility (from SKILL.md): Designed for Claude Code.

Does Moai Workflow Testing access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Moai Workflow Testing safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Moai Workflow Testing use?

Moai Workflow Testing is published under the Apache-2.0 licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Moai Workflow Testing use?

About 2.7k tokens (SKILL.md is roughly 11k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 13k tokens, read only when the agent opens those files.

What are the alternatives to Moai Workflow Testing?

Skills that share tags, products or a category with Moai Workflow Testing: Simple Issue Description (every-app/open-seo, 23k stars), Issue Fix (mono/SkiaSharp, 5.6k stars), MAUI PR Performance Analysis (dotnet/maui, 23k stars) and Community Triage (roryeckel/wyoming_openai, 218 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Moai Workflow Testing?

modu-ai (a GitHub organization) maintains it in modu-ai/moai-adk, which has 1,230 GitHub stars. The repository holds 48 skills in this directory. The repository was last updated on October 7, 2026.

Source: modu-ai/moai-adk on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.