Requirements Test Analysis Skill

test-analysis-skill is an Agent Skill for reviewing requirements before implementation or detailed test design. It helps an agent act like a disciplined senior test analyst: inspect requirement quality, assess testability, surface delivery risk, and turn ambiguity into stakeholder questions.

What This Skill Is Responsible For

• Reviewing requirement artifacts such as use cases, user stories, functional specs, and acceptance criteria.
• Producing structured outputs for testability, static review, risk assessment, and gap analysis.
• Using deterministic helper scripts for risk scoring and report export.
• Maintaining a small, explicit project-local memory of recurring requirement anti-patterns.

What This Skill Is Not Responsible For

• Writing executable test cases, automation code, or product code.
• Acting as a shared-memory system across repositories or teams.
• Providing ALM connectors, Jira/Xray API integrations, or document-conversion pipelines.
• Replacing stakeholder decisions when the requirement is incomplete.

Repository Layout

.github/
  workflows/
    ci.yml
agents/
  openai.yaml
evals/
  output-quality-checklist.md
  trigger-queries.json
examples/
  calculator-requirement.md
  calculator-report.md
  library-checkout-requirement.md
  library-checkout-report.md
  pos-checkout-requirement.md
  pos-checkout-report.md
memory/
  requirement-antipatterns.md
references/
  analysis-framework.md
  risk-model.md
scripts/
  calculate_risk.py
  export_report.py
  validate_skill.py
tests/
  test_calculate_risk.py
  test_export_report.py
  test_validate_skill.py
CHANGELOG.md
.gitignore
README.md
SKILL.md

Installation

Place this folder in a location your agent scans for skills, such as:

• ~/.agents/skills/test-analysis-skill
• <project>/.agents/skills/test-analysis-skill

The skill name is test-analysis-skill, so explicit invocations should use $test-analysis-skill.

How To Use It

Example prompts:

• Use $test-analysis-skill to review this checkout use case for testability, static issues, risk, and gaps.
• Use $test-analysis-skill to assess whether these acceptance criteria are testable before we hand them to QA.
• Use $test-analysis-skill to produce a risk-based requirement review for this story and list stakeholder questions.

The skill defaults to four analysis areas unless the user narrows the scope:

• Testability analysis
• Static review
• Risk assessment
• Gaps and stakeholder questions

Memory Model

This repository uses a deliberately scoped memory architecture:

• Runtime memory: working notes for the current analysis only. It is ephemeral.
• Project or skill memory: memory/requirement-antipatterns.md. This is the only bundled persistent memory file.
• Shared memory: intentionally not bundled here. If broader reuse is needed, integrate with an external shared-memory skill or platform capability.

The skill does not auto-promote runtime observations into persistent memory. New anti-patterns should be proposed first and persisted only with explicit approval.

Scripts

• scripts/calculate_risk.py: validates allowed scales, computes inherent and residual risk, and can emit JSON for traceable scoring.
• scripts/export_report.py: converts Markdown reports to styled HTML without requiring third-party Python packages.
• scripts/validate_skill.py: validates the repository layout, skill metadata, examples, eval assets, and agent metadata.

Validation And Tests

Run the validator:

python scripts/validate_skill.py

Run the unit tests:

python -m unittest discover -s tests -v

Generate an HTML report from a Markdown example:

python scripts/export_report.py examples/pos-checkout-report.md --output pos-checkout-report.html

Evaluation Assets

• evals/trigger-queries.json contains should-trigger and should-not-trigger prompts for description tuning.
• evals/output-quality-checklist.md is a lightweight reviewer checklist for forward-testing the skill's outputs.

Optional Integrations And Out Of Scope Items

• Ticket import JSON is supported as an output format, not as a live connector.
• HTML export is bundled; PDF and Word remain downstream conversions.
• Shared memory is an external integration boundary, not an embedded subsystem in this skill.
• A license file is provided (MIT License).

Standards Alignment

This repository is aligned with the Agent Skills progressive-disclosure model, the SKILL.md frontmatter conventions, and the recommended agents/openai.yaml metadata pattern:

• https://agentskills.io/client-implementation/adding-skills-support
• https://agentskills.io/skill-creation/optimizing-descriptions
• https://agentskills.io/skill-creation/evaluating-skills