TraceMap AI#

TraceMap AI verifies whether requirements, test cases, and code changes truly line up. It converts PRDs, specs, acceptance criteria, test cases, and multi-repo code changes into a requirement-test-code traceability matrix.

It works for product features, backend services, frontend flows, mobile apps, APIs, data pipelines, AI workflows, LLM integrations, agents, RAG systems, and cross-repository releases.

When To Use#

Use this skill when you need to:

• Validate whether a PRD or spec is fully covered by test cases and code changes.
• Review test cases before development, test execution, or release acceptance.
• Analyze multi-repo changes across frontend, backend, services, configuration, prompts, data pipelines, and integrations.
• Build traceability evidence for QA sign-off, release governance, or product acceptance.
• Identify uncovered requirements, weak acceptance criteria, missing evidence, and high-impact defects.

Core Workflow#

1. Collect inputs: PRD, spec, acceptance criteria, test cases, repositories, Git Diff, configuration, prompt/model changes, and release scope.
2. Extract requirements: split product and technical requirements into atomic, testable acceptance points.
3. Map implementation: connect each requirement to code files, services, APIs, configs, prompts, models, and data flows.
4. Map tests: connect each requirement to test cases, fixtures, expected evidence, and execution results.
5. Analyze coverage: classify covered, partially covered, uncovered, redundant, blocked, and untestable requirements.
6. Analyze defects: identify severity, priority, reproduction steps, business impact, and owner suggestions.
7. Generate report: produce a traceability matrix, gap summary, defect list, and release acceptance recommendation.

Reference Guides#

TopicReferenceLoad WhenTraceability validationreferences/traceability-validation-playbook.mdAlways use for coverage categories, mapping dimensions, and matrix template

Required Output#

Produce a Markdown report with:

• Executive summary and release acceptance recommendation.
• Requirement-test-code traceability matrix.
• Coverage summary: covered, partial, uncovered, redundant, blocked.
• Defect list with severity, priority, reproduction steps, owner, and fix recommendation.
• AI workflow validation matrix when applicable.
• Evidence checklist and open questions.

AI Workflow Validation Matrix#

markdown

## AI Workflow Validation Matrix

| Requirement ID | Scenario | AI/Model/Agent Link | Test Case | Code Location | Evidence | Coverage Result | Gap |
| --- | --- | --- | --- | --- | --- | --- | --- |

Quality Bar#

• Do not mark a requirement as covered unless there is clear test and code evidence.
• Distinguish missing implementation from missing tests.
• Every defect must include impact and reproduction path.
• Every AI workflow must include fallback, observability, and safety checks.
• If evidence is incomplete, state what needs to be provided.