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Shiplight Quality

Try Quality on a project (in Claude Code)

From the repository you want to assess, install the quality agent skill for Claude Code:

cd /path/to/your/project
npx skills add ShiplightAI/quality/agent-skills \
  --skill quality --agent claude-code -y

The command above installs the skill only for Claude Code. To install it for several agents, list them after --agent (for example, --agent claude-code cursor); to install it for every supported agent, use --all instead.

Then open Claude Code in that repository and give it this prompt:

/quality start

The agent will inventory the repository, propose a small quality graph for the highest-priority feature, connect the verification methods that already exist, and run an initial assessment when runtime results are available. It will pause when a human needs to confirm feature boundaries, priorities, or quality checks.

After the first pass, inspect the proposed files under .quality/ and answer the agent's review questions. Then continue with the next command it recommends, usually /quality improve or /quality map-feature <feature>.

Want to control the first slice? Include it in the prompt:

/quality start, focus on the highest-risk user-facing workflow first

The skill evaluates existing specifications, tests, workflows, reports, and other evidence; it does not create tests or validate its own proposals. See the quality skill for all commands and workflow details.

Quality Explorer showing the overview for a project: a quality score of 100/100 alongside separate coverage, evidence confidence, and structure confidence scores, the feature and gap counts, and the runtime observation set fetched from a CI workflow run.

What Quality does

Quality connects product intent to independently produced evidence:

requirements (PRDs)
        ↓ intent validation
features (specs)
        ↓
quality checks
        ↓ verification
        ├── reasoning-based verification → analysis results ─┐
        └── empirical verification → empirical observations ┴→ evidence

Requirements define desired outcomes, and people validate that features and checks represent that intent. Verification methods then evaluate whether the implementation or observed behavior satisfies each check. Reasoning-based methods produce analysis results; empirical methods produce observations of behavior. Both can contribute evidence. Quality maps these relationships in .quality/ and keeps missing or weak links visible. Agents can propose maps; people validate intent and decide whether to accept risk.

The engine reports four separate measures:

Measure Question it answers
Quality What do the current observed results report?
Coverage Does every declared check have a mapped verification method?
Evidence confidence Are the mapped methods strong enough for the claim?
Structure confidence Are these the right features, checks, and priorities?

See the terminology guide for the distinction between validation, verification, evidence, and observation, and the concepts guide for the full model and trust boundaries.

Optional: Use spec-project for spec-driven testing

spec-project is an optional companion for turning product intent into accepted feature specs and aligned testing evidence. It produces artifacts; quality independently evaluates them. The skills can be used together or separately.

Install the optional spec-project skill for Claude Code:

npx skills add ShiplightAI/quality/agent-skills \
  --skill spec-project --agent claude-code -y

Then invoke /spec-project init, /spec-project lifecycle, or /spec-project maintenance. The installer creates agent-specific files and skills-lock.json in the target project.

For the quality graph model and independence guarantees, see the concepts guide and how Quality earns your trust.

Development

Requirements: Node.js 24 or newer and pnpm 11.

Install dependencies and run the repository checks:

pnpm install
pnpm test
pnpm typecheck
pnpm build

To inspect another local repository with Quality Explorer, start the application with an absolute project path. For GitHub Actions observations, authenticate with gh auth login first and pass the token; omit the first line for local-only observations:

GITHUB_TOKEN="$(gh auth token)" \
QUALITY_PROJECT_ROOT=/absolute/path/to/project \
  pnpm --filter @shiplightai/quality-explorer dev

The token is passed only to the local process. dev starts the Next.js development server with hot reload; it does not run an assessment or deploy the explorer.

Then open http://127.0.0.1:4173/quality-explorer. The project root is fixed when the process starts and cannot be changed by a browser request.

License

Shiplight Quality is available under the MIT License. See LICENSE.

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