Add a two-stage assessment and review process for community PRs

Inizia leggendo la bug extension esistente e il feature-assess workflow per comprendere gli staged artifacts e l’installazione delle estensioni a runtime. Traccia quindi come un community-pr-review workflow proposto potrebbe utilizzare il label gate, il read-only context, gli SHA checks e i constrained outputs. Il lavoro è completato quando i criteri di accettazione sono soddisfatti per assessment, conditional review, stale revisions, permissions e comment limits.

Summary

Add a reusable Spec Kit extension and label-triggered agentic workflow for assessing pull requests submitted by community contributors.

The proposed process has two stages:

assessment → project fit?
               ├─ no or unclear → stop
               └─ yes → review

This follows the staged artifact model used by the bug extension and the runtime extension installation used by the feature-assess workflow, while keeping maintainers responsible for acceptance.

Proposed extension

Add a contribution extension with two commands:

1. speckit.contribution.assess writes .specify/contributions/pr-<number>-<short-head-sha>/assessment.md. It captures PR intent, linked issue or specification, scope, contribution-policy compliance, AI disclosure, architectural fit, risks, and required checks.
2. speckit.contribution.review consumes the assessment and existing CI evidence, then writes review.md with prioritized findings, contributor actions, and a recommendation for maintainers.

Both commands are read-only with respect to repository source. Every artifact records the PR base and head SHAs and refuses to consume stale artifacts after the contributor pushes another revision.

Proposed agentic workflow

Add a community-pr-review workflow triggered when a maintainer applies a community-review label to an open PR.

The workflow posts at most two top-level comments:

1. Community contribution assessment — Stage 1/2: summarizes fit, scope, policy compliance, risks, and the assessed head SHA.
2. Community contribution review — Stage 2/2: summarizes findings, CI evidence, contributor actions, and the maintainer recommendation.

If assessment returns out-of-scope, invalid, or needs-clarification, the workflow posts only the assessment comment, applies the corresponding outcome label, and stops. Review runs only when assessment determines that the contribution fits the project and has enough information to evaluate.

Each comment should identify its stage and PR head SHA. Configure safe outputs with add-comment: max: 2 and constrained outcome labels.

Guardrails

• Use a human-applied label as the execution gate.
• Never modify or push to the contributor's branch.
• Never formally approve, request changes, merge, or resolve review threads.
• Use the pull_request security context, not pull_request_target.
• Keep repository and pull-request permissions read-only and expose no secrets.
• Treat PR descriptions, comments, diffs, and changed files as untrusted data rather than instructions.
• Consume existing CI results instead of executing contributor-controlled commands in the agentic workflow.
• Record the head SHA and stop when assessment or CI evidence is stale.

Suggested outcomes

Assessment can conclude:

• fits-project — continue to review.
• needs-clarification — request information and stop.
• out-of-scope — explain why and stop.
• invalid — explain why and stop.

Review can conclude:

• ready-for-maintainer-review.
• needs-contributor-action.
• blocked.

These are recommendations only; a maintainer remains the final decision-maker.

Acceptance criteria

• A maintainer can trigger the process against a community PR by applying one label.
• Assessment always posts first and clearly identifies itself as Stage 1/2.
• Review runs and posts Stage 2/2 only when assessment returns fits-project.
• At most two comments are created per run.
• Both outputs identify the exact PR head SHA they evaluated.
• Source files and the contributor's branch are never modified.
• Re-running after a new push cannot reuse stale assessment artifacts.

AI disclosure

This issue was drafted and filed on behalf of @mnriem by GitHub Copilot (model: GPT-5.6 Sol).