Add a two-stage assessment and review process for community PRs
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Ninguém assumiu esta issue ainda.
Avaliação
- Dificuldade
- 5/5
- Tempo estimado
- Mais de uma semana
- Facilidade para iniciantes
- 48/100
Direção de pesquisa
Comece lendo a bug extension existente e o feature-assess workflow para entender os staged artifacts e a instalação de extensões em tempo de execução. Em seguida, acompanhe como um community-pr-review workflow proposto poderia usar o label gate, o read-only context, as SHA checks e os constrained outputs. Está concluído quando os critérios de aceitação forem atendidos para assessment, conditional review, stale revisions, permissions e comment limits.
Escrita pelo modelo de indexação a partir do texto da issue.
Descrição
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:
speckit.contribution.assesswrites.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.speckit.contribution.reviewconsumes the assessment and existing CI evidence, then writesreview.mdwith 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:
- Community contribution assessment — Stage 1/2: summarizes fit, scope, policy compliance, risks, and the assessed head SHA.
- 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_requestsecurity context, notpull_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).
- Linguagem predominante
- Python
- Estrelas
- 140k
- Forks
- 12.6k
- Merge médio
- 2d 11h
- PRs com merge (30d)
- 186
Preparar o ambiente
Inicia o contêiner de desenvolvimento do projeto no navegador, com a sua própria conta do GitHub.
- Sem Dockerfile nem arquivo Docker Compose
- Tem um modelo de pull request
- Ler o guia de contribuição
Primeiros passos
- Leia a issue inteira e depois o guia de contribuição do projeto.
- Comente na issue dizendo que vai assumir — evita que duas pessoas façam o mesmo trabalho.
- Faça um fork do repositório e trabalhe em uma branch.
- Abra um pull request que referencie o número da issue.
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