skills/github-issue-workflow/SKILL.md
Use when work should be tracked and executed through GitHub Issues instead of repo-local todo files. Helps agents adopt a repo's existing issue templates, labels, and project conventions when present, or fall back to a portable seed plus execution workflow when they are missing.
npx skillsauth add grepug/skills github-issue-workflowInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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Use GitHub Issues as the source of truth for scope, acceptance criteria, live progress, and completion state.
Prefer the repo's existing GitHub workflow when it exists. Use the bundled defaults in this skill only when the repo has no established issue templates, label conventions, or execution workflow.
When work depends on third-party, platform, or provider setup outside the repo, do not guess the setup contract and do not defer that research until implementation is already underway. Research the official documentation first, then capture the concrete dependency, how a human retrieves or configures it in the real world, and the verification it unlocks in the issue body before treating the issue as ready for execution.
Execution issues should read like completed implementation plans, not placeholders for future discovery. If the work changes dependencies, data models, schemas, architecture, module boundaries, rollout shape, or other reviewer-sensitive surfaces, research and record those details before marking the issue ready. If that detail is still unknown, keep the work as a seed or research issue instead of presenting it as ready-to-build execution work.
AGENTS.md, README.md, CONTRIBUTING.md, and .github/ISSUE_TEMPLATE/Before creating or reshaping an issue workflow, inspect the repo in this order:
.github/ISSUE_TEMPLATE/ for existing issue classes and required fieldsAGENTS.md for the repo's working language, plus any equivalent repo instructions for repo-specific issue or PR workflow rulesIf the repo already has templates, labels, or project rules, follow them. If the repo's templates are older or thinner than the workflow contract in this skill, still use the repo-native template, then immediately backfill any missing required sections in the final issue body or canonical plan comment instead of silently dropping them.
If the repo has no established workflow, use the portable defaults bundled with this skill:
assets/issue-templates/seed.ymlassets/issue-templates/feature.ymlassets/issue-templates/bug.ymlassets/issue-templates/infra.ymlassets/issue-templates/research.ymlassets/issue-templates/config.yml for GitHub issue-template configuration, not as an execution-issue classreferences/label-conventions.mdreferences/label-bootstrap.mdreferences/external-dependency-research.mdreferences/implementation-readiness.mdreferences/issue-pr-closeout.mdassets/canonical-plan-comment.mdassets/pull-request-body.mdscripts/issue_pr_closeout.pyWhen external dependencies are involved, extend discovery with one more required step before implementation: inspect the official provider or platform documentation for the required setup, configuration, limits, and verification prerequisites.
When that additional step applies, use references/external-dependency-research.md to shape what must be researched and how the issue should record it.
When the work changes dependencies, schemas, data models, architecture, or boundaries, also use references/implementation-readiness.md to shape the level of detail required before the issue is treated as ready.
AGENTS.md as the source of truth for the repo's working languageAGENTS.md does not define a working language, default to English1.0 and use itUse two issue classes:
Use a seed issue for early ideas that are worth capturing but are not ready to implement.
Rules:
seed templatetype:seedUse an execution issue once the work is concrete enough to build, investigate, or review against explicit acceptance criteria.
Rules:
feature, bug, infra, or researchtype:* labelpriority:p0 to priority:p3priority:p2; if the issue needs a different priority, replace that label immediately after creationtype:research as a bounded investigation issue, not as implementation authorization for follow-on code or config changesBefore creating a new execution issue, classify the work source first:
type:research or a seed instead of pretending implementation is authorized.Rules:
Do not implement directly from a seed issue.
Promote a seed into a new execution issue only when all of these are true:
Promotion workflow:
Promoted to #<n>For meaningful execution work, keep these aligned:
Rules:
Options considered, Alternatives, Pros / cons, Tradeoff matrix, or Recommendation in issue content or issue commentsNext runs, option menus, or recommended-vs-alternative paths from the user chat into GitHubAGENTS.md, or English when no language is declaredDo not treat implementation as complete just because code exists locally or a branch has been pushed.
Before opening or updating a PR for an execution issue, do all of the following in this order:
Before merging a PR for an execution issue on user request, do all of the following in this order:
Rules:
scripts/issue_pr_closeout.py as the local closeout gate before opening or updating the PRscripts/issue_pr_closeout.py merge-pr so the PR body, linked issue, canonical plan comment, and related closing issues are audited immediately before mergeExecution issues should capture:
Execution issue bodies must describe the selected contract only. Do not embed rejected alternatives, comparison tables, pros / cons lists, or recommendation prose in the issue body. If the work still depends on comparing options, keep it as type:research until the execution contract is fixed.
The reviewer-attention summary should stay concise and highlight only the change surfaces that deserve extra scrutiny from humans or agents, for example:
Use None only when there is genuinely no material review hotspot. Do not hide important review surfaces inside long prose elsewhere in the body.
Current evidence or code anchors should stay compact and concrete. Prefer 1-3 anchors such as:
Do not paste large code blocks into the issue body. The goal is to anchor the issue in the real current state, not to duplicate implementation.
When the work depends on API shape, keep the issue body short and put the selected contract in the canonical plan comment. Prefer compact stubs, protocols, signatures, payload shapes, or pseudo-types for ordinary code APIs. For GraphQL schema work, include the full selected SDL snippet when the type, input, query, mutation, or subscription shape is the review contract; GraphQL SDL is the contract, not incidental implementation detail.
When external setup dependencies exist, the issue must also capture:
Prefer a concrete structure such as:
Rules:
TBD, guess, or similar placeholders when the information can be determined from official docsUse milestones as the default planning bucket for tracked work. Choose them with the deterministic rule above, create 1.0 if the repo has no milestones, and keep PR milestones aligned to the linked issue.
Do not treat a feature, bug, or infra issue as implementation-ready until both of these are true:
When relevant, the canonical plan comment should make the following explicit:
If those details are not yet known, the work is still in research. Do not disguise incomplete discovery as an execution-ready issue.
type:research issues are different. They are execution-tracked investigations with explicit outputs and acceptance criteria, but they are not themselves implementation-ready contracts for code or configuration changes. Promote the result into a feature, bug, or infra issue when the work becomes concrete enough to build.
Even for type:research, keep the issue body deterministic: state the research question, required output, constraints, and acceptance criteria, not the option analysis itself.
Use assets/canonical-plan-comment.md as the default structure when the repo does not already have one.
Rules:
Options considered, Alternatives, or RecommendationWhen the repo uses the bundled defaults, read references/issue-pr-closeout.md before opening the PR and use scripts/issue_pr_closeout.py to audit the issue state and create or update the PR body locally.
When the user asks to merge, run the merge audit through scripts/issue_pr_closeout.py merge-pr before calling gh pr merge.
Use assets/execution-status-comment.md as the default structure when the repo needs a separate issue comment for execution updates between the canonical plan comment and PR closeout.
Rules:
Run options, Option A/B/C, recommendation prose, or any other conversational decision menutype:research issue instead of an execution issue commentUse repo-native labels when present.
If the repo has none, adopt the portable defaults in references/label-conventions.md:
type:seedtype:featuretype:bugtype:infratype:researchpriority:p0priority:p1priority:p2priority:p3Before relying on those defaults, create or sync the labels in the target repo using references/label-bootstrap.md.
Successful use of this skill should leave:
assets/issue-templates/*.yml - portable issue form defaults for repos that have no issue templates yetassets/canonical-plan-comment.md - default implementation-plan comment structureassets/execution-status-comment.md - default deterministic execution-status comment structureassets/pull-request-body.md - default PR closeout body structure derived from the linked issuereferences/label-conventions.md - portable label policy and meaningsreferences/label-bootstrap.md - how to create or sync the required label set in a repo that does not already have itreferences/external-dependency-research.md - how to research and record real-world external setup requirements for issue bodiesreferences/implementation-readiness.md - how to research and record dependency, schema, architecture, and rollout detail before an execution issue is treated as readyreferences/issue-pr-closeout.md - local issue-to-PR closeout workflow and command examplesscripts/issue_pr_closeout.py - local audit and PR creation helper for the bundled closeout workflowdevelopment
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产品无关的 Linear 工作流,用于创建、更新、检查和讨论产品 issue、元数据、状态、范围、确认事项和长期产品文档同步。
data-ai
One-sentence summary of what this skill helps an agent do and when it should be used.