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apollo-issue-review阿波罗问题回顾

Agent Skill

用于围绕 GitHub 仓库、Issue、Pull Request、分支、提交和代码协作流程提供辅助能力。它适合让 Agent 查询项目状态、整理变更、辅助创建或检查协作事项,并把仓库中的信息转成可执行的下一步。使用时需要区分只读查询和写入操作;涉及创建 PR、修改 Issue、推送分支或访问私有仓库时,应确认 token 权限、目标仓库范围和用户授权。

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安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

MIT-0

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:apollo-issue-review(阿波罗问题回顾)
来源仓库:https://github.com/nobodyiam/apollo-issue-review
安装命令:
openclaw skills install apollo-issue-review
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

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复制命令到本机终端执行。该命令会通过 OpenClaw 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

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openclaw skills install apollo-issue-review

简介

apollo-issue-review 协助审查 GitHub Issue 并提出改进建议。

  • 适合开源项目维护者快速判断问题类型与处理优先级。
  • 依据预设流程检查证据充分性,减少无效讨论与重复劳动。
  • 写入操作需 GitHub Token 授权,确保仅在有权限时执行变更。
  • 建议结合项目贡献指南使用,保持社区协作规范一致。

SKILL.md

name
apollo-issue-review
description
Review Apollo ecosystem issues with a classify-first workflow (reproduce for behavior issues, evidence-check for consultative asks) and draft maintainer-grade replies that directly answer user asks, clarify support boundaries, and provide actionable next paths.

Apollo Issue Review

Follow this workflow to review an Apollo issue and produce a concise maintainer response.

Core Principles

  • Classify first: behavior/regression issue vs consultative/support question.
  • For behavior/regression issues: reproduce first, theorize second.
  • For consultative/support questions (for example "is there an official script/doc"): do evidence check first and answer directly; do not force "reproduced/not reproduced" wording.
  • Solve the user ask, do not debate whether the user is right or wrong.
  • If behavior is already reproduced and conclusion is stable, do not ask for extra info.
  • Do not default to "version regression" analysis unless the user explicitly asks for version comparison or it changes the recommendation.
  • Match the issue language: English issue -> English reply, Chinese issue -> Chinese reply (unless the user explicitly asks for bilingual output).
  • Use canonical Apollo module names from repository reality (AGENTS/module layout/root pom.xml), and correct misnamed terms succinctly when needed.
  • If an existing comment already answers the same ask (including bot replies), avoid duplicate long replies; prefer a short addendum that only contributes corrections or missing deltas.
  • Never wrap GitHub @mention handles in backticks/code spans; use plain @handle so notifications are actually triggered.
  • If a community user volunteers to implement ("认领"/"first contribution"), acknowledge and encourage first, then evaluate the proposal with explicit feasibility boundaries and concrete refinement suggestions.
  • For OpenAPI-related asks, explicitly separate Portal web APIs (e.g., /users) and OpenAPI endpoints (e.g., /openapi/v1/*); only claim "OpenAPI supports X" when token-based OpenAPI path is verified.
  • Before concluding "capability not available", cross-check code + docs/scripts + module/dependency hints from pom.xml to avoid false negatives caused by path assumptions.

Input Contract

Collect or derive these fields before review:

  • repo: <owner>/<repo>
  • issue_number: numeric ID
  • issue_context: title/body/comments
  • publish_mode: draft-only (default) or post-after-confirm
  • output_mode: human (default) or pipeline

Optional but recommended:

  • known_labels: existing labels on the issue
  • desired_outcome: whether user wants only triage or triage + implementation handoff

If issue_number or issue_context is missing, ask one short clarification before continuing.

Workflow

  1. Collect issue facts and user ask
  • Read issue body and comments before concluding.
  • Extract: primary ask, symptom, expected behavior, actual behavior, and whether user asks one path or an either-or path.
  • Keep user asks explicit (for example "better parsing API OR raw text API": answer both).
  • Detect whether the thread includes a contribution-claim ask (for example "can I take this issue?") and treat it as a guidance+boundary response, not only a capability yes/no response.
  • Detect main language from issue title/body/recent comments and set reply language before drafting.
  • Decide issue type up front:

- behavior/regression (needs reproducibility check) - consultative/support (needs evidence check)

  • Normalize names to canonical module/service terms used by Apollo repo (e.g., apollo-portal, not invented service names).
  • If GitHub API access is unstable, use:
curl -L -s https://api.github.com/repos/<owner>/<repo>/issues/<id>
curl -L -s https://api.github.com/repos/<owner>/<repo>/issues/<id>/comments
  1. Run the right validation path (mandatory)
  • For behavior/regression issues:

- Build a minimal, local, runnable reproduction for the reported behavior. - Prefer repo-native unit tests or a tiny temporary script over speculation. - Record exact observed output and types, not just interpretation.

  • For consultative/support questions:

- Verify by repository evidence scan (docs/scripts/code paths), not by speculative reproduction framing. - For API availability asks, verify in three places before concluding: 1) actual controller paths, 2) docs/openapi scripts, 3) module/dependency pointers in pom.xml. - Record exact files/paths searched and what exists vs does not exist.

  • Example checks:
rg -n "<api_or_path_related_to_issue>" -S
go test ./... -run <target_test_name>
# or a minimal go run script under /tmp for one-off validation
# consultative evidence scan example:
rg --files | rg -i "<keyword1|keyword2>"
rg -n "<keyword>" docs scripts apollo-* -S
  1. Branch by validation result
  • Behavior/regression path:

- If reproducible: - State clearly that behavior is confirmed. - Identify whether this is supported behavior, usage mismatch, or current feature gap. - Then answer user asks directly (existing API/workaround/unsupported). - If not reproducible: - Ask for minimal missing evidence only: - input sample - exact read/access code - expected vs actual output - Keep this short and concrete.

  • Consultative/support path:

- If capability/script/doc exists: provide exact path/link and usage entry point. - If it does not exist: state "currently not available" directly and give one practical alternative. - If an existing comment already covered the same conclusion: post only a concise delta/correction instead of repeating the full answer.

  1. Draft maintainer reply (focus on action)
  • Start with a one-paragraph summary in the thread language:

- behavior/regression issue: reproduction summary (复现结论 / Reproduction Result) - consultative/support issue: direct conclusion summary (结论 / Conclusion)

  • Then include:

- 当前能力与边界: what is supported today and what is not. - 可行方案: exact API/command/workaround user can run now. - 后续路径: either invite PR with concrete files/tests, or state maintainers may plan it later without overpromising timeline.

  • If the thread includes a contribution-claim proposal, structure the main body as:

1) appreciation and encouragement, 2) feasibility judgment, 3) concrete implementation refinements (what to reuse vs what not to reuse directly).

  • If user ask is either-or, answer both explicitly.
  • If already confirmed feature gap, do not request more logs/steps by default.
  • Keep wording factual and concise.
  • Use canonical module names in final wording; if the issue uses a non-canonical name, correct it briefly without derailing the answer.
  • If there is already a correct prior comment, prefer "reference + minimal supplement" format.
  • If you mention users/bots, keep mentions as plain text (e.g., @dosubot), not code-formatted mention strings.
  • Use localized section labels and wording by issue language (for example: Reproduction Result / Current Support Boundary / Practical Path / Next Step in English threads).
  1. Ask for publish confirmation (mandatory gate)
  • Default behavior: generate draft only; do not post automatically.
  • Present the exact comment body first, then ask for confirmation in the same thread.
  • Use a direct question in the same language as the thread, e.g.:

- Chinese: 是否直接发布到 issue #<id>?回复“发布”或“先不发”。 - English: Post this to issue #<id> now? Reply "post" or "hold".

  • Treat no response or ambiguous response as not approved.
  1. Post the response only after explicit confirmation
  • Allowed confirmation examples: 发布 / 帮我发 / 直接回复上去.
  • If user intent is unclear, ask one short clarification question before any post command.
  • Preferred:
gh api repos/<owner>/<repo>/issues/<id>/comments -f body='<reply>'
  • Fallback when gh transport is unstable:
TOKEN=$(gh auth token)
curl --http1.1 -sS -X POST \
  -H "Authorization: token $TOKEN" \
  -H "Accept: application/vnd.github+json" \
  -d '{"body":"<reply>"}' \
  https://api.github.com/repos/<owner>/<repo>/issues/<id>/comments
  • After posting, return the comment URL as evidence.

Output Contract

Default (output_mode=human) output should be human-friendly:

  1. Issue Summary
  • issue type + confidence
  • validation result (reproduced / not reproduced / evidence result)
  1. Triage Suggestion
  • labels to add
  • missing information (if any)
  • whether it is ready for implementation handoff
  1. Draft Maintainer Reply
  • First sentence must match issue type:

- behavior/regression: reproducibility status (已复现/暂未复现 or Reproduced/Not yet reproduced) - consultative/support: direct availability conclusion

  • Include at least one concrete API/code path/file reference.
  • If unsupported today: include support boundary + practical workaround + next path.
  • If reproducible and conclusion is stable: do not request extra data.
  • If not reproducible: request only minimal reproducible inputs.
  • If prior comment already solved the ask: provide concise delta only.
  • Do not present unverified root cause as fact.
  • Keep language matched to issue language unless user asks otherwise.
  1. Publish Gate
  • If no explicit publish confirmation exists, end with:

- Chinese: 是否直接发布到 issue #<id>?回复“发布”或“先不发”。 - English: Post this to issue #<id> now? Reply "post" or "hold".

If output_mode=pipeline, append one machine-readable block after the human output:

handoff:
  issue_classification:
    type: "功能咨询|问题排查|技术讨论|Bug 反馈|Feature request"
    validation_path: "behavior-regression|consultative-support"
    confidence: "high|medium|low"
  triage_decision:
    labels_to_add: []
    missing_info_fields: []
    ready_for_issue_to_pr: false
    ready_reason: ""
  implementation_handoff:
    goal: ""
    acceptance_criteria: []
    suggested_modules: []
    risk_hints: []

Load References When Needed

  • Use references/diagnostic-playbook.md for scenario-specific diagnostics and command snippets.
  • Use references/reply-templates.md for reusable Chinese maintainer reply skeletons.

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