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fusion-issue-solving融合问题解决

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

unknown

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:fusion-issue-solving(融合问题解决)
来源仓库:https://github.com/equinor/fusion-skills
仓库路径:skills/fusion-issue-solving
安装命令:
npx skills add https://github.com/equinor/fusion-skills --skill fusion-issue-solving
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。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 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。

skills.shnpx skills
npx skills add https://github.com/equinor/fusion-skills --skill fusion-issue-solving

简介

用于围绕 GitHub 仓库协作流程提供辅助支持。

  • 适合查询项目状态、整理变更或生成协作事项清单。
  • 区分只读查询与写入操作,确保 token 权限匹配需求。
  • 涉及 PR 创建或 Issue 修改时应确认目标仓库授权范围。
  • fusion-issue-solving 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

SKILL.md

Issue Solving Workflow

When to use

Use this skill when the user wants to solve or continue a GitHub issue end-to-end, including short current-repo prompts like solve #123, direct GitHub issue URLs, or requests like lets work on https://github.com/owner/repo/issues/123.

Typical triggers:

Treat GitHub issue URLs as interchangeable with #123 references for verbs like solve, fix, implement, continue, finish, or work on. A direct GitHub issue URL can also serve as the main request payload for this workflow when no competing intent is stated.

When not to use

Do not use this skill when:

  • the request is only issue drafting/authoring,
  • no implementation changes are expected,
  • repository write operations are disallowed.

Required inputs

Collect before execution:

  • issue URL or owner/repo#number,
  • repository and branch/worktree decision,
  • acceptance criteria and out-of-scope constraints,
  • required validation commands for the target repository.

Optional inputs:

  • related issues/PRs,
  • risk areas to prioritize,
  • requested commit/PR granularity.

Instructions

  1. Ask whether to use a dedicated git worktree

- Ask this before any other workflow questions. - If yes, use/create the worktree and continue there.

  1. Confirm issue context and success criteria

- Read the issue body, labels, and linked discussions once, then reuse that context instead of refetching. - Restate the implementable scope and explicitly list out-of-scope items.

  1. Confirm assignee intent for issue closure work

- Check whether the current user is assigned to the primary issue. - If the current user is not assigned, ask whether they want to assign themselves before continuing. - For each sub-issue that will be resolved or closed by this workflow, check assignee status once and reuse the result for closure decisions. - If the current user is not assigned on a sub-issue, ask whether they want to assign themselves before resolving/closing it.

  1. Apply low-token GitHub strategy

- Prefer MCP-backed tools over ad hoc gh api or GraphQL calls when equivalent tools exist. - Avoid duplicate lookups for labels, issue types, and duplicate detection. - Cache per-run context (issue metadata, duplicate matches, issue-type support, label sets, assignee candidates) and reuse it — do not re-fetch data that was already retrieved in this session. - When delegating to fusion-issue-authoring or its subordinate skills, the orchestrator's session-cache rules apply: labels and assignee candidates are fetched once per repository, issue types once per organization. - Use GraphQL fallback only when MCP coverage is unavailable and do not loop retries. - GraphQL mutations cost 5 secondary-limit points each (vs 1 for queries); batch fields into single calls and pause at least 1 second between mutation calls. - Budget awareness: a typical implementation session (read issue + duplicate check + 1–2 mutations + sub-issue links) should stay under ~20 MCP read calls and ~5 mutations. If the running total approaches 30+ calls, pause optional enrichment and proceed with local work. - Respect retry-after and x-ratelimit-reset headers; do not retry before the indicated wait. - If rate limits are hit, stop non-essential operations and continue with local implementation/PR preparation when possible.

  1. Build and track a concrete plan

- Create actionable todos ordered by dependencies. - Keep exactly one step in progress and update status as work completes.

  1. Research before edits

- Inspect relevant files, tests, and adjacent usage. - Prefer root-cause fixes over surface patches.

  1. Implement in small scoped changes

- Keep each change aligned to issue acceptance criteria. - Avoid unrelated refactors and generated release artifacts.

  1. Validate incrementally

- Run targeted checks first, then required project checks. - If checks fail, fix relevant issues and re-run before proceeding.

  1. Prepare PR-ready output

- Summarize what changed and why. - Include validation evidence and known follow-ups. - Draft the PR body in a .tmp/ file with an issue/context-specific name (for example, .tmp/pr-body-issue-123-scope-summary.md), not a shared .tmp/pr-body.md. - Base the draft on .github/pull_request_template.md and keep it updated as implementation evolves. - Ask which base branch to target and propose a likely default (typically main, or the branch the current branch was cut from). - Ask whether the PR should be opened as draft or ready for review. - Ask whether the PR should be assigned to the user and whether related issues should be linked.

  1. Optional GitHub mutation steps
  • Before any GitHub mutation (create/edit/comment/close), ask for explicit user confirmation.
  • If requested, update issue status/comments with objective progress.
  • Prefer MCP tool mutations over ad hoc API calls when equivalent operations exist.
  • If GitHub API rate limits block mutation, report the failure clearly, stop retry loops, and propose a safe retry sequence.
  • If requested, create or update the PR using the repository PR template and the .tmp/ PR body draft file, using the confirmed base branch, draft/ready state, assignee choice, and related issue links.

Expected output

Return a concise delivery report with:

  • implemented scope vs original issue criteria,
  • files changed,
  • validation commands and outcomes,
  • assignment decisions for primary issue and affected sub-issues,
  • API usage strategy used (MCP-first/cache reuse/fallbacks),
  • open risks/blockers,
  • PR body summary (or .tmp/ draft file path when created).

Assets

Safety & constraints

  • This skill is mutation-capable. Repository-local workflow instructions take precedence over inline guidance when they conflict.
  • Never request or expose secrets/credentials.
  • Never run destructive commands without explicit confirmation.
  • Keep changes minimal and scoped to the issue.
  • Do not claim checks passed without running them.
  • Follow repository instructions and contribution rules.

适合场景

01

用户想查找某类 Agent Skill 时

02

需要根据任务场景推荐可安装能力包时

03

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

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能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

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可疑

权限和风险

external-service

该 Skill 可能调用第三方服务、云服务或外部模型 API,使用前需要确认账号、额度、数据发送范围和服务条款。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。来源安全扫描存在 warning/failed 结果,不能写成本站确认安全。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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