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fusion-dependency-review融合依赖性审查

Agent Skill

fusion-dependency-review 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

8,279

周安装

352

GitHub Stars

公开资料未说明

下载量

2,980
CodexClaudeCursorGemini CLI

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-dependency-review(融合依赖性审查)
来源仓库:https://github.com/equinor/fusion-skills
仓库路径:skills/fusion-dependency-review
安装命令:
npx skills add https://github.com/equinor/fusion-skills --skill fusion-dependency-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。

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-dependency-review

简介

用于查找依赖包审查与安全评估相关资料。适用宿主包括 Codex、Claude、Cursor、Gemini CLI,接入前应确认版本、权限和运行环境要求。

  • 适合在引入第三方库时核查许可证与漏洞风险。
  • 可结合 npm 或 NuGet 生态了解常见维护状态指标。
  • 建议在锁定版本前进行人工二次确认与测试验证。
  • fusion-dependency-review 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

SKILL.md

Dependency Review

Structured review workflow for dependency update PRs. Produces consistent research notes that incorporate existing PR discussion, multi-lens analysis, and an actionable verdict with explicit maintainer confirmation before any merge action.

When to use

Use this skill when a dependency PR needs review and you want a consistent, auditable decision process.

Typical triggers:

  • "Review this dependency PR"
  • "Should we merge this dependency update?"
  • "Check this Renovate/Dependabot PR"
  • "Review one of our open dependency PRs"
  • "What changed in this library bump?"
  • "Is this dependency update safe to merge?"
  • A PR title contains dependency update patterns (for example chore(deps):, fix(deps):, bump, update)
  • The user shares a PR URL for a dependency update

When not to use

Do not use this skill for:

  • Feature PRs or application code reviews (use standard code review workflows)
  • Dependency automation or bot configuration
  • Approving/merging without explicit user confirmation
  • Deciding organizational dependency policy

Required inputs

Collect before starting the review:

  • Repository owner and name
  • PR number or URL for the dependency update, or a copied PR summary that includes package name, version change, changed files, and CI status
  • Optional: specific review concerns or areas of focus from the maintainer

If required details are missing, ask concise clarifying questions from references/questions.md.

If the PR target is missing or ambiguous:

  • Ask only the minimal follow-up question needed to identify the target PR.
  • When repository context is known, use GitHub MCP to list likely open dependency PRs and let the user choose instead of guessing.
  • Keep the shortlist concise and decision-friendly: include PR number, title, dependency/package hint, author, and CI state when available.

Auto-extract from the PR when available:

  • Package(s) being updated and version range (from → to)
  • Changelog/release notes URL
  • CI status
  • Changed files and dependency ecosystem
  • Existing top-level PR comments, review comments, and unresolved thread state

Instructions

Preferred advisor orchestration

When the runtime supports skill-local advisors, prefer this execution shape instead of a single long linear pass:

  1. Run agents/target-pr-advisor.md first when the PR target is missing or ambiguous so the review starts from one explicit dependency PR.
  2. Run agents/research-advisor.md to normalize the PR context, existing discussion, source list, and research notes.
  3. Fan out the lens advisors in parallel with the same normalized inputs:
  • agents/security-advisor.md
  • agents/code-quality-advisor.md
  • agents/impact-advisor.md
  1. Chain the combined research and lens outputs into agents/verdict-advisor.md for recommendation, confidence, handoff, and confirmation wording.
  2. Chain into agents/source-control-advisor.md only if the accepted next step requires PR patching, rebase, conflict resolution, or merge-readiness work.

Keep the lens advisors narrow and independent. The parent skill owns the unified review and should preserve disagreement between advisors instead of flattening it early.

Workflow summary

  1. Resolve the target PR with agents/target-pr-advisor.md and the concise prompts in references/questions.md.
  2. Gather context and build the shared evidence packet with agents/research-advisor.md, assets/review-tracker.md, and assets/research-template.md.
  3. Run agents/security-advisor.md, agents/code-quality-advisor.md, and agents/impact-advisor.md in parallel with the same normalized research packet.
  4. Use agents/verdict-advisor.md to produce the recommendation, confidence, follow-up, and explicit maintainer prompt.
  5. Use agents/source-control-advisor.md only after the verdict is accepted and only when branch work is required.
  6. Follow references/instructions.md for the detailed live-PR contract: target selection, checkpoint comments, decision gates, and handoff timing.

Assets

  • assets/research-template.md: research-comment structure for change summary, breaking changes, known issues, and sources
  • assets/verdict-template.md: verdict structure for lens assessments, recommendation, confidence, and follow-up items
  • assets/review-tracker.md: working checklist and tracker for context, validation, lens outcomes, and handoff decisions

References

  • references/instructions.md: detailed execution contract for target selection, live-PR checkpoints, and decision sequencing
  • references/questions.md: concise follow-up questions for choosing the target dependency PR and scoping the review

Advisors

  • agents/target-pr-advisor.md: resolves the exact dependency PR to review or returns a shortlist for user selection
  • agents/research-advisor.md: first pass; builds the shared evidence packet for all later advisors
  • agents/security-advisor.md: parallel lens pass; checks security posture and attack-surface changes
  • agents/code-quality-advisor.md: parallel lens pass; checks upstream stability, regressions, and API drift
  • agents/impact-advisor.md: parallel lens pass; checks repository blast radius, CI, and follow-up work
  • agents/verdict-advisor.md: chained synthesis pass; turns research and lens outputs into one decision
  • agents/source-control-advisor.md: conditional final pass; handles rebase, sync, validation reruns, and push safety when patching the PR

If helper advisors are unavailable, follow the same orchestration inline: research first, lenses next, verdict after that, and source-control last only when mutation is needed.

Expected output

If the PR target is unresolved, return:

  • A concise shortlist of candidate dependency PRs when live PR search is available
  • The minimal follow-up question required to let the user choose the correct PR
  • Explicit status: Awaiting user PR selection

If the PR target is resolved, return a structured review containing:

  • Package name, version change, and update type
  • Existing PR discussion summary (top-level comments, review-thread themes, unresolved concerns)
  • Research summary (changelog highlights, breaking changes, known issues)
  • Security assessment with evidence
  • Code quality assessment with evidence
  • Impact assessment with evidence
  • Verdict: recommendation, rationale, confidence, and follow-up items
  • Handoff recommendation when follow-up work should become a tracked issue
  • Explicit action prompt for the maintainer

Safety & constraints

  • This skill is mutation-capable. Repository-local workflow instructions take precedence over inline guidance when they conflict.

Never:

  • Merge or approve a dependency PR without explicit user confirmation
  • Create a merge commit by merging the base branch into a Dependabot or Renovate PR branch
  • Guess which PR to review when multiple plausible dependency PRs exist
  • Skip the research checkpoint comment or final verdict comment on a live PR
  • Ignore existing reviewer concerns because they are inconvenient or duplicative
  • Claim CI passed or security is clear without checking actual status
  • Expose secrets or tokens in comments or logs
  • Dismiss security concerns for convenience
  • Fabricate changelog entries or version details not found in sources

Always:

  • Ask minimal follow-up questions when the target PR is missing or ambiguous
  • Present evidence for each assessment (link to changelog, CVE, CI status)
  • List candidate dependency PRs for user selection when repository context exists but the PR target does not
  • Fetch existing PR comments and review threads via GitHub MCP before analysis on a live PR
  • Reuse one shared research packet across advisors instead of rediscovering the same facts in each pass — this includes PR metadata, changed files, CI status, and existing discussion
  • Do not re-fetch PR comments or review threads independently in each advisor; pass the pre-fetched data from the research advisor to all lens advisors
  • Prefer parallel lens analysis when the runtime supports it, then chain synthesis after all lens outputs are ready
  • Post the research checkpoint comment to the PR before any branch mutation on a live PR
  • Post the final verdict comment to the PR before any approval or merge on a live PR
  • Make branch-sync or rebase needs explicit before patching the PR
  • Rebase dependency PR branches onto the latest base branch when refresh is required; do not merge the base branch into the PR branch
  • Make follow-up work explicit rather than burying it in review notes
  • Respect the maintainer as the final decision-maker
  • Keep review output in a consistent, repeatable structure

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

按任务关键词查找相关 Skills

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

Codex

34.53%
按下载量换算1,029

Claude

28.53%
按下载量换算850

Cursor

20.71%
按下载量换算617

Gemini CLI

10.53%
按下载量换算314

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

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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