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post-implementation-review实施后审查

Agent Skill

post-implementation-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

699

周安装

28

GitHub Stars

公开资料未说明

下载量

226
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:post-implementation-review(实施后审查)
来源仓库:https://github.com/sjunepark/custom-skills
仓库路径:skills/post-implementation-review
安装命令:
npx skills add https://github.com/sjunepark/custom-skills --skill post-implementation-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/sjunepark/custom-skills --skill post-implementation-review

简介

用于查找、检索和筛选相关信息以支持实施后评估。

  • 适合根据关键词或任务场景快速定位候选结果。
  • 可辅助收集反馈、分析问题根源或推荐改进措施。
  • 安装前建议核对权限范围和维护状态。post-implementation-review 属于研究检索类 Skill,可作为该场景下的辅助能力补充。
  • 注意是否会触发联网、命令执行或文件读写操作。

SKILL.md

Post-Implementation Review

Use this skill manually. Do not invoke it unless the user explicitly asks for a post-implementation review or explicitly asks whether implemented code should now be refactored.

Review the code after the implementation exists. Focus on issues that were hard to see upfront and only became obvious once the change touched real interfaces, control flow, state, tests, or module boundaries.

This skill is for improvement-oriented design review after the real code exists. Prioritize actual design flaws, weak boundaries, ownership confusion, abstraction leaks, overengineered code or structure, and organization problems that will matter as the codebase grows. Prefer recommendations that materially improve a seam, file, module, or end-to-end concern once the code is real. Do not let change size alone veto a worthwhile recommendation, but also do not fill the review with tiny local tidy-ups that barely change maintenance cost or design clarity. If tradeoffs, uncertainty, or hidden constraints matter, surface them clearly.

It is still acceptable for the review to conclude that the implementation is fine. Do not invent a flaw just to produce feedback. If the code does not reveal a meaningful improvement, say plainly that there is nothing worth changing right now.

Workflow

  1. Anchor the review in the actual change.
  • Read the changed files, nearby interfaces, and affected tests or docs.
  • Distinguish between:

- pre-existing design debt - issues introduced by the change - issues the change merely made easier to see

  1. Look for post-implementation signals.
  • Repeated branching, mapping, or glue code that suggests the abstraction boundary is off.
  • A module now knows details it should not need to know.
  • The change forced edits across too many files for one concept.
  • Responsibilities are blurred enough that naming, ownership, or call flow became awkward.
  • Data is being reshaped repeatedly between layers.
  • Tests became hard to set up because dependencies or ownership are misplaced.
  • The implementation needed workarounds that will probably repeat.
  • The implementation introduced speculative or overbuilt structure that current behavior barely uses: extra fields, hooks, wrappers, options, strategy objects, generic layers, or config surfaces.
  • One concern is now scattered across files or modules in a way that weakens discoverability.
  • The feature now feels too flat or mixed: readers must scan unrelated files or responsibilities to follow one concern.
  • The code technically works, but the implementation revealed a real boundary, ownership, organization, or overengineering weakness that will keep taxing future changes.
  1. Prefer credible improvements, not only obvious failures.
  • Do not recommend a refactor just because another design looks cleaner in theory.
  • Do not treat unfamiliar code as broken code.
  • Assume there may be constraints you cannot yet see unless the code gives clear contrary evidence.
  • Recommend a refactor when the implementation shows a solid improvement path for readability, boundaries, extension, or correctness, even if the current code still works.
  • Bias toward improvements that change the design meaningfully at the seam, file, module, or feature-flow level.
  • Prioritize actual design and organization weaknesses over local readability or polish wins.
  • Do not surface tiny helper extractions, one-off log polish, or single-branch cleanup unless they clearly point to a broader pattern, close an important boundary gap, or fix a problem likely to recur.
  • Do not reject a worthwhile recommendation just because it touches many files. Discuss that cost when it matters, but size alone is not a veto.
  1. Separate evidence, recommendation, and decision level.
  • First state what the implementation revealed.
  • Then state whether there is a likely recommended path.
  • Classify every finding or recommendation into one of two buckets:

- Bucket I — Straightforward / recommended: likely has a clear answer or strongly recommended fix path; present briefly for awareness. - Bucket II — Worth discussing: real tradeoffs, multiple plausible directions, unclear constraints, or technical decisions.

  • Use Bucket II for the items that deserve the user's attention.

Review Standard

Treat these as strong signals for a refactor recommendation:

  • The same workaround or translation layer now appears in multiple places.
  • A single change required cross-cutting edits that are likely to recur.
  • One abstraction claims to hide complexity but instead leaks it to callers.
  • Ownership of data, side effects, or orchestration is ambiguous enough to create likely bugs.
  • The new code had to special-case around an existing interface in a way that will spread.
  • The implementation added wrappers, options, strategy points, generic types, or configuration that current behavior does not really need.
  • One concern is split across files or layers in a way that makes the code harder to navigate or evolve.
  • A module, file, or directory now mixes responsibilities that should probably be separated.
  • The current shape is workable, but a concrete refactor would noticeably reduce mental overhead or repeated explanation for future changes.

Treat these as weak signals that often do not justify action on their own:

  • The code feels a bit inelegant but is still locally understandable.
  • A helper or abstraction is slightly misnamed but still usable.
  • There is some duplication, but it is small and isolated.
  • The current design is awkward only for one edge case with no sign of repetition.
  • A tiny helper extraction would save a few lines but would not clarify ownership, boundaries, or future change points.
  • A one-off logging, annotation, or convenience cleanup would make the code a bit nicer but would not materially change debugging leverage or design clarity.
  • The issue is purely inside one function and does not suggest a broader responsibility or interface problem.

If the evidence is weak, say so. If the only available feedback is minor polish, prefer No meaningful improvement identified over padding the review. A clean review is still valid.

Output

Use this structure when reporting:

Bucket I — Straightforward / Recommended

  • Put findings or recommendations here when there is a likely answer or a strongly recommended path that probably does not need much user review.
  • Keep these concise.
  • Use Bucket I for materially worthwhile fixes, not for every plausible tidy-up.
  • Number the items in this bucket (1., 2., 3.). Do not use unordered bullets for the primary items.
  • For each numbered item, include:

- what the implementation revealed - why it became visible after implementation - the recommended fix in short form - the main cost or tradeoff only if it matters

  • Support with a short embedded snippet when existing code is central to the point.

Bucket II — Worth Discussing

  • Put findings or recommendations here when they involve real tradeoffs, technical decisions, hidden constraints, or multiple plausible directions.
  • Number the items in this bucket (1., 2., 3.). Do not use unordered bullets for the primary items.
  • For each numbered item, include:

- what the implementation revealed - why it became visible after implementation - the main options or decision points - the tradeoffs, risks, or uncertainty

  • Support with a short embedded snippet when existing code is central to the point.

Keep As-Is

  • Call out odd-looking choices that should probably remain unchanged for now.
  • If this section has multiple items, number them too.
  • Explain what evidence is missing for a change recommendation.

Verdict

  • End with one of:

- No meaningful improvement identified - Recommended targeted refactors, mostly straightforward - Recommended changes include technical decisions - Broader redesign may be warranted after clarifying constraints

  • If Bucket I or Bucket II is empty, say so explicitly instead of implying hidden findings.

Snippet Rules

  • When citing existing code, prefer embedded snippets over bare file paths and line numbers.
  • Put the source file path on the first line of each snippet as a comment.
  • Match the comment style to the language when practical, for example // src/service.ts or # backend/jobs/sync.py.
  • Keep snippets tight and evidence-focused: signatures, branches, translations, ownership boundaries, and repeated glue code are usually enough.
  • Use multiple small snippets instead of one large excerpt when separate points need separate evidence.
  • Use file and line references only when a snippet would add noise or the exact location itself is the point.

Communication Rules

  • Be direct and specific.
  • Prefer file-level, seam-level, module-level, or feature-flow observations over vague architectural commentary.
  • Do not force the user back into the editor just to follow the review.
  • Default toward surfacing actual design, abstraction, ownership, organization, structure, and overengineering weaknesses that materially affect maintainability or future change paths.
  • Check not only for missing structure but also for structure that is heavier than the current behavior justifies, and call out where it can be reduced.
  • Avoid padding the review with minor pre-fixes: tiny helper extraction, one-off naming polish, isolated local dedupe, or small logging niceties are usually not worth calling out unless they indicate a broader problem.
  • Do not treat code churn alone as a reason to avoid recommending a refactor.
  • Surface real tradeoffs when they exist.
  • Keep Bucket I concise so the user can scan past the obvious items quickly.
  • Put the user's attention on Bucket II.
  • Within each populated bucket, use numbered primary items so the hierarchy stays visually clear.
  • If there are no meaningful design flaws or worthwhile improvements, say so explicitly.
  • If a concern is plausible but not yet well supported, put it in Bucket II or Keep As-Is rather than overstating confidence.
  • Do not manufacture findings to make the review feel useful.

Structure and Complexity Concerns

When a post-implementation review also raises questions about speculative structure, unnecessary complexity, over-engineering, flat organization, or mixed responsibilities, review those concerns inline here instead of delegating elsewhere.

Check structure in both directions:

  • Over-structure: extra fields, config keys, DTO properties, wrappers, extension points, strategy objects, mode switches, or mapping layers that current behavior does not meaningfully use.
  • Under-structure: flat directories mixing unrelated concerns, modules handling multiple capabilities at once, or related files scattered in ways that make one feature harder to follow.

Use the same posture here:

  • Do not remove structure that already improves naming, local reasoning, ownership boundaries, or filesystem-level comprehension.
  • Do not add nesting just because a directory has many files.
  • Treat readability-oriented helpers, small composed objects, and clear subdirectories as legitimate value even when they are single-use.
  • Prioritize structural findings that expose weak ownership, mixed responsibilities, scattered concerns, overbuilt abstractions, or directories/modules that no longer help readers predict where code lives.
  • Recommend simplification or reorganization when the current shape adds recurring maintenance cost, obscures the real flow, or when a credible cleanup would materially improve ownership clarity.
  • Do not reject a structural recommendation just because the reorganization would touch many files; surface the cost and tradeoff instead.

Treat these as strong signals:

  • A new field, option, or hook exists mostly for hypothetical future cases.
  • A wrapper, abstraction layer, strategy object, or config surface adds flexibility that current behavior does not use.
  • A helper or abstraction adds another jump without improving naming, boundaries, invariants, or reuse.
  • Callers still need to know internal details the abstraction claimed to hide.
  • One concept now requires repeated mapping or translation just to preserve genericity.
  • The filesystem or module layout no longer helps a reader predict where a concern lives.
  • A small or medium reorganization would make one concern much easier to follow end to end.

Treat these as weak signals:

  • The code is a bit inelegant but still locally understandable.
  • A helper is slightly misnamed but still usable.
  • There is some duplication, but it is small and isolated.
  • A flat directory is still small and each file name clearly signals its purpose.
  • A tiny extraction or move would polish one function but would not improve the surrounding ownership or structure.

When these concerns matter, keep using the same report structure:

  • Put straightforward structural fixes in Bucket I — Straightforward / Recommended.
  • Put structural items with meaningful tradeoffs or unclear boundaries in Bucket II — Worth Discussing.
  • Use Keep As-Is for structure that pays for itself now.
  • Skip micro-structure polish unless it reflects a broader boundary problem.
  • If the implementation is structurally fine, say so plainly.

Example Triggers

  • "Now that this feature is implemented, do you see any design flaws we missed?"
  • "Did this change reveal any abstraction problems?"
  • "Should we refactor this now, or leave it alone?"
  • "Review this implementation and tell me if the current design will age poorly."
  • "Now that this is implemented, is the structure earning its keep or did we overbuild it?"
  • "This feature works, but did the implementation reveal that the module layout is too flat or mixed?"

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

37.83%
按下载量换算85

Claude

27.1%
按下载量换算61

Cursor

18.32%
按下载量换算41

Gemini CLI

8.94%
按下载量换算20

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

只读

该 Skill 主要提供规则、说明或参考内容,本身偏只读;真正读写文件、联网或执行命令仍取决于宿主 Agent 的任务。

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。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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