将大型调研或生成任务分配给多个AI模型,完成计划评审、并行执行、成果验证与整合,并记录各负责角色的进度和重试情况。
- 并行调研多个竞争对手
- 分担大型内容生成任务
- 让顾问评审计划或草稿
将 Git 差异与修改目的对照,找出可能无关的文件、新增依赖等范围扩张信号,给出保留、拆分或说明必要性的判断,并整理拆分方案。
Analyzes git diffs against a stated intent to detect scope creep, unrelated files, broad pull requests, changes that grew beyond a fix, dependency additions, public API renames, config or CI edits, oversized hunks, and formatting-only files. Use when the user asks whether a change grew beyond the fix, a PR is too broad, or what unrelated stuff they touched, and wants keep, split, or justify guidance. Operates locally and offline.
scope-creep-detector 将 Git 差异与修改目的对照,检查工作范围是否扩大。它会找出与目的关联较弱的文件、新增依赖、公共 API 重命名、配置或 CI 编辑、过大的修改区块,以及仅涉及格式调整的文件。根据这些信号,整理出保留、拆成独立修改或说明必要性的判断。
适合原本的小修复涉及了许多文件,或提交拉取请求前需要核对范围时使用。可以检查工作区修改、已暂存修改、相对于基准分支的差异,也可以分析已保存的差异文件。若多种修改混在一起,可获得标明相关文件或修改区块的拆分方案。
使用 Python 3 脚本在本地运行,不进行网络通信,也不修改工作区。检测会参考文件名与目的描述中的词语是否匹配,因此不能仅凭结果断定某项修改无关。不评估修改的正确性、安全性或测试质量。
本介绍由 AI(OpenAI Codex)根据公开的 SKILL.md 撰写。准确的规格请查看下方原文。
AI 仅根据 SKILL.md 的内容,从 4 个方面进行了评估。星标数和热度不计入评估。
总分按每项 A=25 分、B=15 分、C=5 分相加。 由 AI(OpenAI Codex)于 2026年10月20日 评估。仅供参考,安装前请同时查看原文。
安装前可以查看交给 AI 代理的指令内容。
A one-line fix should not require a reviewer to reverse-engineer fourteen files across three subsystems. This skill compares a git diff with its stated intent, surfaces scope signals, and turns them into keep, split, or justify decisions.
Everything runs locally. The script makes no network calls and does not change the working tree, index, commits, or branches.
Use the user's one-line intent when available. Keep it concrete, such as
fix null dereference in parser or add retry limit to webhook delivery.
If no intent was given, the script falls back to the current branch name. If that name is generic, detached, or unrelated to the work, ask for one line of intent before treating relatedness as meaningful.
Run from this skill directory and point --repo at the target repository.
Working tree diff:
python3 scripts/scope_creep.py --repo /path/to/repo \
--intent "fix null dereference in parser" --json
Staged diff:
python3 scripts/scope_creep.py --repo /path/to/repo --staged \
--intent "fix null dereference in parser" --json
Branch diff against a merge base:
python3 scripts/scope_creep.py --repo /path/to/repo --base main \
--intent "fix null dereference in parser" --json
Saved diff or stdin:
python3 scripts/scope_creep.py --diff change.diff --intent "parser fix" --json
git diff --staged | python3 scripts/scope_creep.py --diff - \
--intent "parser fix" --json
Use --hunk-threshold only when the repository has a documented reason to
change the default churn threshold. Do not tune the threshold merely to make a
warning disappear.
Read references/scope-signals.md before making a recommendation. Treat the classifier as triage evidence, not proof of authorial intent.
in_scope: file paths with at least one intent/path keyword overlaplikely_creep: paths without overlap, with the reason and detected signalsnew_deps: dependencies introduced in supported manifest formatsapi_renames: nearby removed and added public function or class declarationsconfig_edits: CI, container, build, YAML, and TOML changesstats: churn, subsystem counts, oversized hunks, and formatting-only filesEmpty arrays are evidence too. Say that no signal was detected, not that the diff is guaranteed to be in scope.
Give every item in likely_creep one disposition:
Prefer split when evidence is ambiguous. Never claim that a zero overlap score proves a file is unrelated. Path vocabulary is a cheap, deterministic proxy.
Use this compact structure:
Name file paths and hunk headers. For an oversized mixed hunk, explain that the script cannot split it automatically and describe the smallest coherent edit. Ask before applying any split, revert, staging, or commit operation.
scripts/scope_creep.py: deterministic unified-diff parser and classifierreferences/scope-signals.md: signal definitions, thresholds, and limits还没有评价。欢迎分享你的使用感受。
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将大型调研或生成任务分配给多个AI模型,完成计划评审、并行执行、成果验证与整合,并记录各负责角色的进度和重试情况。
指导开发可在ChatGPT内操作的应用,涵盖功能规划、React组件及状态共享的实现。该技能已弃用,并指引用户转向后续技能。
通过本地Git历史调查代码的引入背景与修改意图,追溯最初提交及反复同时修改的文件,整理改动前需要检查的事项。
检查Python和JavaScript依赖文件中的版本约束缺失、重复条目、固定版本冲突及过时兼容包,用易懂的语言说明影响并提出便于核对的修改建议。
从目标读者的角度试读发布前的文稿,检查是否愿意打开、在哪里失去兴趣,以及读后记住什么。它报告模拟读者的反应,不改写文章。
使用mcp-use设计和实现MCP服务器,让AI调用外部操作与数据。指南涵盖认证、交互界面、错误处理及部署,并引导查阅各功能的配套资料。