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prune-context-file修剪上下文文件

Agent Skill

prune-context-file 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

349

周安装

14

GitHub Stars

1

下载量

113
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:prune-context-file(修剪上下文文件)
来源仓库:https://github.com/richardbray/skills
仓库路径:skills/prune-context-file
安装命令:
npx skills add https://github.com/richardbray/skills --skill prune-context-file
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/richardbray/skills --skill prune-context-file

简介

用于查找、检索和筛选相关信息,支持关键词快速定位候选结果。

  • 适用于需要根据任务场景或来源线索在 Codex、Claude 等平台中获取信息时。
  • 可通过 GitHub 仓库路径和 README 进一步核验具体用法和功能范围。
  • 安装方式:通过 npx 从 richardbray/skills 仓库添加技能。
  • 注意:使用前请确认权限范围、维护状态及是否触发联网或命令执行操作。

SKILL.md

Prune Context File

Audit and prune a CLAUDE.md or AGENTS.md file using findings from Gloaguen et al. (2025), the first rigorous study of whether context files improve coding agent performance.

Evidence Base (key findings)

  • LLM-generated context files reduce performance by 0.5–2% and increase cost 20%+. Never suggest auto-generating a context file.
  • Developer-written files marginally help (+4% avg) — except for Claude Code, which showed no benefit from developer-written files either.
  • Codebase overviews don't work. Agents find relevant files at the same speed with or without directory listings and project structure sections.
  • Context files are redundant with existing docs. They only help when a repo has *no other documentation at all*.
  • Tooling instructions are reliably followed. Naming a specific tool (e.g. uv, pytest, a repo CLI) increases its usage 1.6–2.5× vs. not naming it. This is the highest-value content.
  • Instructions cause more testing and exploration, increasing steps and cost. Unnecessary requirements make tasks harder.

Paper: "Evaluating AGENTS.md" — Gloaguen et al., arxiv.org/abs/2602.11988

The Decision Test

For every line or section, ask: *Would the agent write different code, run different commands, or make different assumptions without this?*

  • Yes, always relevant → keep in root
  • Yes, but only when working in a specific subdirectory → move to a nested CLAUDE.md in that directory
  • No / agent can discover it from the codebase → cut it

Classification

Cut (low value)

  • Directory listings and project structure sections
  • Tech stack entries discoverable from package.json / requirements.txt / go.mod (e.g. React, Express, Tailwind, TypeScript)
  • Links to docs files the agent can find itself
  • General coding standards Claude already applies by default (e.g. "use descriptive variable names", "avoid magic numbers")
  • Project overview prose beyond one sentence

Keep in root (high value, always relevant)

  • Specific commands: build, test, migrate, seed, lint — only if non-obvious or not already expressed as package.json / Makefile / config scripts the agent can read directly
  • Non-obvious tooling: libraries or CLIs the agent wouldn't default to (e.g. Better Auth vs. Passport, uv vs. pip)
  • Architectural constraints that would cause wrong assumptions if missing (e.g. non-standard i18n strategy, monorepo layout quirks)
  • Behavioral rules: git workflow, PR requirements, test requirements — things that must be enforced, not inferred
  • Project-specific conventions the agent can't infer from code alone

Move to subdirectory CLAUDE.md (relevant only in specific contexts)

Root CLAUDE.md loads every session regardless of task — content irrelevant to most work has a standing token cost. Subdirectory CLAUDE.md files (e.g. /web/CLAUDE.md, /api/CLAUDE.md) load on-demand only when the agent reads files in that subtree.

Move content here when it only applies to a specific part of the codebase:

  • Frontend-only conventions (component patterns, CSS framework rules, specific UI libraries)
  • Backend-only conventions (ORM patterns, API design rules, service layer constraints)
  • Any subsystem with its own tooling, patterns, or non-obvious constraints

Process

  1. Read the target context file
  2. Classify each section and bullet against the Cut/Keep criteria above
  3. Present a proposed diff: list what you'd remove and why (one line per item)
  4. Wait for approval before rewriting
  5. Write the pruned file, keeping the same structure but leaner

Output Format

When presenting the proposed changes, group by action:

REMOVE
- [Section/item] — [one-line reason]

KEEP
- [Section/item] — [one-line reason]

REWRITE
- [Section/item] → [what it becomes] — [one-line reason]

Then ask for confirmation before applying.

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

37.33%
按下载量换算42

Claude

29.88%
按下载量换算34

Cursor

18.95%
按下载量换算21

Gemini CLI

8.65%
按下载量换算10

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

需要联网

该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

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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