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Agent Skill · 研究检索

context-degradation(环境退化)

context-degradation 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。

context-degradation 是研究检索类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为执行命令;许可证信息还不明确,第三方扫描已通过,按安装量在研究检索类的 73,675 个 Skill 里排第 49,573。

总安装 648周安装 27GitHub Stars 25下载 216核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
unknown

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:context-degradation(环境退化)
来源仓库:https://github.com/oimiragieo/agent-studio
仓库路径:skills/context-degradation
安装命令:
npx skills add https://github.com/oimiragieo/agent-studio --skill context-degradation
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/oimiragieo/agent-studio --skill context-degradation

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

context-degradation 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。适用于上下文退化和环境分析相关的研究检索任务。

通过 GitHub 仓库安装,使用 npx skills add 命令添加技能。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。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。

来源仓库内路径:skills/context-degradation

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 Codex、Claude、Cursor、Gemini CLI;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 npx skills add https://github.com/oimiragieo/agent-studio --skill context-degrad…;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要执行命令,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

context-degradation 怎么安装?

在终端执行 npx skills add https://github.com/oimiragieo/agent-studio --skill context-degradation。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

context-degradation 支持哪些 AI 工具?

公开资料标注支持 Codex、Claude、Cursor、Gemini CLI。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

context-degradation 需要什么权限?

权限级别是执行命令。安装流程涉及命令执行,可能通过 npx skills add https://github.com/oimiragieo/agent-studio --skill context-degradation 联网下载 Skill 或依赖。用户安装前应确认命令来源、仓库内容和执行环境。

context-degradation 是免费的吗?

公开资料没有标注明确许可证,收费和商用限制都无法确认。正式使用前请到来源仓库核对授权说明。

context-degradation 用的人多吗?

公开数据是累计安装 648 次,近一周安装 27 次,下载 216 次,GitHub 25 星。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

context-degradation 安全吗?

第三方扫描结果为通过,但这只覆盖已知的静态检查项,不能替代自己读一遍源码和安装命令。

值得选的地方和要先想清楚的地方

值得选的地方

  • 同时适配 4 种工具,换客户端不用重新找替代品。
  • 第三方扫描已通过,常见的高风险行为没有命中。

先想清楚的地方

  • 需要执行命令,装到常用环境前要先评估影响面。
  • 许可证没有明确标注,能不能商用、能不能再分发都不确定。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 Codex,想直接扩展它能力的人。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。

不太适合

  • 不能接受 Skill 在你机器上执行命令的人。
  • 需要明确授权才能用到公司项目里的场景。
  • 需要厂商级技术支持和 SLA 的生产系统。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
context-degradation

环境退化 · 本页

64825执行命令未明确通过

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

Context Degradation Monitor

Detects context window degradation and prescribes corrective actions before accuracy drops.

Severity Zones

ZoneToken RangeStatusAction
Green< 32KHealthyNormal operation
Yellow32K - 64KCautionBegin selective compression
Orange64K - 100KWarningCompress aggressively; summarize completed phases
Red100K - 140KDangerSpawn fresh subagent for remaining work; pass only essential context
Critical> 140KSevereHalt complex reasoning; compress immediately; do not attempt multi-step tasks

Reference: Models advertise 200K but reliability drops past 32K. "Lost in the middle" effect: middle tokens have 20-40% lower recall past 100K.

Early Warning Indicators

Symptoms that context degradation is affecting output quality (regardless of token count):

  1. Repeated tool calls — Agent re-reads files already read in same session
  2. Contradictory reasoning — Later steps contradict earlier decisions
  3. Missing prior context — Agent "forgets" task scope or constraints stated at session start
  4. Over-explanation — Agent re-explains concepts already established
  5. Stale references — Agent references file paths or task IDs that were resolved earlier

If 2+ indicators are present, treat as one zone higher than token count suggests.

Corrective Routing by Zone

Yellow (32-64K):

  • Invoke Skill({skill: 'context-compressor'}) at the current phase boundary
  • Remove completed phase content from active context
  • Keep: current task spec, key decisions, in-progress file list

Orange (64-100K):

  • Invoke Skill({skill: 'context-compressor'}) — aggressive summarization
  • Write phase summary to .claude/context/tmp/phase-summary-{date}.md
  • Prune: all resolved task details, intermediate research, superseded plans

Red (100-140K):

  • Do NOT continue complex multi-step tasks in current agent
  • Spawn a fresh subagent with only the compressed summary as context
  • Current agent: write handoff doc → call TaskUpdate(completed) with handoff path in metadata

Critical (>140K):

  • Halt immediately
  • Write emergency summary: what was done, what remains, key decisions
  • Route to session-handoff skill
  • Invoke Skill({skill: 'session-handoff'}) before context window forces truncation

Detection Checklist (Run at Each Phase Boundary)

[ ] Token count below 32K? → Green, no action
[ ] Token count 32-64K? → Yellow, begin compression
[ ] Token count 64-100K? → Orange, compress aggressively
[ ] Token count 100K+? → Red/Critical, spawn fresh agent
[ ] 2+ early warning indicators? → Upgrade one severity zone
[ ] Compression reminder file exists? → Invoke context-compressor immediately

Integration

  • Pairs with: context-compressor, context-compressor, session-handoff
  • Called by: planner (at plan start), developer (after each phase), router (before large spawns)
  • Trigger: Check at every phase boundary, not just when problems appear

Iron Laws

  1. ALWAYS check token count at every phase boundary — not just when problems appear or after completing a large task.
  2. NEVER continue complex multi-step tasks past 100K tokens in the same agent context — spawn a fresh subagent with a compressed handoff instead.
  3. ALWAYS treat 2+ early warning indicators as one severity zone higher than the raw token count suggests.
  4. ALWAYS invoke context-compressor at Yellow zone (32–64K) before context bloat becomes severe — prevention is cheaper than recovery.
  5. NEVER claim a task complete without writing a context summary when operating in Red or Critical zone — if it's not written down, the next agent won't know it happened.

Anti-Patterns

Anti-PatternWhy It FailsCorrect Approach
Waiting until output quality degrades before checking contextBy the time quality drops, the context is already in Red/Critical zoneRun detection checklist at every phase boundary proactively
Continuing multi-step tasks past 100K tokens"Lost in the middle" effect causes 20–40% recall drop; decisions made early are forgottenSpawn fresh subagent at 100K with compressed context summary
Ignoring early warning indicators because token count looks fineIndicators are more reliable than raw token counts; a 30K session with 3 indicators is already YellowTreat 2+ indicators as one zone higher regardless of token count
Spawning a subagent without a written handoff documentSubagent starts from scratch, duplicating work or missing constraintsAlways write phase summary to .claude/context/tmp/ before spawning
Compressing context by deleting tool call results without summarizingCompression without summarization loses critical findings from earlier phasesSummarize completed phase outputs before pruning raw tool results

Memory Protocol (MANDATORY)

Before starting: Read .claude/context/memory/learnings.md

After completing:

  • New pattern -> .claude/context/memory/learnings.md
  • Issue found -> .claude/context/memory/issues.md
  • Decision made -> .claude/context/memory/decisions.md
ASSUME INTERRUPTION: If it's not in memory, it didn't happen.

平台分布

Codex

36.64%
按下载量换算79

Claude

27.31%
按下载量换算59

Cursor

19.35%
按下载量换算42

Gemini CLI

8.48%
按下载量换算18

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

执行命令

安装流程涉及命令执行,可能通过 npx skills add https://github.com/oimiragieo/agent-studio --skill context-degradation 联网下载 Skill 或依赖。用户安装前应确认命令来源、仓库内容和执行环境。

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。目前只有一个公开来源,建议同时核对源仓库。

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