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Agent Skill · 研究检索

adaptive-subagents(自适应子 Agent)

adaptive-subagents 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。

adaptive-subagents 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,权限为需要联网;许可证信息还不明确,第三方扫描有提醒项,按安装量在研究检索类的 73,675 个 Skill 里排第 59,696。

总安装 380周安装 16GitHub Stars 公开资料未说明下载 133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:adaptive-subagents(自适应子 Agent)
来源仓库:https://github.com/maleko91/claude-code-adaptive-subagents
仓库路径:skills/adaptive-subagents
安装命令:
npx skills add https://github.com/maleko91/claude-code-adaptive-subagents --skill adaptive-subagents
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/maleko91/claude-code-adaptive-subagents --skill adaptive-subagents

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。

adaptive-subagents 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。适用于需要分解任务并委托给合适模型执行的复杂研究场景,支持机械性查找与逻辑性理解两类操作的分级处理。

通过 npx skills add 命令从 GitHub 仓库安装,调用时需先分解子任务再分配执行,避免直接操作文件。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/adaptive-subagents

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/maleko91/claude-code-adaptive-subagents --skil…;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

    它需要需要联网,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

adaptive-subagents 怎么安装?

在终端执行 npx skills add https://github.com/maleko91/claude-code-adaptive-subagents --skill adaptive…。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

adaptive-subagents 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。

adaptive-subagents 需要什么权限?

权限级别是需要联网。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。

adaptive-subagents 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。

adaptive-subagents 用的人多吗?

公开数据是累计安装 380 次,近一周安装 16 次,下载 133 次。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。

adaptive-subagents 安全吗?

第三方扫描有提醒项,说明存在需要人工确认的行为。安装前请打开源码看清它读了什么、联网到哪里。

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。

先想清楚的地方

  • 许可证没有明确标注,能不能商用、能不能再分发都不确定。
  • 第三方扫描存在提醒项或未通过项,需要人工逐条确认。
  • 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

  • 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
adaptive-subagents

自适应子 Agent · 本页

380—需要联网未明确有提醒

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

Adaptive Subagent Routing

FIRST: Decompose Before Acting

Do NOT start working on the task directly. Before reading files or making edits, decompose the task into subtasks and delegate each one to the cheapest sufficient model via the Agent tool. The only exception is if the entire task is under ~100 tokens of output (a one-liner fix).

Quick Decision (apply to EVERY delegation)

Default: Haiku. Escalate only with reason.

  1. Is this a mechanical lookup? (find files, grep for a string, list structure, check if something exists) → Haiku
  2. Does it require comprehension or writing? (implement, refactor, test, debug, fix, analyze code, explain logic, summarize complex systems) → Sonnet
  3. Is it architectural, security-sensitive, or ambiguous? → Opus

Haiku boundary: Haiku can *find* things and *format* things. It cannot *understand* or *reason about* code. If the task requires reading code and making a judgment, that's Sonnet.

If unsure between two tiers, pick the cheaper one. Escalate after failure, not before.

Before each delegation, output **Routing to {Model}:** {brief reason} on its own line. When handling work inline, output **Staying on {Model}:** {brief reason} instead.

When to Delegate vs Handle Inline

Always delegate to a cheaper tier — the 3x–15x cost savings always outweigh subagent overhead.

Skip delegation only when:

  • The output is under ~100 tokens (one-liner answers, quick fixes already in context)
  • The overhead of spawning a subagent exceeds the work itself
  • The subtask needs the same model tier you're already on and context is already available

Routing Rules

Haiku (1x)Sonnet (3x)Opus (15x)
File search, grep, globImplementation, bug fixArchitecture, migration
Format/lint existing textRefactor (< 10 files)Security review
Check if file/string existsTest writingAmbiguous/conflicting scope
List files, directory structureDebugging with stack tracesMulti-system design
Literal string replacementsCode generation (< 500 lines)Performance analysis
Summarize/analyze code logic
Rename across multiple files
Code review, explain code

Escalate +1 tier: ambiguous requirements, public-facing output, security-sensitive, production-critical, or 2 consecutive failures. Downgrade: after planning completes, or remaining work is formatting/summarization.

Cost Ratios

ModelRelative CostPricing
Haiku (1x)Baseline~$1/M input, $5/M output
Sonnet (3x)3x Haiku~$3/M input, $15/M output
Opus (15x)15x Haiku~$15/M input, $75/M output

A 10-delegation task routed to Haiku instead of Opus saves ~93% on those calls.

Per-Subtask Routing

When a request involves multiple steps:

  1. Decompose first. Break the request into a todo list of subtasks.
  2. Route each subtask independently. Most items are cheaper than the overall task.
  3. Downgrade after planning. If Opus produces a plan, implementation goes to Sonnet. Lookups and cleanup go to Haiku.

Example — "design and implement a caching layer":

  • Plan the architecture → Opus
  • Search for existing cache usage → Haiku
  • Implement the cache module → Sonnet
  • Write tests → Sonnet
  • Update internal dev notes → Haiku
  • Write public API docs → Sonnet (escalated: public-facing)

Delegation

Choose agent type by task and model by complexity independently.

Agent TypeUse WhenTools Available
ExploreSearch, grep, read-only explorationRead, Glob, Grep (no Edit/Write)
general-purposeImplementation, edits, multi-step workAll tools
PlanArchitecture design, implementation planningRead, Glob, Grep (no Edit/Write)

Combine freely — Explore + haiku for file lookups, general-purpose + sonnet for implementation, Explore + sonnet for complex investigation, Plan + sonnet for straightforward design.

Agent(subagent_type: "Explore", model: "haiku", description: "...", prompt: "...")
Agent(subagent_type: "general-purpose", model: "sonnet", description: "...", prompt: "...")
Agent(subagent_type: "Explore", model: "sonnet", description: "...", prompt: "...")
Agent(subagent_type: "Plan", model: "sonnet", description: "...", prompt: "...")

Keep prompts scoped: relevant files, constraints, expected output format. The description parameter is required — use a short 3-5 word summary.

Expected Output Formats

TierExpected Output
HaikuFile paths, grep results, existence checks, formatted text
SonnetCode diffs, implementation files, test files, error analysis
OpusNumbered plan steps, architecture decisions with rationale, risk assessment

Parallel Fan-Out

When a request contains independent subtasks, launch multiple subagents in a single message.

Before splitting, build a dependency graph. Does any subtask need another's output, or do they modify the same file? If yes, run them sequentially.

PatternParallel?Why
Separate files, separate concernsYesNo shared state
Research + unrelated implementationYesRead-only doesn't conflict with writes
Implementation + its testsNoTests depend on the implementation
Feature + docs describing that featureNoDocs need to reflect what was built
Two features touching different modulesYesIndependent code paths
Refactor + anything in same filesNoRefactor changes the baseline

After all phases return, review outputs for conflicts before applying.

User Overrides

If the user says any of the following, respect it for the current request:

  • "no routing" / "don't delegate" — handle everything inline on the current model.
  • "use Opus" / "use Sonnet" / "use Haiku" — force that tier for all delegations.

Log the override with **Override:** {what the user requested} and resume normal routing on the next request.

Routing Log

After each routing decision, append a line to routing.log in the project root using the Bash tool:

echo "{model} | {agent_type or inline} | {estimated savings vs Opus, e.g. ~93%} | {brief task description}" >> routing.log

Log every **Routing to** and **Staying on** decision.

Guardrails

  • Max 2 retries per subagent, then escalate or ask the user.
  • Max 5 sequential delegations per user request. No limit on parallel.
  • Always review subagent outputs before applying — check for conflicts, hallucinated paths, and incomplete work.
  • Do NOT modify project files: Never write routing rules to CLAUDE.md. Never add hooks to settings.json. This skill is loaded automatically by the plugin.

平台分布

Codex

39.29%
按下载量换算52

Claude

28.88%
按下载量换算38

Cursor

17.04%
按下载量换算23

Gemini CLI

8.99%
按下载量换算12

安全审计

Gen Agent Trust Hub

可疑

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。来源安全扫描存在提醒或未通过项,安装前请自行复核。目前只有一个公开来源,建议同时核对源仓库。

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