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Agent Skill · 研究检索

agent-army(特工军)

agent-army 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。

agent-army 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,第三方扫描有提醒项,按安装量在研究检索类的 73,675 个 Skill 里排第 50,189。

总安装 624周安装 26GitHub Stars 103下载 208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:agent-army(特工军)
来源仓库:https://github.com/onewave-ai/claude-skills
仓库路径:skills/agent-army
安装命令:
npx skills add https://github.com/onewave-ai/claude-skills --skill agent-army
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/onewave-ai/claude-skills --skill agent-army

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。

agent-army 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。适用于信息收集、研究支持、线索整理等需要多轮筛选和关联分析的场景。

通过分层代理架构实现大规模上下文管理,支持子代理专项处理和问题标记反馈机制。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操作。agent-army 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

来源仓库内路径:skills/agent-army

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/onewave-ai/claude-skills --skill agent-army;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

agent-army 怎么安装?

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

agent-army 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。

agent-army 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/onewave-ai/claude-skills --skill agent-army 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。

agent-army 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。

agent-army 用的人多吗?

公开数据是累计安装 624 次,近一周安装 26 次,下载 208 次,GitHub 103 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。

agent-army 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

  • 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

  • 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
agent-army

特工军 · 本页

624103执行命令未明确有提醒

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

Agent Army

Architecture

Commander
 |
 |-- Layer 1: Team (3 to 50+, each = own 1M context)
 |    |
 |    |-- Agent A (1M) -- Sub-agent A1 (own context), A2 (own context), ...
 |    |-- Agent B (1M) -- Sub-agent B1 (own context), B2 (own context), ...
 |    |-- Agent C (1M) -- Sub-agent C1 (own context), C2 (own context), ...
 |    |-- ... (no cap)

Layer 1 Prompt Template

This is what spawned agents actually see. It is the most important section in this skill.

You are [AGENT_NAME], specialist on [DOMAIN].

Objective: [One sentence]
Approved patterns: [Exact values -- hex codes, class names, etc.]
Forbidden patterns: [What to remove/avoid]
Your files: [Absolute paths with line counts]
Rules: [Constraints]. Skip files already using approved patterns. Flag issues outside your files in "Flags for Commander" -- do NOT fix them.

CRITICAL: You MUST use the Agent tool to spawn the sub-agents listed below. Do NOT do the work yourself. Do NOT skip spawning. Deploy ALL sub-agents in a single message with multiple Agent tool calls.

Sub-agents:
- "[NAME]": [files with line counts]
- "[NAME]": [files with line counts]

Pass each sub-agent: objective, their files, approved/forbidden patterns, rules, report format. After all complete, aggregate reports and verify no forbidden patterns remain.

Layer 2 Prompt Template

You are [SUB_AGENT_NAME], working under [TEAM_MEMBER_NAME].

Objective: [One sentence]
Files you own: [Absolute paths with line counts -- only touch these]
Approved/Forbidden patterns: [Exact values to use and remove]
Rules: [Constraints]. Skip files already correct. Flag issues outside your files -- do NOT fix them.

Report when done: Files Modified (file: N replacements), Files Skipped (already correct), Flags for Commander, Issues Encountered, Status (COMPLETE/PARTIAL/FAILED).
  1. EVERY Layer 1 agent MUST spawn 2+ sub-agents. No exceptions. If deploying without sub-agents, STOP and restructure.
  2. NEVER silently reduce army size. Match the user's chosen tier.
  3. Report as agents complete: [Agent N/M complete] name: X files modified, Y flags
  4. Show the army plan before deploying (Full Mode). Quick Mode: compose plan internally, skip confirmation.
  5. Sub-agent deployment instructions go INSIDE the Layer 1 brief. If missing, sub-agents will not exist.
  6. Build check after every wave. If it fails, trigger a fix wave.
  7. "Keep going" / "don't stop" = continuous mode. Launch new agents as each completes. Do not wait. Do not ask.

Army Size

Confirm tier before starting. Present this table:

| Tier | Agents | Total with Sub-agents | Est. Tokens |
|------|--------|----------------------|-------------|
| Conservative | 3 | ~9 | ~200-500K |
| Standard | 5-10 | ~15-30 | ~500K-1.5M |
| Aggressive | 10-20 | ~30-60 | ~1.5-4M |
| Maximum | 20-50+ | ~60-100+ | ~4M+ |
| Custom | You pick | You pick | Varies |

Token estimates vary by task complexity. Pick a tier or enter a custom number:

Default to Standard if user says "just do it." Tier question applies to BOTH Quick and Full modes.

After recon (Step 3), recommend a specific number based on what you found. Example: "Found 35 files across 6 domains. I recommend Aggressive tier: 8 Layer 1 agents with 2-3 sub-agents each (~22 total, ~2M tokens). Want to adjust?"

Deployment Gate

Output this checklist in your response before deploying. Do NOT skip it. Do NOT just check it mentally.

DEPLOYMENT GATE:
[ ] Every L1 brief contains "You MUST spawn N sub-agents"
[ ] Every sub-agent named with specific files assigned
[ ] Every file owned by exactly one sub-agent
[ ] L1 briefs include full sub-agent deployment instructions
[ ] Tier matches user's selection

All must PASS. If any FAIL: fix the plan first.

Protocol

Mode: If scope is clear and specific (file paths, exact changes), skip to Step 3. Otherwise start at Step 1.

Step 1: Intake (Full Mode)

Confirm with user:

  1. Goal (one sentence)
  2. Scope (files, directories, or "everything")
  3. Constraints (don't touch X, match Y style)
  4. Tier (show table above)

If user already provided context, confirm in one line: "Goal: [X]. Scope: [Y]. Tier: [Z]. Starting."

Step 2: Git Checkpoint

  1. Run git status. Warn if uncommitted changes.
  2. Create checkpoint: git checkout -b agent-army/checkpoint-{timestamp}, switch back.
  3. No git repo? Warn user and get confirmation.

Step 3: Recon

  1. Scan -- Grep, Glob, Read to find all affected files
  2. Count units of work
  3. wc -l each file. Flag 500+ line files as heavy (assign solo)
  4. Classify into domains (by directory, imports, file type, naming pattern)
  5. Identify shared dependencies (foundation files -- handle first)
  6. Identify build command (check package.json, Makefile, etc.)

Output scope report:

Files: N | Heavy: [list] | Domains: [list] | Shared deps: [list] | Build cmd: [cmd]

Step 4: Compose

  1. Foundation Agent for shared deps (runs first, before parallel wave)
  2. Layer 1: 1 agent per domain. Split large domains across multiple agents.
  3. Layer 2: 2+ sub-agents per L1 agent based on file weight
  4. Name every agent. Assign every file to exactly one sub-agent.

Output army plan. Full Mode: pause for "Proceed?" Quick Mode: show one-line summary, deploy.

Step 5: Deploy

  1. Foundation Agent first (if needed). Wait for completion.
  2. Launch ALL Layer 1 agents in parallel (run_in_background: true, single message).
  3. L1 agents spawn L2 sub-agents in parallel (per their brief).
  4. Report each completion: [Agent N/M complete] name: results

Step 6: Verify

  1. Re-scan for remaining violations (same searches as Step 3)
  2. Run build command
  3. Resolve cross-team flags
  4. Output army report:
Agents: N total | Files modified: N | Skipped: N | Build: PASS/FAIL | Flags: [list] | Rollback: git checkout agent-army/checkpoint-{timestamp}

Waves

After Wave 1: build + re-scan. If clean, done. If issues remain, deploy Wave 2 (fix wave). If still issues, Wave 3 (propagate to tests/docs). Max 3 waves. Pause for user approval before each.

Shared Scratchpad (optional)

For complex multi-wave tasks, write .army-state.md after Wave 1: files modified, flags, issues, decisions. Wave 2 agents read it directly for full context. Skip for single-wave tasks.

Report Format

Every agent returns:

## Report: [Name]
Files Modified: [file: N replacements]
Files Skipped: [file: reason]
Flags for Commander: [issue or "None"]
Issues: [issue or "None"]
Status: COMPLETE / PARTIAL / FAILED

Error Handling

  • Sub-agent fails: L1 agent retries or spawns replacement
  • L1 agent fails: Commander spawns replacement with same brief
  • Build failure: compare against checkpoint, diagnose, fix wave

平台分布

Codex

36.94%
按下载量换算77

Claude

32.58%
按下载量换算68

Cursor

17.11%
按下载量换算36

Gemini CLI

9.06%
按下载量换算19

安全审计

Gen Agent Trust Hub

通过

Socket

可疑

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/onewave-ai/claude-skills --skill agent-army 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。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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