swarm-coding
Orchestrates multi-agent hierarchical swarms using a divide-and-conquer architecture for complex, multi-system, or orthogonal engineering initiatives (e.g., concurrent backend, frontend, database, QA). Manages hierarchical Lead Agents and Specialists, disjoint work allocations, a
供给资产档案
编程与开发 Agent
代码审查、仓库分析、测试、CI、GitHub、DevOps 与开发工作流 Skill。
场景
Testing and QA
I need my agent to test a web app, reproduce bugs, and verify fixes.
适配 Agent
Claude Code + CLI + Codex
适用于 Codex、Claude Code、Cursor、CLI 或自定义 Agent。
安装
就绪
npx skills add danicat/skills --skill swarm-coding
维护状态
新鲜
今天有推送
风险
需审查
Dependency or permission surface needs review
GitHub 质量
16
59/100 质量 · 61/100 信任
覆盖标签
审查说明
Dependency or permission surface needs review · Permission surface may require sandboxing
Agent 采用评分卡
一眼查看信任、审计与安装准备度
这些分数综合公开仓库元数据、OpenAgentSkill 审查信号、维护新鲜度与安装准备度。它用于候选筛选,不替代人工审查。
质量
有潜力有用的候选项,但采用前应与替代方案比较。
信任
Do not auto-installTrust Score v5 found insufficient evidence for agent installation. Treat this as discovery material, not an executable recommendation.
审计
需审查对安装准备度、安全元数据、维护情况与采用风险的机器可读审查。
OpenAgentSkill 信任评分 v5
安装前需人工审查
Choose a stronger alternative or inspect the source manually before any install attempt.
Stars
16 个 GitHub Stars
仓库活跃度
16 个 Star,3 个 Fork
维护状态
今天有推送
许可证
Apache-2.0
安装
npx skills add danicat/skills --skill swarm-coding
安装安全性
标准软件包或运行时安装路径
权限范围
shell or command execution, filesystem or document access
Agent 结果
暂未有 Agent 结果数据
文档
Usable metadata, review docs
风险摘要
生产前审查
- The skill references specific agent framework tools (e.g., define_subagent, invoke_subagent, ask_question) without clarifying that these are environment-specific, which may limit portability.
- Low GitHub adoption signal
- Quality score needs review
- Permission surface needs review: shell or command execution, filesystem or document access
安装准备度
安装路径可用
- 安装路径可用
- 仓库证据可用
- 已声明许可证
- 暂无 Agent 验证结果证据
Agent 可读元数据
这个 Skill 的机器可读决策数据。
使用此区块或内嵌 JSON 判断 Agent 是否应安装该 Skill、选择替代方案,或先请求人工审查。
适用任务
- Testing and QA 工作流
- Claude Code 团队
- builders willing to evaluate younger projects
- Run test suites
适用 Agent
安装决策
- 命令
- npx skills add danicat/skills --skill swarm-coding
- 策略
- 审查
- 人工审查
- 是
信任与风险
- 信任
- 53/100
- 审计
- 71/100
- 风险级别
- 需审查
结果闭环
- 端点
- /api/agent/outcome
- 事件 ID
- resolve
- 结果
- 5
不适用场景
- 需要厂商支持 SLA 的团队
- production agents without a repository review
- Low GitHub adoption signal
- The skill references specific agent framework tools (e.g., define_subagent, invoke_subagent, ask_question) without clarifying that these are environment-specific, which may limit portability.
- 暂未有 OpenAgentSkill 使用反馈数据
替代 Skill
Last30days Skill
53.5K Stars
npx skills add mvanhorn/last30days-skill -g
替代 Skill
Academic Research Skills
38.4K Stars
npx skills add Imbad0202/academic-research-skills
替代 Skill
GPT Researcher
28.0K Stars
npx skills add assafelovic/gpt-researcher
替代 Skill
DeepResearch
19.8K Stars
npx skills add Alibaba-NLP/DeepResearch
Agent 安全 v2
39/100 · 避免自动安装
Sparse or mixed signals. Useful for discovery, but not for autonomous installation.
Test manually in an isolated workspace and compare against safer alternatives.
高
Shell 或命令执行
Skill 元数据引用了终端、CLI、Shell、子进程或命令执行工作流。
中
网络访问
Skill 可能访问远程页面、API、仓库或外部服务。
中
文件系统访问
Skill 可能读取或写入项目文件、文档、生成产物或本地工作区状态。
中
数据库访问
Skill 可能检查 Schema、查询数据库或处理持久化存储。
- 高风险权限提示:Shell 或命令执行
- Dependency or permission surface needs review
安装目标
在你的 Agent 工作流中安装此 Skill
通过公开安装端点获取命令、安全清单、目标提示词和该 Skill 的规范链接。
OpenAgentSkill CLI
Resolve policy, run the source installer safely, and report a verified install receipt.
$ npx --yes https://github.com/Leon-Drq/openagentskill/releases/download/cli-v0.2.1/openagentskill-0.2.1.tgz install danicat-swarm-codingAgent 解析计划
让 Agent 在安装前验证匹配度。
Resolve API 返回首选 Skill、替代方案、安全策略、审计说明、安装目标和可直接执行的提示词,无需抓取此页面。
打开 JSON
/api/agent/resolve?task=Use%20swarm-coding%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Resolve 文本
/api/agent/resolve?task=Use%20swarm-coding%20for%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text
安装交接
/api/skills/danicat-swarm-coding/install
Agent 应检查
- 从 Resolve API 检查任务匹配与替代方案。
- 检查审计评分、信任评分和安全策略警告。
- 检查 Codex、Claude Code、Cursor 或 CLI 的安装目标兼容性。
复制提示词
Task: Use swarm-coding in this workspace.
Resolve first: https://www.openagentskill.com/api/agent/resolve?task=Use%20swarm-coding%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Review install handoff: https://www.openagentskill.com/api/skills/danicat-swarm-coding/install
Install command: npx skills add danicat/skills --skill swarm-coding
Before running it, summarize audit warnings, required permissions, and the fallback skill if install is risky.Agent 交接
把安装路径交给 Agent,而不是再给一个目录页。
通过公开安装端点获取命令、安全清单、目标提示词和该 Skill 的规范链接。
安装交接
/api/skills/danicat-swarm-coding/install
LLM 文本格式
/api/skills/danicat-swarm-coding/install?format=text
寻找替代方案
/api/skills/search?q=swarm-coding&limit=3
Agent 提示词
Use swarm-coding for this task. Review https://www.openagentskill.com/api/skills/danicat-swarm-coding/install, then install with: npx skills add danicat/skills --skill swarm-codingRegistry 元数据
用于自动选择 Skill 的 Agent 可读档案。
本页通过 Registry API 提供相同的决策、信任、审计、场景和安装信号,让 Agent 无需抓取界面即可排序。
Agent 决策面板
Fallback candidate for Testing and QA
先用此 Skill 做原型验证,并保留备选方案。
栈中角色
备选候选
主要匹配
Testing and QA
信任标签
先做原型验证
安装路径
命令已就绪
适用场景
- Testing and QA 工作流
- Claude Code 团队
- builders willing to evaluate younger projects
证据
- 仓库近期活跃
- 已提供安装命令或 GitHub 仓库
- 59/100 质量档案
先审查
- Low GitHub adoption signal
- The skill references specific agent framework tools (e.g., define_subagent, invoke_subagent, ask_question) without clarifying that these are environment-specific, which may limit portability.
- 暂未有 OpenAgentSkill 使用反馈数据
实施路径
- 1在沙盒 Agent 中安装它,并端到端完成一次Testing and QA任务。
- 2Compare output quality, latency, and failure behavior against at least one alternative.
- 3Promote it into production only after reviewing repository permissions, license, and maintenance signals.
信任档案
Do not auto-install
Trust Score v5 found insufficient evidence for agent installation. Treat this as discovery material, not an executable recommendation.
GitHub 采用度
修复16 个 GitHub Stars
Star/Fork 活跃度
修复16 个 Star,3 个 Fork; 当前元数据中没有议题活跃度信息
近期维护
通过今天有推送
许可证清晰度
通过Apache-2.0
积极信号
- AI 审查已通过
- 安装路径可用
- 仓库证据可用
- 近期维护的仓库
- 安装命令未发现明显高风险模式
- 结果闭环已就绪,但需要首次真实 Agent 运行
安装前审查
- The skill references specific agent framework tools (e.g., define_subagent, invoke_subagent, ask_question) without clarifying that these are environment-specific, which may limit portability.
- Low GitHub adoption signal
- Quality score needs review
- Permission surface needs review: shell or command execution, filesystem or document access
- GitHub adoption: 16 GitHub stars
- Stars/forks activity: 16 stars, 3 forks; issue activity unavailable in current metadata
- Dependency/runtime risk: command execution surface, network or browser surface
- Permission surface: shell or command execution, filesystem or document access
- 暂未有真实 Agent 结果报告
- 无人值守安装前需要人工审查
建议操作
Choose a stronger alternative or inspect the source manually before any install attempt.
质量档案
有潜力 适用于 Agent 工作流的候选
有用的候选项,但采用前应与替代方案比较。
工作流匹配
在这些场景使用此 Skill
Verify behavior
Testing and QA
I need my agent to test a web app, reproduce bugs, and verify fixes.
Operate web apps
Browser automation
I need my agent to control a browser, fill forms, and verify web app workflows.
Automate repeated work
Workflow automation
I need my agent to automate a repeated workflow across tools and files.
工作流匹配
加入完整工作流
Operate and verify web apps
Browser QA agent
A workflow for agents that navigate products, fill forms, take screenshots, and verify real user flows across web applications.
Design, build, test, and ship interfaces
Frontend and UI
A practical workflow for agents that turn product briefs or Figma designs into polished frontend code, review the result, test it in a browser, and prepare a safe deployment.
Find, compare, and synthesize
Research report agent
A workflow for agents that gather sources, compare claims, summarize long material, and draft useful research briefs.
替代方案短名单
安装前对比
可能适合该任务的相近 Skill。
Last30days Skill
Research the last 30 days across Reddit, X, YouTube, Hacker News, Polymarket, GitHub, and the web, then synthesize a grounded brief for an AI agent.
Academic Research Skills
Academic Research Skills for Claude Code: research → write → review → revise → finalize
GPT Researcher
Run autonomous deep research over web and local sources
DeepResearch
Tongyi Deep Research, the Leading Open-source Deep Research Agent
概览
--- name: swarm-coding description: > Orchestrates multi-agent hierarchical swarms using a divide-and-conquer architecture for complex, multi-system, or orthogonal engineering initiatives (e.g., concurrent backend, frontend, database, QA). Manages hierarchical Lead Agents and Specialists, disjoint work allocations, and strict parent-child communication. Activate whenever the user mentions 'swarm', requests multi-agent team coordination, or needs context isolation across multiple technical domains. license: Apache-2.0 metadata: category: agents tags: "swarm, subagents, parallel, orchestration, strategy, complexity, coordination" author: Daniela Petruzalek (daniela@danicat.dev) version: "0.2.0" catalog: https://skills.danicat.dev ---
# Swarm Coding
Swarm Coding divides complex engineering objectives among multiple specialized subagents structured in a clear hierarchical organization chart. This divide-and-conquer strategy guarantees context isolation, prevents cross-domain pollution, and accelerates execution by keeping subagent tasks narrowly scoped.
> [!NOTE] > In this guide, the terms "agent" and "subagent" are used interchangeably.
---
## ⚡ Core Principles & Operational Rules
1. **Mandatory Activation:** Activate this skill immediately on any mention of the word "swarm" (case-insensitive) in relation to planning or executing a task. 2. **Coordinator Persistence & Non-Execution:** - The ROOT Swarm Coordinator ALWAYS remains a coordinator and NEVER falls back to an executor. - The Swarm Coordinator is strictly forbidden from writing production implementation code, running tests/builds, or performing direct command execution. 3. **Split Coordinator Profiles:** - **Swarm Coordinator (ROOT):** Attributed strictly to the ROOT agent that activated the skill (Multiplicity: 1). Defines the top-level **Org Chart**, names Lead Agents, allocates the agent budget, writes top-level architecture specs, and coordinates overall progress. - **Lead Agent:** Attributed to domain or system leads (Multiplicity: N, one per system/domain). Receives an allocated sub-budget from the Swarm Coordinator, assembles a specialist team, writes domain specifications, delegates tasks, and integrates domain deliverables. 4. **Specialist Role:** Attributed to task executors. Designs and implements narrowly-scoped components within a single domain, adhering to domain specs and running operational validation loops. 5. **Strict Communication Hierarchy (No Lateral Messaging):** - **Allowed:** Messaging between immediate parents and children ONLY (Swarm Coordinator $\leftrightarrow$ Lead Agent, Lead Agent $\leftrightarrow$ Specialist). - **Forbidden:** Direct communication between agents on the SAME layer (Lead Agent $\leftrightarrow$ Lead Agent, Specialist $\leftrightarrow$ Specialist) or direct escalation (Specialist $\leftrightarrow$ Swarm Coordinator) is strictly forbidden. - **Design Document First:** Inter-domain or cross-layer coordination MUST be handled by writing or updating shared design documents first, then notifying parent/child agents via hierarchical messaging. 6. **Team Continuity & Semi-Permanent Hierarchy (No Disposable Assets):** Treat agents as persistent team members, not disposable assets. Do not prematurely terminate subagents and spawn new ones. Retain and aggressively reuse active Lead Agents and Specialists across task iterations to preserve accumulated context. 7. **Fine-Grained Targeted Testing (No Broad Root Sweeps):** Specialists MUST execute fine-grained, package-scoped unit tests (e.g., `go test ./internal/physics/...`) strictly targeting their assigned task. Running broad project-root test commands (e.g., `go test ./...`) is strictly forbidden for Specialists unless explicitly requested by the Swarm Coordinator, preventing cross-task contamination and false failures while parallel agents work concurrently.
---
## 🎯 Agent Budget & Degree of Parallelism (DOP)
* **Definition**: **Agent Budget** is synonymous with **Degree of Parallelism (DOP)**. It defines the maximum number of **active, concurrent subagents** allowed to execute at the exact same time across the entire swarm hierarchy. * **Active vs. Past Capacity**: Completed or terminated subagents do **not** consume budget. The budget applies strictly to currently running subagents. When a subagent completes its work, its concurrency slot is immediately freed. * **Default Concurrency**: Assumes a default budget of **10** active concurrent agents if omitted by the user. * **Low Budget Guard ($\le 1$):** If the user explicitly specifies an `agent budget <= 1`: - **HALT immediately** and do NOT spawn subagents or start implementation. - Trigger an interactive conversation with the user using `ask_question`. - Explain that multi-agent swarm orchestration requires budget $> 1$ (recommended 10). Present choices: (1) Increase budget to 10 (Recommended), (2) Specify a custom budget $> 1$, or (3) Fall back to single-agent execution. * **Adaptive Team Hierarchy**: - **Focused ($\text{DOP} \le 4$)**: Flat structure (Coordinator $\rightarrow$ Specialists directly). - **Standard / Multi-Domain ($\text{DOP} \ge 6$)**: Hierarchical structure (Coordinator $\rightarrow$ Domain Tech Leads $\rightarrow$ Specialists). - **Massive Swarms ($\text{DOP} \ge 20\text{--}50+$)**: Subagents act as focused micro-probes, returning dense, high-signal structured findings ($\le 150$ words) to enable crisp synthesis without context dilution.
### Concurrency Sizing Matrix:
| Initiative Scale | Agent Budget ($\text{DOP}$) | Structure Type | Domain Tech Leads | Specialists per Lead | Typical Scope | | :--- | :---: | :---: | :---: | :---: | :--- | | **Focused** | **2–4** | Flat | None (Direct Coordinator) | 2–4 Specialists | Targeted dual-subsystem or focused feature | | **Standard (Default)** | **10** | Hierarchical | 2–3 (e.g., Backend, Frontend, QA) | 2–3 per domain | Full-stack application, multi-package service | | **Complex Platform** | **16–20+** | Hierarchical | 4–5 (API, Core Engine, UI, Infra, QA) | 3–4 per domain | Distributed microservices, full platform build | | **Massive Swarm** | **20–50+** | Elastic Micro-Probes | Distributed Leads / Probes | Micro-probes ($\le 150$w) | Wide ecosystem sweeps, multi-file migrations |
---
## 📡 Non-Blocking Coordinator & Reactive Concurrency
The Swarm Coordinator is the primary user interface and top-level organizational conductor. It must remain **unblocked $\ge 99\%$ of the time** to receive steering comments, scope modifications, and status requests from the user.
1. **Role Separation (Delegation over Execution):** - The Swarm Coordinator acts like an engineering director: it breaks down epics, writes top-level architectural contracts, and manages the org chart. It **never** blocks itself with sequential coding, manual building, or terminal test runs. 2. **Fire-and-Yield Concurrency:** - When the Coordinator spawns Lead Agents via `invoke_subagent`, it **immediately halts tool calls to end its turn**. It never loops, sleeps, or polls. 3. **Always Unblocked for User Steering & Status Inquiries:** - Because the Coordinator never enters busy-wait polling loops, it is permanently available to process incoming user messages while the swarm works in the background: - **Status Inquiries**: The Coordinator can immediately provide live progress updates or inspect active workers via `manage_subagents (Action="list")`. - **In-Flight Steering / Scope Changes**: If the user provides new constraints or changes requirements mid-run, the Coordinator can steer active Lead Agents via `send_message` or cancel/restart them via `manage_subagents (Action="kill")`. 4. **Sole User Escalation Interface:** - Subagents do not possess `ask_question`. All requirement ambiguities or design trade-offs encountered by Specialists are messaged up to their Tech Lead, who routes them to the Swarm Coordinator via `send_message`. The Coordinator prompts the user with `ask_question` and relays decisions back down the hierarchy.
---
## 🔄 Map-Reduce Workflow & The "Reduce" (Reconciliation) Step
Swarm Coding operates as a two-stage **Map-Reduce** engineering pipeline:
```mermaid graph TD subgraph Map Phase [1. Map Phase: Parallel Stream Execution] direction TB L1[Tech Lead Backend] --> S1[Specialist: Core API] L1 --> S2[Specialist: Database Models] L2[Tech Lead Frontend] --> S3[Specialist: UI Components] end
subgraph Reduce Phase [2. Reduce Phase: Reconciliation & Final Verification] direction TB AUD[Audit Boundaries & Scan Placeholders] --> WIRE[Task QA/Integration Specialist to Wire Real Components] WIRE --> PURGE[Purge Temporary Stubs & Mock Adapters] PURGE --> E2E[Run End-to-End Integration Test Suite] E2E --> PROOF[Deliver Verified Evidence Log to Coordinator] end
Map Phase --> Reduce Phase ```
### 1. Map Phase (Parallel Development & Collision Avoidance) * **Flexible Subagent Prompting**: Provide clear domain goals and target boundaries in prompts without brittle syntax constraints. * **Tech Lead Arbitration**: Team Leads dynamically arbitrate file boundaries and dependencies among their specialists as changes evolve. * **Temporary Interface Contracts**: When Specialist A depends on in-progress work from Specialist B, they program against agreed interface stubs or mocks.
### 2. The Final "Reduce" Phase (Integration & Placeholder Purge) Parallel execution often leaves behind temporary mocks or stubs where real implementations were created by peer agents. Before declaring success, the Coordinator orchestrates the final **Reduce** step:
1. **Placeholder & Stub Audit**: Scans code boundaries to ensure no dangling `TODO` comments, dummy return values, or temporary mock adapters survive. 2. **Reconciliation & Real Component Wiring**: The Coordinator tasks a designated **Integration/QA Specialist** to connect all real modules together. 3. **End-to-End Project Verification**: The QA Specialist runs full project builds, integration tests, and linters, reporting actual terminal proof back to the Coordinator before final delivery to the user.
---
## 👥 Mechanics and Roles
Subagents in a Swarm Coding session assume one of three roles:
1. **Swarm Coordinator (ROOT)** [Multiplicity: 1] - Acts as top-level architect and organizational manager. - Defines the **Org Chart**, names Lead Agents for each domain, allocates agent budgets, and writes top-level architecture specs. - **Persistence & Non-Execution:** Strictly forbidden from executing code or running build/test commands. - **Sole User Interface:** Sole agent in the swarm authorized to interact with the user via `ask_question`. 2. **Lead Agent (Domain Tech Lead)** [Multiplicity: N] - Technical lead for a specific domain or system (e.g., Frontend, Backend, Database). - Assembles a Specialist team within their allocated sub-budget, writes domain specs ("Design Document First"), deconstructs domain tasks, arbitrates collisions, and integrates deliverables. - **Tool Restrictions:** Command/script execution is disabled (`commandExecutionPolicy: off`). Delegates execution to Specialists and routes user questions up to the Swarm Coordinator via `send_message`. 3. **Specialist (Task Implementer / QA)** [Multiplicity: N] - Executes narrowly-scoped technical tasks within their assigned domain. - Follows domain specifications, executes the operational validation loop (build, test, lint, format), replaces stubs, and provides proof-of-validation logs to their parent Lead Agent.
---
## 💬 Communication Hierarchy & Rules
```mermaid graph TD ROOT["Swarm Coordinator (ROOT)"] <-->|Parent-Child Message| LEAD1["Lead Agent (Backend)"] ROOT <-->|Parent-Child Message| LEAD2["Lead Agent (Frontend)"] LEAD1 <-->|Parent-Child Message| SPEC1["Specialist (API Dev)"] LEAD1 <-->|Parent-Child Messa
技术详情
- 版本
- 1.0.0
- 许可证
- Apache-2.0
- 最近更新
- 2026年8月24日
- 发布时间
- 2026年8月24日
决策摘要
备选候选
仓库近期活跃
Agent 验证证据
Agent 验证证据
来自解析、审查、安装和一次小范围运行后的结果报告。
- 成功率
- —
- 近期失败
- —
- 结果
- 0
- 输出质量
- —
- 失败
- 0
- 不相关
- 0
- 安装次数
- 0
- 风险拦截
- 0
- 需要配置
- 0
- 生产环境
- 0
暂时没有 Agent 结果数据。首次 Agent 执行可以通过 /api/agent/outcome 报告成功、需要设置、风险拦截、失败或不相关。
增长闭环
分享工具包
为 swarm-coding 准备的场景化草稿,可手动发布到 X。
swarm-coding: Orchestrates multi-agent hierarchical swarms using a divide-and-conquer architecture for comp... 16 stars https://www.openagentskill.com/skills/danicat-swarm-coding?ref=x
可选:带安装命令的回复
Listing + install path for swarm-coding: https://www.openagentskill.com/skills/danicat-swarm-coding?ref=x Install: npx skills add danicat/skills --skill swarm-coding
收录来源
Registry 收录
此列表来自公开来源,维护者认领获批前不会标记为官方。
- 创作者
- danicat
- 收录方
- OpenAgentSkill 社区索引
归属链接指向公开仓库或创作者主页。创作者可认领列表以更新所有权信号。
认领此 Skill所有者认领
认领此 Skill 页面
这条 Registry 收录 列表归属于 danicat,但尚未标记为官方。认领后可增加已验证所有者信号,使后续发布、安装和审计更新更值得信赖。
创作者外链工具包
将证据徽章加入你的 README
在开发者评估仓库的位置展示规范页面、当前信任与审计信号,以及真实的 Agent 验证证据。
[](https://www.openagentskill.com/skills/danicat-swarm-coding)
[](https://www.openagentskill.com/skills/danicat-swarm-coding)
[](https://www.openagentskill.com/skills/danicat-swarm-coding/audit)
[](https://www.openagentskill.com/skills/danicat-swarm-coding)作者
danicat
@danicat
平台适配
健康信号
- GitHub Stars
- 16
- 质量评分
- 32/100
- 最近 GitHub 推送
- 2026年8月23日
- 框架提示
- 未知
- OpenAgentSkill 浏览量
- 0
- 复制安装命令
- 0
- 跳转点击
- 0
社区信号
告诉我们这个 Skill 是否对你的 Agent 工作流有帮助。汇总反馈会持续改善排序。
信任与安全
Do not auto-install
- GitHub 采用度16 个 GitHub Stars修复
- Star/Fork 活跃度16 个 Star,3 个 Fork; 当前元数据中没有议题活跃度信息修复
- 近期维护今天有推送通过
- 许可证清晰度Apache-2.0通过
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