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multi agent analysis and execution

作者 RubenCoppensOnGit · GitHub ↗ · v1.0.4 · MIT-0
cross-platform ✓ 安全检测通过
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在 OpenClaw 中安装
/install multi-agent-analysis-execution
功能描述
Orchestrate complex multi-agent workflows with explicit coordinator planning, execution governance, and *automatic output management*. Each skill run creates...
使用说明 (SKILL.md)

multi_agent_coordinator - SKILL.md (Lean + Debug Mode)

Description

Orchestrate complex multi-agent workflows with an explicit coordinator-driven process that plans, sequences, and governs execution across multiple agents.

This version keeps the system lean by default while preserving the full coordination logic, guardrails, and execution discipline required for reliable multi-agent workflows.

Critical Rule: When this skill is invoked, the coordinator process MUST execute fully across all phases. No phases may be skipped or partially executed.


Core Principles

  1. Lean by default — minimal files, fast execution
  2. Debug on demand — full traceability when needed
  3. Run isolation always — every run gets its own directory

Run Directory (Always Created)

Each execution creates a unique directory:

Coordinator_runs/
└── run_YYYYMMDD_HHMMSS/
  • No absolute paths
  • Prevents collisions
  • Keeps runs isolated

Modes

mode = lean (default) | debug

Lean Mode (default)

  • Minimal output
  • No intermediate files

Debug Mode

  • Full artifact generation
  • Complete traceability

The Five-Phase Coordinator Process

MANDATORY EXECUTION CONTRACT

  • You MUST start at PHASE 0
  • You MUST execute phases sequentially (0 → 4)
  • You MUST NOT skip phases
  • You MUST NOT perform ad-hoc reasoning outside the coordinator structure
  • You MUST follow the planned execution (no improvisation during execution)

PHASE 0: COORDINATOR PLANNING

This phase defines the core intelligence of the skill and MUST be executed carefully.

Mandatory Planning Steps

  1. Task Plan Creation

    • Analyze the problem
    • Answer: "What steps are required to solve this?"
    • Decompose into clear, atomic tasks
    • Limit the number of tasks to 15 for any given problem.
  2. Dependency Analysis

    • Answer: "What depends on what?"
    • Identify ordering constraints
    • Identify parallelizable tasks
  3. Execution Group Formation

    • Group independent tasks
    • Define strict execution order between groups
  4. Agent Specification (CRITICAL GUARDRAIL) For each task (max 15 ):

    • Define a single-purpose agent
    • Assign a clear responsibility
    • Define:
      • Inputs
      • Outputs
      • Constraints (read/write, safety, isolation)
        • Work and scanning only limited to the workspace unless explicit approval of user
      • Agent prompt
    • Each task MUST map to exactly one agent
    • No credentials, tokens etc should be passed or to be found in the generated prompt.
    • If the sub agent requires credentials they should be available via ENV or other tools.
  5. Coordinator Execution Strategy The coordinator MUST:

    • Maintain full control of execution
    • Enforce group sequencing
    • Ensure all agents complete before proceeding
    • Handle failures explicitly (no silent failures)

Lean Mode

  • All planning done in memory

Debug Mode

Persist planning artifacts


PHASE 1: EXECUTION

This phase executes the previously defined plan with strict governance.

Execution Rules (MANDATORY)

For each execution group in order:

  1. Spawn all agents with the generated prompt of phase 0 in the group (parallel allowed)
  2. Ensure agents only operate within their defined scope
  3. Wait for ALL agents in the group to complete
  4. Verify successful completion of each agent
  5. ONLY THEN proceed to next group

Failure Handling (GUARDRAIL)

  • If an agent fails:
    • Coordinator MUST detect it
    • MUST stop progression OR handle explicitly
    • MUST report failure in final output

Lean Mode

  • In-memory execution

Debug Mode

  • Persist prompts and outputs

PHASE 2: OUTPUT MANAGEMENT

Core Rule

All outputs MUST remain scoped to the current run directory.

Lean Mode

Only create:

runs/run_YYYYMMDD_HHMMSS/
└── REPORT.final

Optional:

└── run.log

Debug Mode

Full structure:

runs/run_YYYYMMDD_HHMMSS/
├── TASK_PLAN.md
├── DEPENDENCY_GRAPH.md
├── EXECUTION_GROUPS.md
├── AGENT_REQUIREMENTS.md
├── prompts/
├── outputs/
└── REPORT.final

PHASE 3: REPORTING

The coordinator MUST consolidate all results.

Requirements

  • Include results from ALL agents
  • Verify execution order was respected
  • Report any failures or inconsistencies

Output:

REPORT.final

PHASE 4: CLEANUP

Lean Mode

  • Minimal footprint
  • No additional cleanup required

Debug Mode

Optional retention policy:

keep_last = N

Guardrails Summary

  • MUST execute all phases sequentially
  • MUST NOT skip planning
  • MUST NOT bypass coordinator
  • MUST enforce task → agent mapping (1:1)
  • MUST enforce execution group sequencing
  • MUST detect and report failures
  • MUST isolate each run in its own directory

Summary

  • Lean by default, debug when needed
  • Full coordinator logic preserved
  • Strong execution guarantees via guardrails
  • Every run isolated
安全使用建议
This skill is a coherent orchestration template that will create per-run directories, generate planning artifacts and agent prompts, spawn and wait for sub-agents, and persist outputs (especially in debug mode). It does not require credentials or install anything, but it will write files that can contain the problem text and generated prompts — avoid including secrets (API keys, tokens, passwords) in your problem statement or prompts. If you plan to run in Debug mode, expect persistent artifacts (prompts, outputs) on disk; decide whether that data retention is acceptable. Confirm you want the coordinator to refuse direct answers (the skill enforces 'no direct answers') and to always follow the full 5-phase contract before invoking. If you need the coordinator to access credentials for sub-agents, prefer providing them through platform-approved secret mechanisms rather than embedding them in prompts or files.
功能分析
Type: OpenClaw Skill Name: multi-agent-analysis-execution Version: 1.0.4 The skill is a structured orchestration framework for multi-agent workflows, emphasizing a strict five-phase process (Planning, Execution, Output Management, Reporting, and Cleanup). It includes explicit security guardrails in `SKILL.md`, such as prohibiting the inclusion of credentials in generated prompts, enforcing run isolation in timestamped directories, and limiting scanning to the workspace. The 'Mandatory Execution Contract' described in `README.md` and `SKILL.md` uses strong prescriptive language to ensure the agent follows the defined logic rather than skipping steps, which is a standard prompt engineering technique for complex tasks and does not indicate malicious intent.
能力评估
Purpose & Capability
Name/description (multi-agent orchestration) aligns with the SKILL.md and README: both describe planning, spawning agents, sequencing, output management, reporting, and cleanup. The required artifacts and filesystem writes are consistent with an orchestration/coordinator skill.
Instruction Scope
Instructions are focused on orchestration and file-scoped outputs (per-run directories, prompts, outputs, reports). This is within scope, but the skill mandates producing and persisting prompts and outputs (especially in debug mode) and forbids giving direct answers. Persisting prompts may capture user-provided sensitive data if the user includes secrets in the problem statement; the skill does not prescribe sanitization of user inputs.
Install Mechanism
No install spec and no code files — instruction-only. This is the lowest-risk install model and matches the stated behavior.
Credentials
The skill declares no required environment variables or credentials, which matches the registry metadata. The SKILL.md does mention that sub-agents that require credentials should obtain them via ENV or other tools; this is advisory only and not a declared requirement. Users should be cautious about providing secrets in prompts or files created by the coordinator.
Persistence & Privilege
The skill does not request always:true, does not install or modify other skills, and only instructs the coordinator to create per-run directories under a workspace (relative paths only). It requires filesystem writes but does not request elevated or cross-skill privileges.
如何使用
  1. 确保已安装 OpenClaw(本地或 Docker 部署)
  2. 在对话框中输入安装命令:/install multi-agent-analysis-execution
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /multi-agent-analysis-execution 触发
  4. 根据 Skill 的参数说明提供必要输入,即可获得结构化输出
版本历史
v1.0.4
Updated README.md to accurately reflect the content of SKILL.md, providing clear documentation of the five-phase coordinator process, modes (lean/debug), run directory structure, and mandatory execution contract
v1.0.2
Updated README.md to accurately reflect the mandatory execution contract from SKILL.md, removing conflicting two-step approval process and emphasizing that all phases must be executed, all artifacts produced, and no shortcuts allowed
v1.0.1
Updated skill documentation to use relative paths instead of absolute paths, making them workspace-relative as requested
v1.0.0
Initial release of the multi agent analysis execution skill for orchestrating complex multi-agent workflows
元数据
Slug multi-agent-analysis-execution
版本 1.0.4
许可证 MIT-0
累计安装 0
当前安装数 0
历史版本数 4
常见问题

multi agent analysis and execution 是什么?

Orchestrate complex multi-agent workflows with explicit coordinator planning, execution governance, and *automatic output management*. Each skill run creates... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 102 次。

如何安装 multi agent analysis and execution?

在 OpenClaw 或 Claude Code 对话框中运行命令「/install multi-agent-analysis-execution」即可一键安装,无需额外配置。

multi agent analysis and execution 是免费的吗?

是的,multi agent analysis and execution 完全免费,采用 MIT-0 许可证,可自由下载、安装和使用。

multi agent analysis and execution 支持哪些平台?

multi agent analysis and execution 跨平台运行,可在任意部署了 OpenClaw / Claude Code 的环境中使用(cross-platform)。

谁开发了 multi agent analysis and execution?

由 RubenCoppensOnGit(@rubencoppensongit)开发并维护,当前版本 v1.0.4。

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