Agent Skills › win4r/MuseAI-Skills › wide_research

wide_research

GitHub

用于协调子智能体并行执行大量独立研究任务,通过统一输入输出模式实现批量数据收集与结构化汇总。

opt/hatch/skills/wide-research/SKILL.md win4r/MuseAI-Skills

Trigger Scenarios

用户需要针对多个独立对象进行大规模并行调研 请求宽泛或并行的信息检索与筛查任务

Install

npx skills add win4r/MuseAI-Skills --skill wide_research -g -y
More Options

Non-standard path

npx skills add https://github.com/win4r/MuseAI-Skills/tree/main/opt/hatch/skills/wide-research -g -y

Use without installing

npx skills use win4r/MuseAI-Skills@wide_research

指定 Agent (Claude Code)

npx skills add win4r/MuseAI-Skills --skill wide_research -a claude-code -g -y

安装 repo 全部 skill

npx skills add win4r/MuseAI-Skills --all -g -y

预览 repo 内 skill

npx skills add win4r/MuseAI-Skills --list

SKILL.md

Frontmatter
{
    "name": "wide_research",
    "metadata": {
        "includeInPrompt": false
    },
    "description": "Use when the user needs broad parallel research across many independent inputs with a shared output schema."
}

Wide Research

Purpose

Coordinate one manager subagent that fans out the same research task across many independent inputs and returns a single normalized result set.

When to Use

  • The task can be split into many independent subtasks (for example, one company/person/topic per input).
  • Each subtask should return the same structured fields.
  • The user asks for "wide research", "parallel research", or high-volume lookup/screening.

Do not use this workflow for single-item tasks or when subtasks depend on each other.

Tooling

Use exactly one manager subagent for the overall operation.

Manager input contract:

  • operation_brief: one concise sentence.
  • inputs: one independent item per element.
  • output_schema: required fields and allowed types.
  • worker_prompt_template: per-input instructions.
  • completion_format: exact JSON object shape for the manager's final response.

Manager output contract:

  • total
  • success_count
  • failure_count
  • results
  • failures
  • notes

Operating Rules

  1. Deduplicate and normalize the input list before spawning the manager.
  2. Keep the output schema minimal and explicit; avoid optional or free-form fields unless the user asked for them.
  3. Use one manager coordinator for one user goal; do not fan out multiple sibling root-level subagents.
  4. Instruct the manager to assign one worker per input and keep each worker scoped to its own item.
  5. If completeness matters and some inputs fail, retry only the failed inputs, once, when feasible.
  6. Reply to the user immediately that wide research has started; do not block on completion.
  7. In the final user-facing output, always report coverage (success_count/total) and unresolved gaps.

Version History

  • 38bbb45 Current 2026-10-18 15:49

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Metadata

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Version
38bbb45
Hash
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Indexed
2026-10-18 15:49

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