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felt cute uploaded skill

作者 flip-in · GitHub ↗ · v1.0.0 · MIT-0
cross-platform ✓ 安全检测通过
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在 OpenClaw 中安装
/install test-research-delete
功能描述
Orchestrate parallel codebase research. Spawns multiple researcher subagents to investigate different areas, then synthesizes findings into research.md.
使用说明 (SKILL.md)

Research Orchestration

Methodology for systematic codebase research using parallel subagents.

Purpose

This skill runs on the main thread and orchestrates multiple researcher subagents to investigate a codebase in parallel. Produces a research.md file for downstream planning.

Mandate: Document the codebase as it exists today. No improvements, no critique, no suggested changes—pure technical mapping.

Workflow

Step 1: Capture the Research Question

Record the exact research question from $ARGUMENTS.

If no arguments provided, ask the user for their research question before proceeding.

Step 2: Read Referenced Files First

If the user mentions specific files, read them completely before spawning agents. Use Read tool without limit/offset.

Step 3: Decompose into Investigation Areas

Break the research question into 3-5 distinct investigation areas. For each define:

  • Search targets - patterns, keywords, file types
  • Search locations - directories, file patterns
  • Questions to answer - what we need to learn

Step 4: Spawn Parallel Researcher Subagents

Use the Task tool to spawn multiple researcher subagents in parallel. Each investigates one area.

Critical: Send ALL Task tool calls in a SINGLE message to run them in parallel.

Task tool calls (all in one message):
- subagent_type: "researcher"
- prompt: "Investigate [area]. Search targets: [targets]. Search locations: [locations]. Questions: [questions]"
- description: "Research [area name]"

Example parallel spawn:

[Task 1] subagent_type: researcher
         prompt: "Investigate authentication middleware and guards.
                  Search targets: auth, jwt, session, middleware, guard patterns
                  Search locations: src/, lib/
                  Questions: Where is auth middleware defined? How are routes protected? What token format is used?"

[Task 2] subagent_type: researcher
         prompt: "Investigate user model and storage.
                  Search targets: User, schema, model, database, repository patterns
                  Search locations: src/, models/, db/
                  Questions: Where is the User model? What ORM/database is used? What fields exist?"

[Task 3] subagent_type: researcher
         prompt: "Investigate login/logout flows.
                  Search targets: login, logout, signin, signout, authenticate patterns
                  Search locations: src/, routes/, controllers/
                  Questions: What is the login endpoint? How are sessions created/destroyed?"

Step 5: Collect Results

Wait for all researcher subagents to complete. Each returns:

  • Key files with file:line references
  • How the mechanism works
  • Answers to the questions posed
  • Notable details and gaps

Step 6: Gather Metadata

Run git commands to collect:

git rev-parse --short HEAD    # commit hash
git branch --show-current     # branch name
git remote get-url origin     # repository URL

Step 7: Synthesize and Write research.md

Combine all subagent findings into a single research.md file in the current working directory.

Required format:

---
date: YYYY-MM-DD
commit: \x3Cshort-hash>
branch: \x3Cbranch-name>
repository: \x3Crepo-name>
topic: \x3Cresearch-topic>
status: complete
---

# Research: \x3CTopic>

## Research Question

\x3COriginal question from user>

## Summary

\x3C2-3 sentence executive summary of findings>

## Detailed Findings

### \x3CArea 1>

\x3CSynthesized findings with specific file:line references>

### \x3CArea 2>

\x3CSynthesized findings with specific file:line references>

...

## Code References

Key files and their purposes:

- `path/to/file.ts:123` - \x3Cdescription>
- `path/to/other.ts:45-67` - \x3Cdescription>

## Architecture Insights

\x3CHow components connect, data flow, key abstractions>

## Open Questions

- \x3CUnresolved question 1>
- \x3CUnresolved question 2>

Step 8: Report Completion

After writing, report:

  1. Location of research.md
  2. Summary of key findings (2-3 sentences)
  3. List of open questions

Output Requirements

  • Always produce research.md - even partial findings are valuable
  • Use file:line references - enable navigation: src/api/handler.ts:42
  • Document what exists - not what should exist
  • Note gaps - unclear items go to Open Questions

Example Decompositions

"How does authentication work?"

Investigation areas (spawn 5 researcher subagents):

  1. Auth middleware and guards
  2. Token/session management
  3. User model and storage
  4. Login/logout flows
  5. Permission checking

"Research the database layer"

Investigation areas (spawn 5 researcher subagents):

  1. ORM/query builder setup
  2. Schema definitions
  3. Migration system
  4. Connection management
  5. Query patterns
安全使用建议
This skill appears to do exactly what it says: read repository files, spawn parallel researcher subagents via the platform Task tool, run a few git commands, and write research.md. Before installing, confirm you are comfortable with the agent reading the repository in bulk (the instructions explicitly permit unlimited reads) and ensure $ARGUMENTS maps only to the user-supplied research question. If you want tighter controls, ask for limits on which directories can be read or require explicit confirmation before scanning large paths.
功能分析
Type: OpenClaw Skill Name: test-research-delete Version: 1.0.0 The skill is designed to automate codebase research by spawning parallel subagents and synthesizing findings into a 'research.md' file. It uses standard git commands in SKILL.md to collect repository metadata (commit hash, branch, and origin URL) for documentation purposes, which is consistent with its stated goal of technical mapping. No evidence of data exfiltration, malicious execution, or prompt injection was found.
能力评估
Purpose & Capability
The name/description (orchestrating parallel codebase research) matches the instructions: decomposing a question, spawning researcher subagents, collecting results, and writing research.md. There are no unexpected binaries, env vars, or config paths requested.
Instruction Scope
SKILL.md instructs the agent to read user-specified files (and to use the Read tool without limit/offset) and to spawn Task tool subagents (all calls in a single message). Reading repository files and running git commands is expected for this purpose, but 'use Read tool without limit/offset' could lead to large/unbounded reads of repository content — this is functionally necessary for deep research but is broader than a single-file lookup. Also the document references $ARGUMENTS (platform placeholder) — ensure this maps only to the user-provided question.
Install Mechanism
Instruction-only skill with no install steps, no external downloads, and no code files. This is low risk and consistent with the stated behavior.
Credentials
The skill declares no required environment variables, credentials, or config paths. The only external actions are calls to platform tools (Read, Task) and local git commands, which are proportional to repository research.
Persistence & Privilege
always:false and no special persistence or cross-skill configuration changes requested. Autonomous invocation is allowed (platform default) but not combined with other privilege escalations.
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 test-research-delete
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /test-research-delete 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
v1.0.0
Initial release of the research orchestration skill. - Orchestrates parallel research tasks across codebases using multiple subagents. - Produces a comprehensive research.md that documents technical findings without critique or suggestions. - Decomposes user research questions into 3–5 investigation areas, each investigated in parallel. - Synthesizes subagent results, git metadata, and open questions into a structured markdown report. - Ensures research.md always includes file:line references and explicitly notes any knowledge gaps.
元数据
Slug test-research-delete
版本 1.0.0
许可证 MIT-0
累计安装 0
当前安装数 0
历史版本数 1
常见问题

felt cute uploaded skill 是什么?

Orchestrate parallel codebase research. Spawns multiple researcher subagents to investigate different areas, then synthesizes findings into research.md. 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 76 次。

如何安装 felt cute uploaded skill?

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

felt cute uploaded skill 是免费的吗?

是的,felt cute uploaded skill 完全免费,采用 MIT-0 许可证,可自由下载、安装和使用。

felt cute uploaded skill 支持哪些平台?

felt cute uploaded skill 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 felt cute uploaded skill?

由 flip-in(@flip-in)开发并维护,当前版本 v1.0.0。

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