felt cute uploaded skill

v1.0.0

Orchestrate parallel codebase research. Spawns multiple researcher subagents to investigate different areas, then synthesizes findings into research.md.

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Best for remote or guided setup. Copy the exact prompt, then paste it into OpenClaw for flip-in/test-research-delete.

Previewing Install & Setup.
Prompt PreviewInstall & Setup
Install the skill "felt cute uploaded skill" (flip-in/test-research-delete) from ClawHub.
Skill page: https://clawhub.ai/flip-in/test-research-delete
Keep the work scoped to this skill only.
After install, inspect the skill metadata and help me finish setup.
Use only the metadata you can verify from ClawHub; do not invent missing requirements.
Ask before making any broader environment changes.

Command Line

CLI Commands

Use the direct CLI path if you want to install manually and keep every step visible.

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openclaw skills install test-research-delete

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npx clawhub@latest install test-research-delete
Security Scan
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high confidence
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.
Assessment
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.

Like a lobster shell, security has layers — review code before you run it.

latestvk970q8hqzf338348tc754vgf7184vpmj
79downloads
0stars
1versions
Updated 1w ago
v1.0.0
MIT-0

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: <short-hash>
branch: <branch-name>
repository: <repo-name>
topic: <research-topic>
status: complete
---

# Research: <Topic>

## Research Question

<Original question from user>

## Summary

<2-3 sentence executive summary of findings>

## Detailed Findings

### <Area 1>

<Synthesized findings with specific file:line references>

### <Area 2>

<Synthesized findings with specific file:line references>

...

## Code References

Key files and their purposes:

- `path/to/file.ts:123` - <description>
- `path/to/other.ts:45-67` - <description>

## Architecture Insights

<How components connect, data flow, key abstractions>

## Open Questions

- <Unresolved question 1>
- <Unresolved 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

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