agentleFS
B-M-Capital-ResearchB-M-Capital-Research/honeclaw/skills/deep_stock_research/SKILL.md

Deep Stock Research

Skill748 starsChanged 3 months agoMITView on GitHub

Admin-only skill for launching deep research on a specific company for about 1-2 hours while reporting progress every minute

We split this skill into the rules it gives an agent

3 rules. About 0 are common, 3 are distinctive, and 0 are very specific to this project.

  • ≈0

    Common · estimate

    Many files like this have a rule of this kind.

  • ≈3

    Distinctive · estimate

    This author's own choices. Worth a look.

  • 0

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Distinctive:

    After the tool succeeds, tell the user in natural language:

    line 46
  2. Distinctive:

    If the tool returns an error, tell the user that startup failed and include the error message

    line 60
  3. Distinctive:

    If the user has no admin permission, politely refuse: "Sorry, the deep stock research feature is currently available to administrators …

    line 61

≈ “Common” is an estimate: at least 1 in 5 of the 308,232 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

Deep Stock Research (OWDR - One-Way Deep Research)

Security note: This skill is available to administrators only. If a non-admin user tries to trigger it, politely refuse without explaining internal details.

Trigger

Users can trigger this skill in any of the following ways:

  • OWDR, nvidia
  • OWDR, NVIDIA
  • Deep stock research NVIDIA
  • Deep research BYD
  • Help me deeply research AAPL

The company name may be Chinese, English, or a ticker; pass it through directly to the research API.

Workflow

Step 1 - Extract the company name

Extract the company name from the user input. If it is unclear, ask for confirmation first.

Step 2 - Start the research

Call the tool:

deep_research(company_name="<extracted company name>")

Step 3 - Inform the user

After the tool succeeds, tell the user in natural language:

  • The deep research for <company> has started successfully
  • The system will report progress once per minute, up to 15 minutes
  • The full report is expected in 1-2 hours and can be viewed later on the "Stock Research" page

Example reply:

The deep research for NVIDIA has started successfully! Task ID: <task_id> The system will report progress once per minute for up to 15 minutes. The full report should be ready in about 1-2 hours and can be reviewed on the "Stock Research" page.

Error Handling

  • If the tool returns an error, tell the user that startup failed and include the error message
  • If the user has no admin permission, politely refuse: "Sorry, the deep stock research feature is currently available to administrators only."

Download now (ZIP)

Does it work?

Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.

No reviews yet

People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.

  • It worked
  • Partly
  • It didn't
What did you use it for? e.g. Reviewing pull requests in a Rails app

Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.

Your trail

Files you open will collect here, so you can find them again.

Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.

Now do this for your own.

Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.