agentleFS
latour-ailatour-ai/skills/tear-sheet-private-co/SKILL.md

tear-sheet-private-co

Skill69 starsChanged 26 days agoNo licenceView on GitHub

Generate investor-grade tear sheets on venture-backed private companies. Produces a structured, sourced markdown brief covering company snapshot, business model, funding history, operating metrics, management, competitive landscape, and investor perspective. Use this skill whenever the user asks for a "tear sheet," "company overview," "company profile," "investor brief," "due diligence summary," "company research," "private company analysis," "investment memo," or says things like "pull up a tear sheet on [company]," "research [company] for me," "what do we know about [company]," "give me the rundown on [company]," "prep a company overview," or "diligence [company]." Also trigger when the user names a specific startup or venture-backed company and asks for a summary, profile, or overview in an investment context. Do NOT use for public-company equity research (10-K analysis, DCF models) or for simple news lookups — this is for structured private-company tear sheets.

The file

We split this skill into the rules it gives an agent

6 rules. About 0 are common, 6 are distinctive, and 0 are very specific to this project.

  • ≈0

    Common · estimate

    Many files like this have a rule of this kind.

  • ≈6

    Distinctive · estimate

    This author's own choices. Worth a look.

  • 0

    Very specific

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

No licence file, so all rights are reserved — read it at the source. We count its rules but don't quote them. Read them on GitHub.

≈ “Common” is an estimate: at least 1 in 5 of the 350,495 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.

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.