llmquant-investor-lenses
Router skill for LLMQuant investor-lens workflows. Use when the user wants an investor-style reasoning overlay grounded in LLMQuant Data evidence.
npx skills add LLMQuant/skills --skill llmquant-investor-lenses --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# LLMQuant Investor Lenses This category routes investor-style reasoning overlays. The named workflows are analytical lenses, not claims of endorsement or replication. All external evidence must come from LLMQuant Data. ## Routing Rules 1. Identify the requested investor lens, ticker/asset, horizon, and decision type. 2. Select the closest workflow below. 3. Open only that workflow and any local resources explicitly referenced by that workflow. 4. Use LLMQuant Data for filings, prices, fundamentals, ownership, macro, and valuation evidence. 5. Separate evidence from interpretation and avoid unsupported persona claims. ## Workflow Index | User intent | Workflow | |---|---| | Long-term owner lens: moat, circle of competence, and margin of safety. | [`workflows/warren-buffett.md`](workflows/warren-buffett.md) | | Quantitative value and margin-of-safety discipline. | [`workflows/ben-graham.md`](workflows/ben-graham.md) | | Multi-model quality investor with inversion discipline. | [`workflows/charlie-munger.md`](workflows/charlie-munger.md) | | Dhandho, cloning, and low-risk doubles. | [`workflows/mohnish-pabrai.md`](workflows/mohnish-pabrai.md) | | Emerging-market compounder and ROE-fi
- Routing Rules
- Workflow Index
- LLMQuant Data Contract
What does the llmquant-investor-lenses skill do?
Router skill for LLMQuant investor-lens workflows. Use when the user wants an investor-style reasoning overlay grounded in LLMQuant Data evidence.
How do I install it?
Run `npx skills add LLMQuant/skills --skill llmquant-investor-lenses --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From LLMQuant/skills, a repository with 183 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.