Update model card

README.md

@@ -1,7 +1,119 @@
 ---
 license: mit
+language:
+- en
+tags:
+- agents
+- llm
+- venture-capital
+- decision-support
+- behavioral-bias
+- typescript
+- react
+- trpc
+- drizzle
 ---
 
-# vc-performance-agent
+# VC Performance Agent
 
-Project files for **vc-performance-agent** by AgenThink.
+VC Performance Agent is a full-stack web application for venture capital decision support. It combines a deal-flow CRM with an LLM-backed "AI Copilot". The Copilot analyzes deals for behavioral biases and red flags, suggests due-diligence questions, and scores founders, alongside a research-insights library, a Monte Carlo portfolio simulator and fund performance metrics (IRR, MOIC, batting average). The target users are VC fund managers, investment teams and fund operations staff.
+
+This is an application codebase, not a trained model. LLM calls go to an external OpenAI-compatible chat-completions endpoint.
+
+**Author:** AgenThink, Kuwait City
+
+> The application lives in the nested folder **[`vc-performance-agent/`](https://huggingface.co/agenthinkmesh/vc-performance-agent/tree/main/vc-performance-agent)**. Its own README is here: [vc-performance-agent/README.md](https://huggingface.co/agenthinkmesh/vc-performance-agent/blob/main/vc-performance-agent/README.md).
+
+---
+
+## Key features
+
+Features as implemented in `server/routers.ts` and `client/src/pages/`:
+
+| Area | What it does |
+|---|---|
+| **Deal flow CRM** | Deals move through a pipeline with statuses Sourced → Meeting → Due Diligence → Term Sheet → Closed / Passed (as coded in the schema and UI). Also covers companies, contacts, an activity timeline and pipeline statistics. |
+| **AI Copilot** | `copilot.analyzeDeal` flags 7 bias types: gambling mentality, ego-driven decisions, network homogeneity, confirmation bias, anchoring, herd mentality, and over-reliance on gut feel. It also flags red flags. `copilot.suggestQuestions` generates due-diligence questions and `copilot.detectPatterns` analyzes patterns across the portfolio. |
+| **Deal evaluation** | `deals.analyzeWithAI` scores deals from 0 to 100 using weighted criteria from the research notes: Team Quality 95%, Business Model 74%, Market Size 68%. |
+| **Founder assessment** | Founder profiles with an LLM-generated 0–100 assessment (`founders.assessWithAI`) covering leadership, domain expertise, track record, team building, execution ability, and vision. |
+| **Research library** | Curated research insights (power law, J-curve, founder assessment, behavioral biases), filterable by category. |
+| **Portfolio simulator** | A server-side Monte Carlo simulation of portfolio outcomes from success rate and return-multiple parameters. |
+| **Performance dashboard** | Fund metrics (IRR, MOIC, batting average) with history. |
+| **Due diligence** | Per-deal checklists. |
+
+---
+
+## Architecture
+
+- **Frontend:** React 19, Tailwind CSS 4, shadcn/ui, wouter routing, tRPC client
+- **Backend:** Express with tRPC. The routers are `auth`, `companies`, `deals`, `founders`, `contacts`, `activities`, `portfolio`, `dueDiligence`, `research`, `simulations`, `performance` and `copilot`.
+- **Database:** MySQL/TiDB via Drizzle ORM. Tables: `users`, `companies`, `deals`, `founders`, `contacts`, `activities`, `portfolio_investments`, `due_diligence_checklists`, `research_insights`, `portfolio_simulations`, `fund_metrics`.
+- **LLM:** `server/_core/llm.ts` calls an OpenAI-compatible `/v1/chat/completions` endpoint with model `gemini-2.5-flash`.
+- **Auth:** OAuth via the Manus platform (session cookie with JWT)
+- **Tests:** Vitest (`server/*.test.ts`)
+
+### Repository structure
+
+| Path | Description |
+|---|---|
+| `VC_PERFORMANCE_AGENT_EXECUTIVE_SUMMARY.md` | Stakeholder overview: features, target users, methodology, roadmap |
+| `vc_research_findings.md` | Research notes on VC returns (power law, the math of VC returns, VC decision-making surveys) |
+| `vc_success_factors.md` | An analysis of the key drivers of venture capital success |
+| `vc-performance-agent/client/` | React frontend. `src/pages/` has Home, Deals, DealDetail, Companies, CompanyDetail, Founders, Portfolio, Performance, Research and Simulator. |
+| `vc-performance-agent/server/` | Express + tRPC backend: `routers.ts`, `db.ts`, `storage.ts`, `_core/` (LLM, OAuth, env, Vite integration) |
+| `vc-performance-agent/drizzle/` | Schema, relations and SQL migrations |
+| `vc-performance-agent/shared/` | Types and constants shared by client and server |
+| `vc-performance-agent/todo.md` | Feature checklist (73 items done, 32 open) |
+
+---
+
+## Getting started
+
+Requirements: Node.js 22+, pnpm, and a MySQL-compatible database.
+
+```bash
+cd vc-performance-agent
+pnpm install
+# create .env with the variables below (the upstream README refers to a .env.example that is not included)
+pnpm db:push        # drizzle-kit generate && drizzle-kit migrate
+pnpm dev            # development server
+```
+
+Other scripts: `pnpm build`, `pnpm start` (production), `pnpm test` (Vitest), `pnpm check` (type-check), `pnpm format`.
+
+Environment variables read by `server/_core/env.ts` (names only):
+`DATABASE_URL`, `JWT_SECRET`, `VITE_APP_ID`, `OAUTH_SERVER_URL`, `OWNER_OPEN_ID`, `BUILT_IN_FORGE_API_URL`, `BUILT_IN_FORGE_API_KEY`.
+
+---
+
+## Results / metrics
+
+The files report no evaluation results for the AI Copilot or the scoring model. The criterion weights (95% / 74% / 68%) come from the research notes. The "80% of VC investments fail" framing is the project's own motivation statement, not a measured outcome of this tool.
+
+---
+
+## Limitations
+
+- **Tied to the Manus platform.** Authentication and the default LLM endpoint depend on Manus OAuth and the Manus "Forge" API, so running elsewhere requires replacing `server/_core/oauth.ts` and `llm.ts`, or pointing them at compatible services.
+- **Referenced files are missing.** The upstream README mentions a `.env.example`, a `seed-research.mjs` seed script, a Dockerfile, and several specification documents (technical spec, dev guide, process flows, flowcharts). None of these are in this repository.
+- **Simplified simulator.** The Monte Carlo simulation is a basic random-draw model and is not calibrated to real fund data.
+- **Unvalidated scores.** Bias detection and scoring are LLM-generated judgments, not validated predictors. Treat them as prompts for discussion, not investment advice.
+- **Unfinished items.** Several items in `todo.md` remain open, among them network analysis, reference-check tracking and industry benchmarking.
+
+---
+
+## License
+
+MIT (see [`vc-performance-agent/LICENSE`](https://huggingface.co/agenthinkmesh/vc-performance-agent/blob/main/vc-performance-agent/LICENSE)).
+
+## Citation
+
+```bibtex
+@software{agenthink2026vcperformance,
+  title        = {VC Performance Agent: AI-Assisted Venture Capital Decision Support},
+  author       = {{AgenThink}},
+  year         = {2026},
+  address      = {Kuwait City, Kuwait},
+  url          = {https://huggingface.co/agenthinkmesh/vc-performance-agent}
+}
+```