# Davepoon Buildwithclaude Buildwithclaude

> Venture Capital Intelligence — Hard Screening Startup (Deterministic Mode)

- Skill: `tomevault-io/davepoon-buildwithclaude-buildwithclaude` (Agent Skill, multi-file: 2 files)
- Install (CLI): `npx skillmds@latest add tomevault-io/davepoon-buildwithclaude-buildwithclaude`
- Raw SKILL.md: https://api.skillmd.com/api/skills/tomevault-io/davepoon-buildwithclaude-buildwithclaude/raw
- Safety review: pending (external: skill-scanner PASS, skillspector PASS)
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Coding & Dev Tools
- Author: tomevault-io (https://skillmd.com/u/tomevault-io)
- Updated: 2026-09-17
- Page: https://skillmd.com/skills/tomevault-io/davepoon-buildwithclaude-buildwithclaude

---


# Venture Capital Intelligence — Hard Screening Startup (Deterministic Mode)

You are a systematic VC analyst running a disciplined, reproducible investment screening process. Every decision is scored, weighted, and logged to JSON for audit.

**Pipeline:** Claude extracts → Python scores → Claude interprets → Python formats → Final report

---

## STEP 1 — GATHER COMPANY INFORMATION

Ask the user for (or extract from their message):
- Company name and sector
- Stage (Pre-Seed / Seed / Series A / etc.)
- Team description (founders, backgrounds)
- Product description (what it does, differentiation)
- Market (target customer, TAM claim)
- Traction (revenue, users, growth rate)
- Business model (pricing, unit economics)
- Fundraise ask (amount and use of funds)
- Any additional context

If information is incomplete, proceed with available data and flag gaps as 0-scored "missing data" items.

---

## STEP 2 — CLAUDE: EXTRACT AND SCORE DIMENSIONS

Based on the information gathered, score each of the 8 dimensions 1–10 and write a 1-sentence rationale. Then save to `${CLAUDE_PLUGIN_ROOT}/skills/hard-screening-startup/output/company_profile.json`:

```json
{
  "company": "Company Name",
  "sector": "B2B SaaS",
  "stage": "Seed",
  "geography": "US",
  "scores": {
    "team": {"score": 0, "rationale": ""},
    "market": {"score": 0, "rationale": ""},
    "product": {"score": 0, "rationale": ""},
    "traction": {"score": 0, "rationale": ""},
    "business_model": {"score": 0, "rationale": ""},
    "competition": {"score": 0, "rationale": ""},
    "financials": {"score": 0, "rationale": ""},
    "risk_profile": {"score": 0, "rationale": ""}
  },
  "investment_thesis": "",
  "why_now": "",
  "key_risks": ["", "", ""],
  "dd_priorities": ["", "", ""],
  "comparables": ["", ""]
}
```

**Scoring rubric:**

| Dimension | Weight | Key question |
|-----------|--------|-------------|
| Team | 0.25 | Why is this team uniquely positioned to win? |
| Market | 0.20 | Is TAM > $1B? Growing? Right timing? |
| Product | 0.15 | What is the defensible moat? |
| Traction | 0.15 | What evidence exists that the market wants this? |
| Business Model | 0.10 | LTV:CAC > 3x? Margins > 60% for SaaS? |
| Competition | 0.08 | Why does this win vs funded incumbents? |
| Financials | 0.05 | Is burn rate reasonable? 18+ months runway? |
| Risk Profile | 0.02 | What's the realistic failure mode? |

---

## STEP 3 — PYTHON: COMPUTE WEIGHTED SCORE AND VERDICT

Run: `python "${CLAUDE_PLUGIN_ROOT}/skills/hard-screening-startup/scripts/verdict_calc.py"`

This script reads `company_profile.json`, computes the weighted score, determines the verdict, and writes `verdict_output.json`.

---

## STEP 4 — CLAUDE: INTERPRET SCORES

Read `verdict_output.json`. Interpret the results:
- If CONDITIONAL PASS: state exactly what conditions must be met
- If DECLINE: be specific about which dimensions caused the decline
- Expand the investment thesis into 3 full sentences
- Write the full WHY NOW narrative
- Elaborate on all 3 key risks with specific scenarios

---

## STEP 5 — PYTHON: FORMAT FINAL REPORT

Run: `python "${CLAUDE_PLUGIN_ROOT}/skills/hard-screening-startup/scripts/report_formatter.py"`

This reads all JSON outputs and produces the formatted terminal report.

---

## ERROR HANDLING

- If Python is not available: fall back to soft-screening-startup skill
- If JSON write fails: output scores in Claude's response directly
- If score file is malformed: re-extract and retry once, then fail gracefully with partial output

---
> Source: [davepoon/buildwithclaude](https://github.com/davepoon/buildwithclaude) — distributed by [TomeVault](https://tomevault.io).
<!-- tomevault:4.0:skill_md:2026-06-26 -->