cofounder-matching

name	cofounder-matching
version	0.3.0
description	Rubric-based co-founder matching methodology. Scores candidate co-founders against a founder's startup profile using a 6-axis framework (domain fit, skill complementarity, values alignment, equity expectations, time commitment, track record). Produces a ranked shortlist with gap analysis + interview questions per candidate. Works standalone (manual candidate input) — can consume DojoOS candidate pool via dojoos-api-consumer agent when available. Use when the user asks "co-founder matching", "find co-founder", "evaluate candidate", "co-founder fit", "co-founder scoring", "/cofounder-matching". NOT legal or HR advice.

Co-Founder Matching

Evalúa candidatos a co-founder contra un startup profile usando una rubric de 6 ejes. Produce un ranked shortlist + gap analysis + interview questions customizadas por candidato.

⚠️ Disclaimer

Co-founder matching es decisión high-stakes:

• Co-founder equity grants son típicamente 20-50% — irreversible sin término (o clawback tras vesting)
• Co-founder disputes son la razón #1 de failure en early stage startups
• Este skill genera marco de evaluación estructurado, NO sustituye:
  • Working session trial (4-8 semanas de trabajo pre-grant)
  • Legal review del Founder Agreement
  • Background / reference checks profesionales
  • Red flag conversations (visión a 10 años, sacrifice tolerance, exit expectations)

Regla de idioma

Español.

Directorio de salida

./launchpad/{startup-slug}/cofounder-matching/
├── rubric.md                           # Rubric personalizada para esta startup
├── candidate-[name]/
│   ├── scorecard.md                    # 6-axis scorecard con evidencia
│   ├── gap-analysis.md                 # Qué falta vs ideal candidate
│   └── interview-questions.md          # Preguntas customizadas para este candidato
└── shortlist.md                        # Ranked list + recommendation

---

La rubric — 6 ejes de evaluación

1. Domain fit

¿El candidato entiende el mercado objetivo?

Score 1-5:

• 5: Operador/builder en el vertical con >5 años + network relevante
• 4: Usuario profundo del problema + research extensa del mercado
• 3: Familiar con el mercado pero sin operator experience
• 2: Conoce el mercado desde afuera (consumidor casual, articles)
• 1: Sin conocimiento relevante del dominio

2. Skill complementarity

¿Las skills del candidato llenan gaps del founder existente?

Mapear a los 3 roles archetype de Y Combinator:

• Hacker (builds the product)
• Hustler (sells and markets)
• Designer (designs the experience)

Score 1-5:

• 5: Cubre completamente un gap crítico + es world-class en eso
• 4: Cubre un gap + tiene competencia sólida
• 3: Cubre parcialmente un gap existente
• 2: Duplica skills existentes (overlapping, not complementary)
• 1: No aporta skills relevantes al stage actual

3. Values alignment

¿Comparten los valores clave para esta venture?

5 valores standard a evaluar:

• Ambition (growth-oriented vs. lifestyle)
• Risk tolerance (VC path vs. bootstrap)
• Time horizon (10-year commitment vs. 3-year exit)
• Ethics (how they've handled moral edge cases pre)
• Impact (profit alone vs. impact + profit)

Score 1-5:

• 5: Explícitamente alineado en los 5 valores con evidencia
• 4: Alineado en 4/5, el 5° es aceptable divergence
• 3: Alineado en 3/5, 2 divergencias require explícit conversation
• 2: Divergente en ≥3 valores — red flag
• 1: Misalignment fundamental que predicto breakdown

4. Equity expectations

¿El candidato espera un equity split compatible con el stage + contribution?

Score 1-5:

• 5: Expectativa razonable (10-50% dependiendo stage) + flexible + firma vesting 4yr/1yr cliff sin fricción
• 4: Razonable pero negotiations on terms (acceleration, cliff variation)
• 3: Expectativa alta pero negociable con clarification
• 2: Expectativa inflada (e.g., 50% joining at Seed post-MVP)
• 1: Unreasonable — demand sin justificación o sin aceptar vesting

5. Time commitment

¿Fulltime es realista para este candidato?

Score 1-5:

• 5: Available full-time desde día 1, financial runway personal ≥12 meses
• 4: Full-time en ≤30 días + financial runway ≥6 meses
• 3: 80%+ committed con day-job por ≤3 meses transition
• 2: Part-time indefinido (>50%) — risky pero manageable para stage
• 1: Part-time <30% o indefinido — usualmente red flag para founder

6. Track record + execution evidence

¿Qué ha shipped / construido / logrado el candidato antes?

Score 1-5:

• 5: Exit previo o role senior en exitosa startup + refs strong
• 4: Built/shipped product con traction cuantificable + refs positivos
• 3: Builds independientes con evidence (GitHub, Dribbble, case studies)
• 2: Training/certification sin ship evidence
• 1: Puro CV sin evidence de ship capability

---

Weighted scoring

Los ejes NO pesan igual — el peso depende del stage de la startup:

Eje	Ideation	MVP	Traction	Funded+
Domain fit	20%	15%	25%	30%
Skill complementarity	30%	35%	25%	20%
Values alignment	25%	20%	15%	15%
Equity expectations	10%	10%	15%	15%
Time commitment	10%	15%	10%	10%
Track record	5%	5%	10%	10%

Rationale: early stage prioriza skill complementarity + values (team gelling); later stage prioriza domain fit + proven execution.

---

Flujo del skill

Paso 1 — Load startup context

CM-1: "Vamos a evaluar co-founder candidates contra tu startup. Primero necesito el context:

1. ¿Tenés startup-profile.md generado por startup-intake? Si sí, lo leo.
2. ¿Cuál es el stage actual? (Ideation / Formation / MVP / Traction / Funded / Scaling)
3. ¿Qué gaps de skills tenés explícitos? (CEO + falta CTO, o tenés CEO+CTO y te falta CMO, etc.)
4. ¿Qué equity range estás considerando ofrecer? (típico 20-50% dependiendo contribution pre-existente)"

Paso 2 — Generate rubric personalizada

CM-2: Generar rubric.md con weights ajustados al stage, y hacerlo visible al usuario para que vea los criterios antes de evaluar candidates.

Paso 3 — Collect candidates

CM-3: "¿Cuántos candidates querés evaluar?

Para cada candidate, necesito:

• Nombre + contacto (LinkedIn URL ideal)
• Cómo los conociste
• Domain expertise claim (self-described + evidencia)
• Skills claim
• Time commitment expectation
• Equity expectation (o rango)
• Track record: 2-3 highlights verificables

Si tenés DojoOS API habilitada (via dojoos-api-consumer agent), puedo pull candidates from your co-founder matching queue directly. Si no, proceedemos con manual input."

Paso 4 — Score cada candidate

CM-4: Para cada candidate, generar scorecard.md con:

• Score por eje (1-5 con evidencia citada)
• Weighted total score
• Relative ranking vs otros candidates
• Key strengths
• Key concerns
• Kill-switch flags: criterios que si fallan, desqualify regardless de total score (ej. values misalignment severo, equity expectation outrageous, concurrent commitment a competitor venture)

Paso 5 — Gap analysis

CM-5: Generar gap-analysis.md por candidate:

• Qué axis están under-scored
• Can gaps be closed pre-grant? (training, trial period, advisor bridge)
• Can gaps be tolerable post-grant? (rare — usually breaks later)
• Compare candidate profile to "ideal candidate" for this stage

Paso 6 — Interview questions

CM-6: Generar interview-questions.md customizado por candidate:

• 5-8 preguntas targeted a sus weakest axes
• 2-3 preguntas de values exploration (hipotéticos concretos: "Si el lead VC te pidiera firing de un early employee antes de Series A, ¿cómo responderías?")
• 1-2 red flag probes (ej. "Contame de un conflict con un co-founder o partner pasado y cómo se resolvió")
• Reference check questions para terceros (ex-managers, ex-co-founders)

Paso 7 — Shortlist + recommendation

CM-7: Generar shortlist.md:

• Ranked list por weighted score
• Top recommendation con rationale
• Runner-up con rationale
• "Avoid" list con explicit red flags
• Next steps recommended:
  • Trial period before grant (4-8 weeks paid engagement)
  • Reference checks (3+ independent)
  • Founder Agreement + Vesting (via founder-documents skill)
  • Shared equity milestones (e.g., grant 5% immediately, rest after 3-month trial validated)

---

Output template — scorecard.md

# Candidate Scorecard — [Candidate Name]

**Startup**: [Startup Name]
**Evaluator**: [Founder Name]
**Date**: YYYY-MM-DD
**Stage weighting**: [Ideation / MVP / Traction / Funded]

---

## Overview

- **Contact**: [LinkedIn / email]
- **How we met**: [context]
- **Time commitment claim**: [full-time / part-time X%]
- **Equity expectation**: [X% range or specific]

---

## Score by axis (1-5 with evidence)

### 1. Domain fit — Score: X/5 (weight XX%)

**Evidence**:
- [Specific observation, quote, or claim]
- [Another evidence]

**Analysis**: [why this score, not higher/lower]

### 2. Skill complementarity — Score: X/5 (weight XX%)

[same format]

### 3. Values alignment — Score: X/5 (weight XX%)

[Evaluate each of the 5 standard values with specific observations]

### 4. Equity expectations — Score: X/5 (weight XX%)

### 5. Time commitment — Score: X/5 (weight XX%)

### 6. Track record — Score: X/5 (weight XX%)

---

## Weighted total

| Axis | Score (1-5) | Weight | Weighted |
|---|---|---|---|
| Domain fit | X | XX% | X.XX |
| Skill complementarity | X | XX% | X.XX |
| Values alignment | X | XX% | X.XX |
| Equity expectations | X | XX% | X.XX |
| Time commitment | X | XX% | X.XX |
| Track record | X | XX% | X.XX |
| **TOTAL** | — | **100%** | **X.XX / 5** |

---

## Kill-switch flags

- [ ] Values severe misalignment? Y/N
- [ ] Equity demand unreasonable / no vesting? Y/N
- [ ] Concurrent commitment to competitor? Y/N
- [ ] Failed reference check? Y/N
- [ ] IP conflict / non-compete issue? Y/N

If ANY kill-switch → **DISQUALIFY regardless of score**.

---

## Summary

**Strengths**:
- [Top 3]

**Concerns**:
- [Top 3]

**Recommendation**: [Progress to interview / Trial period / Pass]

**Next step**: [specific action with timeline]

---

Integración con DojoOS (via dojoos-api-consumer agent)

Disponible desde v0.5.0 — el agent dojoos-api-consumer (ver agents/dojoos-api-consumer.md) es invocable desde este skill en el Paso 3 (collect candidates) pidiendo la operación list_candidate_pool. Hoy esa operación retorna SPEC_GAP (el endpoint no está en la OpenAPI spec todavía) y el skill procede con manual candidate input — como siempre. Cuando @william + @garbanzo expongan el endpoint en DojoOS, el agente comenzará a retornar LIVE_DATA automáticamente sin cambios en este skill: candidate pool + Dojo Score embebido se inyectan al rubric 6-axis. Mismo patrón para push de scorecards de vuelta via sync_candidate_scorecard (también SPEC_GAP hoy).

Integración con otras skills

• startup-intake: source de startup-profile.md para stage + gaps context
• cap-table-builder: post-matching, el co-founder grant se ejecuta vía este skill
• founder-documents: Founder Stock Purchase Agreement + IP Assignment + Vesting Exhibit
• feature-to-spike: si durante matching se descubre pattern útil para DojoOS (ej. "weighted scoring ajustado por stage es mejor que pesos fijos"), generar SPIKE

Principios clave

• Kill-switches override score: nunca avanzar si hay values misalignment fundamental
• Trial period obligatorio antes de grant completo: 4-8 semanas paid + milestone-based equity release
• Reference checks siempre: mínimo 3 ex-colleagues o ex-partners (NO solo los que el candidate eligió)
• Weighted scoring ajustado por stage: pesos no son fijos, dependen del momento de la venture
• Documentación como audit trail: cada scorecard referencable ante future founder disputes

Anti-patterns

• Grant de equity sin vesting porque "confiamos" → red flag VC + future dispute risk
• Skipping reference checks porque the candidate es amigo de un amigo
• Over-weighting de domain fit en Ideation stage (se aprende; skill complementarity pesa más temprano)
• Ignorar kill-switches "porque el candidate es excepcional en otros ejes"
• Una sola session de evaluación (no trial period)

Recursos

• Y Combinator Co-Founder Matching (ycombinator.com/cofounder-matching)
• Paul Graham — "The 18 Mistakes That Kill Startups" — #1 is single founder
• First Round Review — Co-Founder Guide
• "The Founder's Dilemmas" (Noam Wasserman, Princeton 2012) — research sobre founder splits
• Reference check framework: 3×3 (3 refs, 3 questions each: values, skills, conflict resolution)