Investor Matching

Investor Matching

Evalúa candidatos a investor (VCs, angels, family offices, CVCs) contra un startup profile con un framework de 5 ejes. Produce target list ranked + outreach customizado.

⚠️ Disclaimer

• Fundraising tiene regulatory + tax implications en cada jurisdicción (securities law, accreditation requirements, tax treatment)
• Este skill genera investor research structured, NO sustituye:
  • Securities lawyer (Reg D filing, Blue Sky compliance, cross-border)
  • Tax advisor (QSBS timing, Section 1202 tracking)
  • Professional fundraising coach o advisor con track record
• Nunca enviar outreach sin review legal de los materials (deck + data room + term sheet draft)

Regla de idioma

Español.

Directorio de salida

./launchpad/{startup-slug}/investor-matching/
├── target-criteria.md                  # Qué perfil de investor buscamos
├── investor-[name]/
│   ├── fit-scorecard.md                # 5-axis scorecard con evidencia
│   ├── outreach-template.md            # Customized email + LinkedIn
│   └── intelligence-notes.md           # Check history, portfolio fit, known biases
├── target-list.md                      # Ranked list + outreach sequence plan
└── tracker.md                          # Pipeline status per investor (emailed, responded, meeting, etc.)

Los 5 ejes de evaluación

1. Stage fit

¿El investor escribe checks en el stage actual de la startup?

Score 1-5:

• 5: Primary focus es tu stage + >50% de portfolio en este stage
• 4: Active en tu stage + invierte en adjacent stages
• 3: Invierte ocasionalmente en tu stage, más focused en adjacent
• 2: Solo invierte ocasionalmente en tu stage (outlier checks)
• 1: Nunca invierte en tu stage

Data source: Crunchbase, PitchBook, investor's "About" page, recent check announcements.

2. Check size fit

¿El check size típico del investor coincide con el amount que estás raising?

Score 1-5:

• 5: Tu round size = median check size del investor (ideal lead)
• 4: Tu round = 50-80% of median o 120-150% (co-lead o primary)
• 3: Tu round = 30-50% o 150-200% (follower check or stretch)
• 2: Tu round = 10-30% o >200% (unlikely to engage)
• 1: Rounds outside their mandate entirely

Formula:

• Median investor check = typical size from recent portfolio announcements
• Target ownership = check size / post-money valuation (most VCs target 10-20%)

3. Thesis alignment

¿El problema que resuelve tu startup cabe en la thesis del investor?

Score 1-5:

• 5: Tu startup es explicitly mentioned en su public thesis
• 4: Thesis cubre el espacio + portfolio has 2+ similar ventures (positive signal)
• 3: Thesis cubre el espacio pero no hay portfolio proof
• 2: Thesis adjacent pero NOT primary focus
• 1: Thesis distinct o incompatible

Data source: Investor's blog posts, Twitter, podcasts interviews, portfolio list, published thesis docs.

Red flags:

• Investor has already invested in direct competitor (usually a pass due to portfolio conflict)
• Thesis has shifted recently (old deals don't reflect current focus)

4. Geography / vertical overlap

¿El investor opera en tu región + vertical?

Score 1-5:

• 5: Primary geography + primary vertical — deep rolodex en ambos
• 4: Primary geography OR vertical strongly, pero not both
• 3: Covers both pero not primary
• 2: Covers one secondarily, not primary
• 1: Outside their active operating zone

LATAM-specific scoring:

• Latitud, KaszeK, Monashees, Endeavor: primary LATAM focus
• GV, SoftBank, Sequoia: LATAM via specific local partners
• Most US funds: LATAM only via Delaware/Cayman wrapped entities (see venture-studio-toolkit:structure-decision)

5. Value-add depth

¿Qué aporta el investor más allá del capital?

Score 1-5:

• 5: Hands-on operating partner experience + active engagement (2-3 operator platforms per portfolio company)
• 4: Strategic advisor access + warm intros + domain expertise
• 3: Warm intros + occasional strategic guidance
• 2: Capital + quarterly check-ins (mostly passive)
• 1: Capital only (transactional, no engagement)

Data source: portfolio founder references (critical — interview 2-3 portcos per investor), LinkedIn posts patterns.

Dark side probes (ask references):

• "How did the investor behave when [portco] had a down round / missed metrics?"
• "Has the investor pushed for exits / board changes / founder replacements?"
• "How engaged are they with the portco beyond board meetings?"

Weighted scoring

Ajustado por prioridad del founder:

Default: fundraising-first — maximiza probabilidad de close del round.

Value-add-first: cuando founder priorizes strategic investor sobre optimal check terms (ej. post-Series A necesita operating help).

Stealth / Strategic: cuando necesitas investor that strongly matches thesis over pure check efficiency.

Flujo del skill

Paso 1 — Load startup + fundraising context

IM-1: "Vamos a targetear investors contra tu round. Necesito:

1. startup-profile.md (si existe — lo leo)
2. Round specifics:
   • Amount raising: $X
   • Target valuation: $Y pre-money (o post-money)
   • Instrument: Priced equity (Series Seed/A+) o SAFE (pre-priced)
   • Close timeline: [weeks]
3. Fundraising priority: Fundraising-first / Value-add-first / Stealth-Strategic
4. Geography preference: [LATAM / US / EU / Global]
5. Sector: [fintech / healthtech / B2B SaaS / marketplace / etc.]
6. Existing investor intros: ¿Hay existing investors que pueden referir?"

Paso 2 — Generate target criteria

IM-2: Generar target-criteria.md con el perfil ideal de investor derivado de respuestas anteriores.

Paso 3 — Source candidates

IM-3: "¿Cómo querés sourcear candidates?

• Manual input: vos me das N nombres + contexto
• Curated lists: YC Investor Day List, NVCA directory, Crunchbase, LATAM VC directory (CB Insights tables)
• DojoOS investor database (cuando la API esté disponible via dojoos-api-consumer agent)

Para cada candidate necesito: nombre del fund, partner / angel name, LinkedIn, recent checks public info."

Paso 4 — Score cada investor

IM-4: Por cada candidate, generar fit-scorecard.md con:

• Score por eje (1-5 con evidence citation)
• Weighted total
• Competitors en su portfolio (red flag if strong)
• Warm intro path (1st/2nd/3rd degree LinkedIn connection)

Paso 5 — Intelligence notes

IM-5: Por cada investor top-tier, generar intelligence-notes.md:

• Last 5 investments (amount + stage)
• Public thesis evolution (track changes over last 2 years)
• Podcast / blog appearances con positions relevantes
• Known biases (e.g., "pasa en founders sin CS degree", "prefers technical co-founders", "no invierte en marketplaces")
• Founder references feedback (si disponible)

Paso 6 — Outreach customization

IM-6: Generar outreach-template.md por top-tier investor:

• Email 1: Intro vía warm path si existe; cold email templated si no
• Email 2: Follow-up (7 días post-1) con update concreto (traction, pipeline, team)
• LinkedIn message: Short, thesis-specific, incluye 1 metric
• Intro request to mutual: Template de pedido de introducción vía mutual contact

Personalization per investor:

• Ref al último deal relevante del investor ("Vi tu inversión en X — hay paralelos con nuestro enfoque en Y")
• Ref a su thesis published ("Tu post de Jun 2025 sobre Z resonó con nuestro approach")
• NO menciones generic fund info que todos saben

Paso 7 — Target list + sequence plan

IM-7: Generar target-list.md (ranked) + sequence plan:

• Tier 1 (top 5 scores): parallel outreach en primeras 2 semanas
• Tier 2 (next 10): parallel outreach en week 3-4
• Tier 3 (remainder): reserve para post first-pass learnings

Sequence tactics:

• NEVER mass email (destroys reputation + signals desperation)
• Batch de 3-5 investors por semana con staggered follow-ups
• Track response rate + adjust outreach based on early results
• Maintain "no-shop" consistency: si lead investor pidió no-shop, respectar period

Paso 8 — Tracker setup

IM-8: Generar tracker.md — simple kanban:

• Queue: not yet contacted
• Contacted: email sent, awaiting response
• Responded positive: scheduled intro call
• Intro done: post-call, awaiting followup decision
• Partner meeting: advanced to partnership meeting
• Term sheet in discussion: active negotiation
• Committed: soft/hard commitment
• Passed: no (with rationale)

Update cadence: weekly during active fundraise.

Output template — fit-scorecard.md

# Investor Fit Scorecard — [Investor Name / Fund]

**Startup**: [Name]
**Partner / Angel**: [Name]
**Fund**: [Fund name if VC]
**Date**: YYYY-MM-DD
**Priority weighting**: [Fundraising-first / Value-add-first / Stealth-Strategic]

---

## Investor profile snapshot

- **Check size**: [median] (based on last [N] deals)
- **Stage focus**: [Seed / Series A / etc.]
- **Geography**: [list]
- **Vertical**: [list]
- **Thesis**: [1-2 sentence summary from public sources]
- **Last 5 investments**: [brief list]

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

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

### 2. Check size fit — Score: X/5 (weight XX%)

**Their median**: $X
**Our round**: $Y
**Fit**: [expressed as overlap]

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

**Our thesis**: [1 sentence]
**Their thesis**: [1 sentence]
**Overlap evidence**: [citation]

### 4. Geography / vertical — Score: X/5 (weight XX%)

### 5. Value-add depth — Score: X/5 (weight XX%)

---

## Weighted total

| Axis | Score | Weight | Weighted |
|---|---|---|---|
| Stage fit | X | XX% | X.XX |
| Check size fit | X | XX% | X.XX |
| Thesis alignment | X | XX% | X.XX |
| Geography / vertical | X | XX% | X.XX |
| Value-add depth | X | XX% | X.XX |
| **TOTAL** | — | **100%** | **X.XX / 5** |

---

## Red flags checklist

- [ ] **Portfolio conflict**: ¿invirtieron en direct competitor?
- [ ] **Recent thesis drift**: ¿cambió focus away from our space en últimos 6 meses?
- [ ] **Bad founder references**: ¿references negative on specific behaviors?
- [ ] **Process red flags**: ¿timeline lento históricamente? (>90 days decision cycle = pass)

If ANY red flag = **DISQUALIFY o approach con caution**.

---

## Warm intro path

**Direct**: [if we have connection]
**1st degree mutual**: [name + strength of relation]
**2nd degree path**: [chain + likelihood of ask]

**Recommendation**: [Cold email / Intro request / Event meet / Pass]

---

## Next step

[Specific action: "Draft intro email to [mutual] by YYYY-MM-DD"]

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

Disponible desde v0.5.0 — este skill puede invocar al agent dojoos-api-consumer con las operaciones get_investor_database (listado candidate investors) y get_investor_profile (detail por investor). Ambas retornan SPEC_GAP hoy (los endpoints no están en la OpenAPI spec todavía) y el skill continúa con sources manuales (NVCA, Crunchbase, LAVCA, CSV upload). Cuando los endpoints lancen, el agente retornará LIVE_DATA sin cambios acá — el target list inicial se pre-popula con investors + check history + portfolio fit + Dojo Score weighting automáticamente. Cada SPEC_GAP que retorna el agente viene con un SPIKE_SUGGESTION listo para alimentar el skill feature-to-spike.

Integración con otras skills

• startup-intake: source del startup-profile.md para thesis alignment + fundraising context
• cap-table-builder: post-match, post-commit, track dilution per investor check
• founder-documents: SAFE o Term Sheet (NVCA) generados después de soft-commit
• demo-day-prep (sibling): si es demo day investor, coordinate flow
• feature-to-spike: SPIKE para DojoOS si detectás matching gap o pattern útil
• venture-studio-toolkit:structure-decision: si venture es LATAM-based + US VC, needs Cayman Sandwich o Delaware flip first

Principios clave

• Target quality > quantity: 15-20 well-researched investors > 100 spray-and-pray
• Warm intros siempre que sea posible: 10x response rate vs cold
• Never negotiate alone: especially first-time founders — bring advisor or counsel
• Track every interaction: response rate + time-to-response + pipeline velocity informan el próximo round
• Investor quality affects the cap table forever: bad investor > no investor
• "No" es información útil: si multiple top-tier pass with similar rationale, revisar pitch/deck/metrics

Anti-patterns

• Mass cold emails (destroys reputation, signals desperation)
• Pitching investors outside stage/check size fit ("maybe they'll stretch")
• Starting fundraise without 8+ weeks runway to close (runway pressure = bad terms)
• Ignoring portfolio conflicts ("maybe they won't notice")
• Sharing deck publicly (securities law + competitive risk)
• No "no-shop" respecting if lead asked
• Negotiating one investor at a time (lose optionality + leverage)

Recursos

• NVCA Member Directory — US VC directory
• Crunchbase — investor database + check history
• PitchBook — professional-grade investor data
• LAVCA — LATAM VC Association — LATAM investor directory
• CB Insights — market intelligence + investor tracking
• "Venture Deals" (Brad Feld + Jason Mendelson) — essential reading for founder-investor negotiation
• "Secrets of Sand Hill Road" (Scott Kupor, Andreessen Horowitz) — VC insider perspective
• Twenty Minute VC Podcast — investor thesis intelligence gathering