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**: | Eje | Fundraising-first (default) | Value-add-first | Stealth / Strategic | |---|---|---|---| | Stage fit | 25% | 20% | 20% | | Check size fit | 25% | 20% | 20% | | Thesis alignment | 20% | 20% | 30% | | Geography / vertical | 15% | 15% | 15% | | Value-add depth | 15% | 25% | 15% | **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 ```markdown # 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](https://nvca.org/about-us/nvca-members/)** — US VC directory - **[Crunchbase](https://www.crunchbase.com/)** — investor database + check history - **[PitchBook](https://pitchbook.com/)** — professional-grade investor data - **[LAVCA — LATAM VC Association](https://lavca.org/)** — LATAM investor directory - **[CB Insights](https://www.cbinsights.com/)** — market intelligence + investor tracking - **"Venture Deals"** (Brad Feld + Jason Mendelson) — essential reading for founder-investor negotiation