draft-investor-outreach

name	draft-investor-outreach
description	Draft personalized investor outreach emails and LinkedIn messages using the startup thesis, investor fit rationale, and specific personalization hooks. Saves a final ranked outreach list and exports to CSV. Triggers on: "draft outreach", "write emails", "draft messages", "step 6", "next step", "continue to draft", "write investor emails", "draft linkedin messages".

Draft Investor Outreach

Pipeline: clarify-thesis → find-vcs → map-investors → enrich-vc-contacts → score-vc-fit → draft-investor-outreach

You are step 6 of 6. Your job is to draft a tailored email and LinkedIn message for each investor in the ranked list, then save the complete output.

Tools

None. This step is reasoning + writing only.

Input

Read data/normalized/scored_funds.json. If the file does not exist, stop and ask the founder to complete score-vc-fit first.

Also read data/normalized/company_profile.json for the startup voice and thesis.

Draft outreach only for firms and contacts that the founder confirmed in step 5. Skip any firms that were removed.

Message principles

Every message must:

• Be tailored to this specific investor — not a template with a name swapped in
• Reference one real, specific reason this investor was selected
• Explain the company clearly in 1–2 sentences
• Make a simple, clear ask
• Avoid hype, generic praise, and fake familiarity

Tone

• Concise
• Confident but not arrogant
• Specific — no filler
• Founder-like — sounds like a person wrote it
• Respectful of the investor's time

Personalization rules

Good personalization hooks:

• "You invested in [portfolio company] — we're solving the same problem from the infrastructure layer"
• "Your thesis post on [topic] directly maps to what we're building"
• "You led [comparable company]'s seed — our model is similar but in [market]"
• Portfolio adjacency that is genuinely relevant, not superficial

Bad personalization:

• "I've long admired your work"
• "You're one of the top funds in [sector]"
• "I noticed you invest in B2B SaaS" (too generic)
• Anything that could apply to 50 other investors

Output format

For each investor, write:

Field	Description
personalization_hook	The specific angle used (1 sentence)
email_subject	Short, specific, non-salesy
email_body	3–5 sentences: who we are, why this investor, traction signal, ask
linkedin_message	Shorter version — 2–3 sentences max
call_to_action	Clear and simple: "Happy to share a brief deck — would a 20-min call make sense?"
optional_follow_up_angle	One angle for a follow-up if no reply in 1 week

Email rules:

• Subject line: max 8 words, no clickbait, no ALL CAPS
• Body: 3–5 sentences. Don't over-explain. One traction signal if available.
• End with a simple, low-friction CTA

LinkedIn message rules:

• Max 300 characters
• No long background — get to the point immediately
• Still include one real reason for reaching out

Rules:

• Do not fabricate traction, portfolio connections, or relationships
• Do not claim a warm intro if none exists
• If there is not enough personalization data for a meaningful hook, note it and draft a simpler but honest message
• Keep messages distinct — each should feel written for that investor

Saving output

Write the final ranked outreach array to data/normalized/final_output.json conforming to schemas/final_output.schema.json.

Field names map directly to CSV columns — use exact field names from the schema.

Final summary to founder

After writing data/normalized/final_output.json, present the output:

Done. Here's your investor outreach list for [company_name]:

[N] personalized outreach drafts saved to data/normalized/final_output.json

Preview of top 5:

--- #1: [investor_name], [fund_name] (score: [score_total]/[score_max_possible]) ---
Subject: [outreach_subject_line]
Email:
[outreach_email_body]

LinkedIn:
[outreach_linkedin_dm]

Hook: [outreach_personalization_hook]
---

[Repeat for top 5]

Contact quality breakdown:
  ✓ [N] confirmed emails
  ~ [N] inferred emails (marked clearly in the file)
  ✗ [N] LinkedIn-only contacts

Next steps:
  1. Review and edit messages in data/normalized/final_output.json
  2. Use your email tool (Instantly, Apollo, Gmail) to send
  3. For inferred emails — verify before sending or use LinkedIn as primary channel
  4. For investors with no email — send via LinkedIn DM

Want any messages revised? Tell me which investor and what to change.

CSV export

After the founder approves the messages, write data/normalized/output.csv by flattening final_output.json.

CSV column order:

priority_rank, fund_name, score_total, score_max_possible, investor_name, investor_title,
contact_tier, work_email, linkedin, outreach_subject_line, outreach_email_body,
outreach_linkedin_dm, outreach_personalization_hook, outreach_cta

Rules:

• Wrap any field containing commas or newlines in double quotes
• Escape internal double quotes as ""
• Include a header row
• One row per investor (same as final_output.json)
• Do not include fund_id in the CSV — it is internal only

Confirm to the founder: data/normalized/output.csv written — [N] rows.

After writing the CSV, remind them:

• data/normalized/output.csv is ready to drop into Notion, Airtable, or an email tool
• data/normalized/final_output.json has the full structured output for re-processing
• All inferred emails are marked contact_tier: "inferred" — verify before sending
• Re-run clarify-thesis at any time to start a fresh campaign with a new fundraising profile