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Investor Targeting

skill-oncesylvia-fundraising-skills-investor-targeting · by oncesylvia

Build a tiered, stage- and sector-fit list of investors (VCs, angels, micro-funds, accelerators) for a founder's raise, using free public sources and live web search. Use when a founder asks "who should I raise from", "find investors for my startup", "which funds invest in <sector> at <stage>", or wants to build or qualify a fundraising target list. Never invents firms or partners — every name is…

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Install

$ agentstack add skill-oncesylvia-fundraising-skills-investor-targeting

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Security review

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No issues found. Passed automated security review. · v0.1.0 How review works →

  • Prompt-injection patterns
  • Secret / credential exfiltration
  • Dangerous shell & filesystem operations
  • Untrusted network calls
  • Known-malicious package signatures

What it can access

  • Network access No
  • Filesystem access No
  • Shell / process execution No
  • Environment & secrets No
  • Dynamic code execution No

From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.

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About

Investor targeting

Help a founder build a tiered target list of investors that actually fit their stage, sector, geography, and check size — grounded in live research, not memory. A wrong or invented name wastes the founder's scarcest resource (warm intros and credibility), so the prime directive is: research, cite, flag — never fabricate.

Read shared/references/outreach-ethics.md before producing output.

The hard rule on hallucination

You do not have a reliable investor database in your weights. Fund theses, partner moves, check sizes, and "are they actively deploying" change constantly. Therefore:

  • **Do not name a specific firm, partner, or angel from memory as a

recommendation.** Every name in the final list must come from a live WebSearch / WebFetch performed in this session.

  • Each entry carries a source link and a confidence flag

(verified / likely / unverified — check).

  • If research is thin for a niche, say so. A short honest list beats a long

fabricated one. It is correct to return "I found 6 strong fits; here are 4 search angles to find more" rather than padding to 30.

Step 1 — Profile the raise (ask before searching)

Collect these from the founder. If they're missing, ask; don't assume.

  1. One-liner: what you do, for whom, the wedge.
  2. Stage & round: pre-seed / seed / Series A; how much you're raising; how

much is committed. (See references/stage-map.md for what each stage means for targeting.)

  1. Sector / category + business model (B2B SaaS, consumer, deep tech,

fintech, hardware, marketplace, AI infra, etc.). See references/sector-taxonomy.md.

  1. Geography: where you're based, where you can take money from (some funds

only invest in their region/jurisdiction).

  1. Traction: the 1–2 metrics that make you fundable right now (revenue,

growth, users, LOIs, a notable design partner). This drives who is a fit — a fund's check size must match your stage.

  1. Any constraints: strategic investors to court or avoid, conflicts

(competing portfolio cos), values requirements.

Step 2 — Search across complementary angles

Don't rely on one query. Use several angles so you don't miss whole pockets. See references/free-data-sources.md for the full source list. Core moves:

  • Thesis search: " investors", `"funds investing in

2025", " seed funds"`.

  • Portfolio-analogy search: find a few non-competing companies one notch

ahead of you in the same category, then search who funded their seed/A. Their investors have proven appetite for your space. ("who invested in seed round").

  • Operator-angel search: search for angels who built or led in your

category (" angel investors", notable operators who now angel invest). Angels move faster and are often the first checks.

  • Accelerator search: if pre-seed/idea stage, search accelerators/studios

that focus on your sector or geography.

  • Directory search: OpenVC, NFX Signal, the fund's own "submit a deal"

page, recent SEC Form D filings, AngelList/Wellfound syndicates, relevant newsletters and "VC thesis" posts.

For each promising hit, WebFetch the firm/angel's own site to confirm: stage focus, check size, sector, geography, and how they want to be contacted (many list a submit form or a partner's preferred path).

Step 3 — Qualify and tier

Score each candidate on fit, then sort into tiers:

  • Stage fit — does their typical check match your round?
  • Sector fit — explicit thesis or portfolio evidence in your space?
  • Geo/jurisdiction fit — can they legally/practically invest in you?
  • No conflict — not already backing a direct competitor.
  • Reachability — is there a warm path or a clear public contact route?

Tier the output:

  • Tier A (high conviction, lead with these) — strong on all five, clear

contact path. Aim for a focused set you can deeply personalize.

  • Tier B (good fit, second wave) — solid fit, weaker on one axis or no warm

path yet.

  • Tier C (worth watching / opportunistic) — plausible but unverified, or

fit is partial.

Step 3.5 — Sequence the outreach (don't burn your best leads first)

Recommend running outreach in waves: start with a few Tier B firms to pressure- test the pitch and gather objections, refine, then approach Tier A with the sharpened version and your best warm intros. Hand the Tier A targets to the warm-intro and cold-email skills.

Step 4 — Deliver

Output a table the founder can paste into a tracker (the pipeline-tracker format if present), with columns:

| Firm / Angel | Tier | Why they fit | Stage & check | Contact path | Source | Confidence | |---|---|---|---|---|---|---|

Then add:

  • Coverage note: which angles you searched and which you didn't, so the

founder knows what's not covered.

  • Next searches: 3–5 concrete queries to extend the list themselves.
  • Verify-before-send reminder: re-check each firm's current stage focus and

contact preference right before reaching out — these go stale.

Bilingual / China market (中文)

If the founder is raising in the China market, read shared/references/china-market-playbook.md first. The free data sources differ — use IT桔子 / 企查查 / 天眼查 / 36氪 / 投资界 instead of Crunchbase to verify a fund's deals and whether it's an RMB or state-backed fund (人民币/国资, which changes its mandate and process). Same anti-hallucination rule: research live, cite the source, never invent a 机构 name.

Anti-patterns to refuse

  • Producing a long list "from knowledge" without searching.
  • Guessing partner email addresses.
  • Recommending a fund whose stage clearly doesn't match (e.g., a growth fund

for a pre-seed idea) just to lengthen the list.

  • Dropping source links "to keep it clean." The links are the point.

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

Install and usage instructions live in the source repository linked above.

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Versions

  • v0.1.0 Imported from the upstream source.