Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add oncesylvia/fundraising-skills --skill investor-researchgit clone --depth 1 https://github.com/oncesylvia/fundraising-skillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/oncesylvia/fundraising-skills/investor-research)<a href="https://agentmods.dev/skills/oncesylvia/fundraising-skills/investor-research"><img src="https://agentmods.dev/badge/skills/oncesylvia/fundraising-skills/investor-research/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/oncesylvia/fundraising-skills/investor-research"><img src="https://agentmods.dev/badge/skills/oncesylvia/fundraising-skills/investor-research.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00113 | $0.01110 |
| Opus 5 | $0.00056 | $0.00555 |
| Sonnet 5 | $0.00023 | $0.00222 |
| Haiku 4.5 | $0.00011 | $0.00111 |
Grade A, and why
investor-research scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 12d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 84 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Investor research (single-firm diligence)
Before a founder spends a warm intro or sits in a meeting, they should know who they're talking to. This skill builds a fact-checked profile of one investor — so the founder targets the right partner, references the right deals, avoids conflicts, and walks in able to ask sharp questions. Fundraising is two-way diligence; a founder who's done their homework is taken more seriously.
Read shared/references/outreach-ethics.md first. Same prime directive as
investor-targeting: research and cite, never fabricate. Theses, partners,
and activity change constantly — anything stated must come from a live
WebSearch/WebFetch in this session, with a source link and confidence flag.
What to produce
A one-page profile with these sections. If a section can't be verified, say "couldn't verify" rather than guessing.
- Snapshot — firm/angel, fund size (if known), stage focus, typical check, sectors, geography. Source each.
- Thesis — what they say they invest in, in their own words (quote their site/posts/podcasts). Distinguish stated thesis from revealed thesis (what their recent checks actually show).
- Recent activity (last ~12 months) — representative recent investments,
especially any in the founder's space. Are they actively deploying? A fund
that hasn't led a deal in a year is a different conversation. (See
references/diligence-checklist.md.) - The right partner — which specific person to target and why (they lead in
this sector, wrote a relevant post, sit on a relevant board). Partner fit
matters more than firm fit — you're pitching a person. (To go deep on
pinpointing the person and finding a warm path to them, use the
warm-path-finderskill.) - Portfolio fit & conflicts — analogous wins that build appetite, and any direct competitor in their portfolio (usually a hard blocker; flag it).
- How they decide — partnership process, speed, check/ownership targets, whether they lead or follow, board involvement — whatever is publicly known.
- Reputation / founder-friendliness — signals from public founder references, their content, how they behave in downturns. Flag both green and red. Be fair: report what's sourced, label opinion as opinion.
- Contact path — how they want to be approached (submit form, warm intro preference, public email), and whether a warm path likely exists.
- Smart questions to ask them — 4–6 specific questions that show the founder did the work and surface whether this investor is right for them (reserve, follow-on behavior, where they add value, recent exits/markups).
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 12d ago First seen · 84 lines · 113 tokens per session scan A 9bf1ed050045
investor-research is a skill published in the GitHub repository oncesylvia/fundraising-skills (4 stars, last pushed 2mo ago), licensed MIT. It adds 113 tokens to every session and 1,110 once invoked, about $0.0006 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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