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 warm-introgit 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/warm-intro)<a href="https://agentmods.dev/skills/oncesylvia/fundraising-skills/warm-intro"><img src="https://agentmods.dev/badge/skills/oncesylvia/fundraising-skills/warm-intro/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/warm-intro"><img src="https://agentmods.dev/badge/skills/oncesylvia/fundraising-skills/warm-intro.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 | $0.00105 | $0.01285 |
| Opus 5 | $0.00053 | $0.00642 |
| Sonnet 5 | $0.00021 | $0.00257 |
| Haiku 4.5 | $0.00011 | $0.00128 |
Grade A, and why
warm-intro 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 — 113 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Warm introductions
A warm intro is the highest-converting way into an investor. This skill helps a founder (1) find who can introduce them and (2) write a forwardable, double opt-in intro that makes the connector's job effortless and the investor's decision easy.
Read shared/references/outreach-ethics.md first. The connector is spending
their credibility for you — never make that costly or risky for them.
The core mechanic: double opt-in, forwardable
The gold-standard etiquette:
- You write a short note to your connector asking if they're willing to intro — and you include a forwardable blurb they can paste/forward as-is.
- The connector checks with the investor first ("can I intro you to X?") — double opt-in. This protects the connector and means the investor arrives warm, not ambushed.
- The connector forwards your blurb; the investor replies; you take it from there.
Your job is to make step 1 take the connector 30 seconds. The easier you make it, the more likely it happens — and the better it reflects on you.
Step 1 — Find the warm path
If the founder doesn't yet know who to target at the firm or who can introduce them, run the
warm-path-finderskill first — it pinpoints the right person and ranks connection paths from the founder's own authorized data (Gmail, exported LinkedIn connections, contacts) and public sources. This skill takes over once a named introducer exists.
Before writing, help the founder figure out who can intro them:
- Direct: do they already know someone at/near the firm?
- Second degree: search LinkedIn for shared connections to the target partner; check who in their network knows portfolio founders (a portfolio founder's intro is gold — investors trust their founders).
- Community paths: accelerator alumni, university/employer networks, angel syndicates, founder Slacks, mutual advisors.
- Best connector ≠ most senior. The ideal introducer is someone the investor trusts and replies to and who genuinely rates you. A lukewarm intro from a big name is worse than an enthusiastic one from a respected peer.
What ships with it
2 files 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 · 113 lines · 105 tokens per session scan A 97fbe0abc912
warm-intro is a skill published in the GitHub repository oncesylvia/fundraising-skills (4 stars, last pushed 2mo ago), licensed MIT. It adds 105 tokens to every session and 1,285 once invoked, about $0.0005 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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