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 AndrewNgGirl/SkillLens --skill startup-fundraising-advisorgit clone --depth 1 https://github.com/AndrewNgGirl/SkillLensWrote 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/andrewnggirl/skilllens/startup-fundraising-advisor)<a href="https://agentmods.dev/skills/andrewnggirl/skilllens/startup-fundraising-advisor"><img src="https://agentmods.dev/badge/skills/andrewnggirl/skilllens/startup-fundraising-advisor/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/andrewnggirl/skilllens/startup-fundraising-advisor"><img src="https://agentmods.dev/badge/skills/andrewnggirl/skilllens/startup-fundraising-advisor.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 | $0.00054 | $0.00813 |
| Opus 5 | $0.00027 | $0.00407 |
| Sonnet 5 | $0.00011 | $0.00163 |
| Haiku 4.5 | $0.00005 | $0.00081 |
Grade A, and why
startup-fundraising-advisor 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 7d 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.
What it actually says
Startup Fundraising Memo Advisor
Description
帮助早期创业团队把融资材料、运营数据和市场假设整理成可投资人沟通的融资备忘录。适用于准备天使轮、Pre-A 或 A 轮融资的创始人、CFO 和投融资顾问。
When to use
- 创始人需要把 pitch deck、财务模型、用户增长数据和竞品信息转成一页式投资人 memo。
- 团队需要识别融资故事里的关键缺口,例如牵引力不足、商业模式证据薄弱、估值假设过激。
- 投融资顾问需要在路演前快速形成 due diligence 风险清单和下一步补证建议。
Inputs
company_profile: 公司简介、团队背景、产品阶段、目标融资轮次。traction_metrics: MRR、ARR、留存、CAC、LTV、毛利率、回款周期、客户数量。fundraising_terms: 目标融资金额、估值区间、资金用途、runway。market_notes: 市场规模、竞品、客户访谈、渠道反馈。
Workflow
- 判断融资阶段和投资人关注点,区分天使轮的团队/愿景、A 轮的增长效率、B 轮后的规模化证据。
- 计算关键指标并标记异常:例如 CAC 回收期过长、净收入留存不足、客户集中度过高。
- 生成投资人 memo:问题、解决方案、市场、牵引力、商业模式、竞争优势、融资用途。
- 输出 due diligence 清单,明确哪些结论来自真实数据,哪些只是创始人假设。
- 给出补证建议,例如补充 cohort 留存、客户 pipeline、付费转化漏斗、毛利拆解。
Risk and compliance boundaries
- 不承诺融资成功率,不生成误导性估值背书。
- 对没有数据支持的 TAM、增长率、回款周期和 LTV/CAC 结论必须降级为假设。
- 涉及投资邀约、证券发行或跨境融资时,提示用户咨询持牌机构或律师。
Output
返回结构化 JSON:
{
"memo": {
"stage_fit": "pre_a",
"one_liner": "AI workflow agent for compliance-heavy finance teams",
"traction_summary": ["MRR 48k USD", "net revenue retention 112%"],
"business_model": "seat-based SaaS with pilot-to-annual conversion",
"fundraising_use": ["product", "sales", "security audit"]
},
"risks": [
{
"risk": "customer concentration",
"severity": "high",
"evidence": "top 2 customers contribute 61% of MRR",
"fix": "add pipeline conversion and expansion plan before investor outreach"
}
],
"questions_for_founder": [
"What is the latest cohort retention by acquisition channel?",
"Which revenue is signed ARR versus non-binding LOI?"
]
}
Example prompt
“根据这份 deck 和财务模型,帮我生成 Pre-A 投资人 memo,并指出最可能被投资人追问的 5 个问题。”
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.
- 7d ago First seen · 67 lines · 54 tokens per session scan A 838ff0d19088
startup-fundraising-advisor is a skill published in the GitHub repository AndrewNgGirl/SkillLens (75 stars, last pushed 3mo ago), licensed MIT. It adds 54 tokens to every session and 813 once invoked, about $0.0003 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 2026-09-03.
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