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 SELAT-AI/selat-skills --skill vc-ai-infra-scoutgit clone --depth 1 https://github.com/SELAT-AI/selat-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/selat-ai/selat-skills/vc-ai-infra-scout)<a href="https://agentmods.dev/skills/selat-ai/selat-skills/vc-ai-infra-scout"><img src="https://agentmods.dev/badge/skills/selat-ai/selat-skills/vc-ai-infra-scout/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/selat-ai/selat-skills/vc-ai-infra-scout"><img src="https://agentmods.dev/badge/skills/selat-ai/selat-skills/vc-ai-infra-scout.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 | $0.00119 | $0.02239 |
| Opus 5.5 | $0.00048 | $0.00896 |
| Sonnet 5.5 | $0.00024 | $0.00448 |
| Haiku 4.5 | $0.00012 | $0.00224 |
Grade A, and why
vc-ai-infra-scout 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 22d 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 — 119 lines — stays where its author put it; the contents beside it link to each section on GitHub.
vc-ai-infra-scout
When To Use
Use this skill when the user wants to discover early-stage companies, funding rounds, founders, and investor theses across the AI-infrastructure ecosystem. Covers four sub-theses:
- AI Infrastructure — inference runtimes, GPU orchestration, training stacks, vector/data infra
- Crypto-AI / Decentralized AI — on-chain AI agents, DePIN-for-compute, distributed GPU/ML
- Robotics / Embodied AI — robotics foundation models, humanoid/embodied-AI, sim-to-real, actuation/sensor stacks
- Agentic Payments — agent commerce, x402/stablecoin agent settlement, agentic-payment rails
Workflow
- Install:
selat skill install vc-ai-infra-scout - Pick a thesis preset (see Thesis Presets) and a target company, then run:
selat skill run vc-ai-infra-scout --thesis "robotics foundation model" --twitterQuery "robotics foundation model" --fundraisingQuery "robotics startup raised seed funding" --investorQuery "robotics seed fund partner" --domain "<target-domain>".--domainis required: the run is refused without it. Before running, tell the user the cost: all 9 steps run every time, about $0.087 at live prices. Wait for a yes. - The skill compiles each of 9 steps into
selat-paycalls and returns a JSON response. - Synthesize the 9 steps into a VC intelligence memo (tiered funding map, investor thesis extraction, geographic blindspots, strategic recommendations).
Pipeline Steps
| Step | Source | Rail | Purpose |
|---|---|---|---|
| 1 | Tavily | x402 on Base | Broad web discovery for ${thesis} startup funding |
| 2 | Parallel (Product Hunt scope) | MPP on Tempo | Product Hunt launches scoped to ${thesis} |
| 3 | Exa | x402 via Circle Gateway | Deep web context on startup + funding signals |
| 4 | SELAT-native Twitter/X advanced_search | x402 via Circle Gateway | Founder buzz, company chatter |
| 5 | SELAT-native Twitter/X advanced_search | x402 via Circle Gateway | Recent pre-seed/seed fundraising news |
| 6 | Tavily (LinkedIn scope) | x402 on Base | LinkedIn post search for funding announcements |
| 7 | SELAT-native Twitter/X advanced_search | x402 via Circle Gateway | Investor/fund-partner thesis tweets |
| 8 | Apollo people-search | MPP on Tempo | Founder shortlist by keyword + title |
| 9 | Apollo org-enrichment | MPP on Tempo | Deep-dive enrichment on the target domain |
What ships with it
3 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.
- 22d ago Changed · +15 lines · +17 tokens per session 8174adf928ce
- 25d ago Changed · +13 lines ca071428961b
- 1mo ago First seen · 91 lines · 102 tokens per session scan A 6fcafd84a028
vc-ai-infra-scout is a skill published in the GitHub repository SELAT-AI/selat-skills (2 stars, last pushed yesterday), licensed Apache-2.0. It adds 119 tokens to every session and 2,239 once invoked, about $0.0005 per session on Opus 5.5. 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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