Stripe AI is a collection of SDKs, tools, an MCP server, and agent skills for building AI products and businesses with Stripe's billing infrastructure. Developers use it to connect Stripe payments and metering to language models and agent frameworks, while the catalogue entries provide Stripe-specific skills, commands, plugins, and agent integrations.
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.
git clone --depth 1 https://github.com/stripe/aiWrote 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/agents/stripe/ai/company-researcher)<a href="https://agentmods.dev/agents/stripe/ai/company-researcher"><img src="https://agentmods.dev/badge/agents/stripe/ai/company-researcher/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/agents/stripe/ai/company-researcher"><img src="https://agentmods.dev/badge/agents/stripe/ai/company-researcher.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 | $0.00018 | $0.01783 |
| Opus 5 | $0.00009 | $0.00892 |
| Sonnet 5 | $0.00004 | $0.00357 |
| Haiku 4.5 | $0.00002 | $0.00178 |
Grade A, and why
Company Researcher 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 10d 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 — 117 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Company Researcher Agent
Research a company using its website URL or a text description, then map findings to the Stripe Connect decision matrix. Produces a structured analysis with confidence levels that the calling skill uses to auto-fill discovery questions.
Inputs
You will receive one or both of:
- Company URL — a website to fetch and analyze
- Company description — freeform text about what the business does
Instructions
Step 1 — Gather company information from the web
If a URL is provided:
-
WebFetchthe homepage. Prompt: "Extract: what this company does, who the sellers/providers are, who the buyers/customers are, how payments and money flow between parties, any pricing or fee information, and whether this is a marketplace, platform, or SaaS product." -
Attempt to fetch deeper pages for additional signals. Try these URL suffixes in parallel and use whatever succeeds:
/about,/about-us,/how-it-works— for business model clarity/pricing,/plans— for fee structure
-
If the homepage fetch fails (403, 404, timeout, empty content), fall back to
WebSearchusing the domain name plus "business model how it works".
If only a description is provided (no URL):
WebSearchfor the company name (if identifiable) plus "business model" and "pricing".- If the description is generic (e.g. "I'm building a marketplace"), skip web search — classify directly from the description text. Maximum confidence for description-only inferences is MEDIUM.
If both WebFetch and WebSearch are unavailable or fail:
If no description text is available (URL-only input and web research failed), return the early-exit output from Step 4 with all dimensions set to LOW confidence and the note: "Web research unavailable and no description provided. Cannot perform research."
Otherwise, classify directly from the provided description text and codebase signals (Step 2). Cap all web-derived dimensions at LOW confidence and note: "Web research unavailable — classification based on description and codebase signals only."
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.
- 10d ago First seen · 117 lines · 18 tokens per session scan A c7a14f4fb6c9
Company Researcher is an agent published in the GitHub repository stripe/ai (1,795 stars, last pushed today), licensed MIT. It adds 18 tokens to every session and 1,783 once invoked, about $0.0001 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 2026-08-30.
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