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 nostrband/ServiceGraph --skill find-ai-consultancygit clone --depth 1 https://github.com/nostrband/ServiceGraphWrote 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/nostrband/servicegraph/find-ai-consultancy)<a href="https://agentmods.dev/skills/nostrband/servicegraph/find-ai-consultancy"><img src="https://agentmods.dev/badge/skills/nostrband/servicegraph/find-ai-consultancy/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/nostrband/servicegraph/find-ai-consultancy"><img src="https://agentmods.dev/badge/skills/nostrband/servicegraph/find-ai-consultancy.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 | $0.00244 | $0.03475 |
| Opus 5 | $0.00122 | $0.01737 |
| Sonnet 5 | $0.00049 | $0.00695 |
| Haiku 4.5 | $0.00024 | $0.00347 |
Grade A, and why
find-ai-consultancy scanned grade A with 1 finding 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
Any HTTP client works (curl, fetch, requests). Examples below use curl. How it starts
The opening of the file, as written. The whole thing — 288 lines — stays where its author put it; the contents beside it link to each section on GitHub.
find-ai-consultancy
Drive the ServiceGraph API (https://api.servicegraph.co) to find,
shortlist, and enrich US AI/ML and data consultancies via the
pro_services dataset. The catalog tags firms with
industry:data_ai_consulting and a 4-tag service sub-taxonomy:
ai-ml-development (the largest at ~12k firms), data-analytics,
cloud-services, and api-integration. There is no
data-engineering or business-intelligence sub-tag —
data-analytics covers both. Confirm exact tag names via
/v1/datasets/pro_services/fields?include_values=1.
Always pin industry:data_ai_consulting. This skill exists to
do that automatically — the user shouldn't have to think about catalog
taxonomy.
Any HTTP client works (curl, fetch, requests). Examples below use curl.
Sibling skills — defer when scope is different
- General application or backend dev that uses AI as a feature
(e.g. "build us a SaaS with an AI chatbot tab") →
find-software-developer. - Web/site projects that include some AI →
find-web-developer. - AI-related marketing or content →
find-marketing-agency.
This skill is for engagements where the AI/ML/data work IS the deliverable.
When NOT to use this skill
- Consumer AI courses or learning ("find me an online course to learn ML").
- AI/LLM product comparisons ("ChatGPT vs Claude vs Gemini", "Cursor vs Copilot").
- DIY/code tasks ("how do I fine-tune Llama", "review this PyTorch loop").
- In-house ML/data hires (Machine Learning Engineer, Data Scientist).
- Generic AI knowledge questions.
- Non-US firms / individual freelance ML engineers.
MCP server (preferred for authed calls)
If your harness has the ServiceGraph MCP server loaded (tools
containing servicegraph), prefer those — OAuth 2.1 + PKCE keeps the
token in the harness sandbox. Otherwise use the REST flow below.
API surface (dataset id: pro_services)
Every endpoint requires the bearer (Authorization: Bearer vk_…).
No anonymous tier.
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 · 288 lines · 244 tokens per session scan A e3d88c1891db
find-ai-consultancy is a skill published in the GitHub repository nostrband/ServiceGraph (62 stars, last pushed 3mo ago), licensed MIT. It adds 244 tokens to every session and 3,475 once invoked, about $0.0012 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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