Find AI Consultancy

What it does

When your agent uses it

• The user wants to find
• Enrich US AI/ML/data consulting firms (consultancies) — AI/ML development
• Generative AI / LLM apps (RAG
• Computer vision

Example prompts

• “find an AI/ML consulting firm to build our recommendation engine”
• “shortlist three RAG/LLM consultancies for an enterprise chatbot”
• “compare three AI/ML consulting firms with strong ratings”
• “/find-ai-consultancy”

Requirements

• A credential in SERVICEGRAPH_API_KEY
• Compatibility (from SKILL.md): Designed for Claude Code
• Pre-approved tools (allowed-tools): Bash(curl:*), mcp__servicegraph__list_fields, mcp__servicegraph__list_field_values, mcp__servicegraph__check_filter, mcp__servicegraph__translate_intent, mcp__servicegraph__search_dataset, mcp__servicegraph__get_row, mcp__servicegraph__unlock_rows, mcp__servicegraph__get_credit_balance

Workflow steps

7 steps, taken from the first numbered list in SKILL.md.

1. 1Pick the call path — the ServiceGraph MCP tools if loaded, otherwise the
2. 2GET /v1/datasets/pro_services/fields?include_values=1 — confirm the
3. 3Build the filter (Filter DSL below) and validate it with
4. 4GET /v1/datasets/pro_services/search — present the free brief cards and
5. 5Quote the unlock cost (10 credits per row, 30-day TTL) and get an explicit
6. 6POST /v1/datasets/pro_services/unlocks with the chosen apexes; report the
7. 7GET /v1/me/credits to report the remaining balance when asked.

What it can do on your machine

Read from SKILL.md and the folder at commit cfae287. It shows what the files ask for, not the result of running them.

• Tool permissions

  Pre-approves these tools, so the agent can use them without asking each time:

  • Bash(curl:*)
  • mcp__servicegraph__list_fields
  • mcp__servicegraph__list_field_values
  • mcp__servicegraph__check_filter
  • mcp__servicegraph__translate_intent
  • mcp__servicegraph__search_dataset
  • mcp__servicegraph__get_row
  • mcp__servicegraph__unlock_rows
  • mcp__servicegraph__get_credit_balance

  From allowed-tools in the SKILL.md frontmatter.

• Runs code

  Shell commands in SKILL.md call:

  • curl

  From the folder's file list and the shell code blocks in SKILL.md.

• Network

  Hosts in commands or code, which the agent is likely to contact:

  • api.servicegraph.co
  • mcp.servicegraph.co

  Also links to:

  • servicegraph.co
  • github.com

  From URLs in SKILL.md, links to its own repository left out.

• Credentials

  Names these keys or tokens, usually read from environment variables:

  • SERVICEGRAPH_API_KEY

  From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

• Compatibility

  Designed for Claude Code

  From compatibility in the SKILL.md frontmatter.

Context cost

Find AI Consultancy loads about 4k tokens when it runs. Until then it costs about 259 tokens; SKILL.md has 1,361 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it

~259

When it runs · the whole SKILL.md, loaded when a task matches

~4k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

• NoteMentions a .env fileSKILL.md:72

  ICEGRAPH_API_KEY` in the environment or `.env.local` for the REST

• NoteMentions a .env fileSKILL.md:124

  LLM context** — never read `.env*` into your context; dispatch via

• NoteMentions a .env fileSKILL.md:128

  `.env.local`:

• NoteMentions a .env fileSKILL.md:131

  ( set -a; [ -f .env.local ] && . ./.env.local; set +a;

• NoteMentions a .env fileSKILL.md:139

  and add `SERVICEGRAPH_API_KEY=vk_…` to `.env.local` here

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from jeremylongshore/tons-of-skills-marketplace at commit cfae287, republished under its MIT licence (© jeremylongshore). 1,361 words, ~3,973 tokens.

name

find-ai-consultancy

description

Use whenever the user wants to find, shortlist, vet, or enrich US AI/ML/data consulting firms (consultancies) — AI/ML development, MLOps, generative AI / LLM apps (RAG, chatbots, agents), computer vision, NLP, recommendation systems, data engineering, BI/analytics. Triggers on "find an AI/ML consulting firm to build our recommendation engine", "shortlist three RAG/LLM consultancies for an enterprise chatbot", "compare three AI/ML consulting firms with strong ratings", or "pull contact info for these 8 AI consultancy domains", even when described indirectly (we want to use AI for X, deploy ML to production). Drives the ServiceGraph API (api.servicegraph.co) — a 100k+ US firm catalog filterable by industry, services, location, size, ratings. Defer to find-software-developer for general app/backend work where AI is just a feature. Skip in-house ML/data hires, LLM/AI-tool comparisons (ChatGPT vs Claude), "how do I fine-tune X" DIY questions, AI courses for individuals, non-US firms, individual freelancers.

allowed-tools

Bash(curl:*), mcp__servicegraph__list_fields, mcp__servicegraph__list_field_values, mcp__servicegraph__check_filter, mcp__servicegraph__translate_intent, mcp__servicegraph__search_dataset, mcp__servicegraph__get_row, mcp__servicegraph__unlock_rows, mcp__servicegraph__get_credit_balance

compatibility

Designed for Claude Code

version

0.3.0

author

Artur Briugeman <artur@nostr.band>

license

MIT

tags

ai-consulting, machine-learning, service-providers, lead-generation, servicegraph

metadata.api_base

https://api.servicegraph.co

metadata.dataset_id

pro_services

metadata.industry

data_ai_consulting

filter   := orExpr
orExpr   := andExpr ("OR" andExpr)*
andExpr  := notExpr (("AND")? notExpr)*    # whitespace = implicit AND
notExpr  := ("NOT" | "-") notExpr | atom
atom     := "(" filter ")" | predicate
predicate:= IDENT op valueOrList | bareword
op       := ":" | "=" | ">=" | "<=" | ">" | "<"
valueOrList := value ("," value)*
value    := IDENT | NUMBER | tagAtEvidence
tagAtEvidence := IDENT "@" ("low"|"medium"|"high")
bareword := IDENT | NUMBER          # → keyword:<bareword>

industry:data_ai_consulting service_provided:ai-ml-development
industry:data_ai_consulting service_provided:ai-ml-development@high state:CA
industry:data_ai_consulting service_provided:data-analytics pipelines
industry:data_ai_consulting llm rag
industry:data_ai_consulting "computer vision" healthcare
industry:data_ai_consulting mlops
industry:data_ai_consulting (service_provided:ai-ml-development OR service_provided:data-analytics)
industry:data_ai_consulting service_provided:ai-ml-development@high rating>=4 has:clutch

GET /v1/datasets/pro_services/search?filter=industry:data_ai_consulting+service_provided:ai-ml-development+recommendation+ecommerce&limit=10

# Present, get pick of 3. "Unlocking 3 = 30 credits, 30-day TTL."
POST /v1/datasets/pro_services/unlocks
  { "apexes": ["firm-a.com", "firm-b.com", "firm-c.com"] }

GET /v1/datasets/pro_services/search?filter=industry:data_ai_consulting+(rag OR llm)+chatbot+enterprise&limit=10

GET /v1/datasets/pro_services/search?filter=industry:data_ai_consulting+service_provided:data-analytics+(pipelines OR engineering)&limit=10

GET /v1/datasets/pro_services/search?filter=industry:data_ai_consulting+mlops&limit=10

GET /v1/datasets/pro_services/search?filter=industry:data_ai_consulting+service_provided:ai-ml-development+(churn OR predictive)&limit=10

POST /v1/datasets/pro_services/translate-intent
  { "intent": "AI consultancy to build customer churn prediction" }

GET /v1/datasets/pro_services/search?filter=industry:data_ai_consulting+"computer vision"+healthcare&limit=10

GET /v1/datasets/pro_services/search?filter=industry:data_ai_consulting+service_provided:ai-ml-development@high+rating>=4+fortune&limit=10

GET /v1/datasets/pro_services/search?filter=industry:data_ai_consulting+(llm OR agent)+("customer service" OR support)&limit=10

GET /v1/datasets/pro_services/fields?include_values=1
GET /v1/datasets/pro_services/check?filter=industry:data_ai_consulting+service_provided:ai-ml-development@high+recommendation+ecommerce+rating>=4
GET /v1/datasets/pro_services/search?filter=...&limit=10
# Present briefs. "Unlocking 3 = 30 credits, 30-day TTL."
POST /v1/datasets/pro_services/unlocks
  { "apexes": ["firm-a.com", "firm-b.com", "firm-c.com"] }
GET /v1/me/credits

© jeremylongshore, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in plugins/mcp/servicegraph/skills/find-ai-consultancy of jeremylongshore/tons-of-skills-marketplace.

Open the folder on GitHubat commit cfae287