AI Catalog manifest · DataRobot

DataRobot Agent Skills

DataRobot serves an AI Catalog manifest at /.well-known/ai-catalog.json on datarobot.com, declaring 10 agentic resources that a discovery service can index without asking anyone’s permission.

Structural grade · AI Catalog 1.0
Flavored
Fails a hard check in the data model. A catalog in spirit rather than in schema.
ARD conformance tool v0.5.0
FAIL
Run against this exact body with the project’s own conformance CLI — 10 critical errors.
Declared spec version
1.0
The specVersion in the manifest. AI Catalog 1.0 is current; anything lower is an earlier draft.
⚠ Hard checks failed. An ARD client cannot assume this manifest parses to the model the specification defines.

The urn:ai: prefix is not sloppiness — it is the identifier scheme ARD itself specified until ADR-0009 moved the namespace identifier from ai to air for URN validity. This publisher implemented against the earlier draft.

Optional affordances missing. None of these break a client, but each one costs the publisher search relevance or verifiability.
10 entries
1 media type
0 representative queries
0 trust manifests
Host identifier: none

What this manifest advertises

datarobot-model-training

urn:ai:github.com:datarobot-oss:datarobot-agent-skills:model-training

Train models, manage projects, and run AutoML experiments on DataRobot.

application/ai-skill artifact →

datarobot-model-deployment

urn:ai:github.com:datarobot-oss:datarobot-agent-skills:model-deployment

Deploy models, manage deployments, and configure prediction environments on DataRobot.

application/ai-skill artifact →

datarobot-predictions

urn:ai:github.com:datarobot-oss:datarobot-agent-skills:predictions

Make predictions, batch score, and generate prediction datasets on DataRobot.

application/ai-skill artifact →

datarobot-feature-engineering

urn:ai:github.com:datarobot-oss:datarobot-agent-skills:feature-engineering

Engineer features, run feature discovery, and analyze feature importance on DataRobot.

application/ai-skill artifact →

datarobot-model-monitoring

urn:ai:github.com:datarobot-oss:datarobot-agent-skills:model-monitoring

Monitor model performance, track data drift, and manage model health on DataRobot.

application/ai-skill artifact →

datarobot-model-explainability

urn:ai:github.com:datarobot-oss:datarobot-agent-skills:model-explainability

Explain model predictions, compute SHAP values, and run model diagnostics on DataRobot.

application/ai-skill artifact →

datarobot-data-preparation

urn:ai:github.com:datarobot-oss:datarobot-agent-skills:data-preparation

Upload datasets, manage data assets, and validate data for DataRobot workflows.

application/ai-skill artifact →

datarobot-app-framework-cicd

urn:ai:github.com:datarobot-oss:datarobot-agent-skills:app-framework-cicd

Set up CI/CD pipelines for DataRobot application templates with GitLab and GitHub Actions.

application/ai-skill artifact →

datarobot-external-agent-monitoring

urn:ai:github.com:datarobot-oss:datarobot-agent-skills:external-agent-monitoring

Instrument external agents with OpenTelemetry for DataRobot observability. Supports LangGraph, CrewAI, LlamaIndex, PydanticAI, and others.

application/ai-skill artifact →

datarobot-agent-assist

urn:ai:github.com:datarobot-oss:datarobot-agent-skills:agent-assist

Build and deploy AI agents on DataRobot. Supports LangGraph, CrewAI, LlamaIndex, and base agents with MCP server and React frontend bundling.

application/ai-skill artifact →

How it is served

The publishing guide asks for three things at the transport layer, because a crawler is the consumer that matters and a crawler is a browser-shaped client.
Evidence. Fetched https://www.datarobot.com/.well-known/ai-catalog.json on 2026-07-31, HTTP 200. The verbatim body is stored alongside its manifest in the DataRobot repository as ai-catalog/datarobot-ai-catalog.json. Nothing on this page is derived or generated: an AI Catalog manifest is served from the publisher’s own domain or it does not exist, which makes it — like an A2A Agent Card — one of the few agent artifacts that cannot be produced on a provider’s behalf. Grades are recomputed on every build; the specification is a v0.9 draft and these verdicts will move when it does.

Work with this as data

Every descriptor here is available over the APIs.io API and to AI agents over MCP. Agent Discovery is not yet its own endpoint on the v1 API. Reach it through catalog search and the tag graph, or the MCP server.

MCP server

One button, every client — Claude, Cursor, VS Code and the rest.

https://apis.io/mcp

Tools for agent discovery

3 MCP tools reach this
  • apis_io_searchSTART HERE — APIs, providers and tags for one query, each with its total.
  • resolveTurn a domain, URL or GitHub org into the provider it belongs to.
  • find_cohortsEvery scored population of providers in the catalog.
All 92 tools

Call it yourself

curl for this page
Search the catalog
curl "https://apis.io/api/v1/search?q=datarobot&limit=10"
Everything under a tag
curl "https://apis.io/api/v1/tags/datarobot"

Discovery needs no key. Ratings and market analysis are Pro.

Get an API key

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