HuggingFace New Dataset Release Tracker (hfdatasets)

get_agent_contract

Read-onlyIdempotent

✅ No API key needed — call this now. Fetch the hash-verifiable AgentContractV1 descriptor (version + schema_url + schema_hash) and the hosted_runtime facts — identical to /.well-known/agent.json. Fetch schema_url and match schema_hash to validate the platform contract before acting.

Input Schema

TableJSON Schema

Name	Required	Description	Default
No arguments

Output Schema

TableJSON Schema

Name	Required	Description	Default
`schema_url`	Yes
`schema_hash`	Yes
`runtime_types`	Yes
`hosted_runtime`	No
`agent_contract_version`	Yes

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

First observedSep 6, 2026

TDQS

A4.2/5.0

Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already mark it readOnly, openWorld, idempotent, and non-destructive. The description adds behavioral value by revealing the response is hash-verifiable and identical to a known well-known endpoint, plus the no-API-key property, which is not present in annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is short and information-dense, with the key 'no API key' call-to-action up front. The second sentence partially repeats schema_url/schema_hash from the first, so a small redundancy prevents a higher score.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a zero-argument, read-only tool with a provided output schema, the description explains what the tool returns, the source equivalence, the authentication requirement, and how to use the result. Nothing essential is missing for an agent to call and interpret this tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

With zero parameters, the schema fully covers inputs and the description correctly notes the owner is derived from the authenticated principal. There is nothing for the description to add beyond confirming no arguments are required.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description names a specific resource (AgentContractV1 descriptor with version + schema_url + schema_hash) and hosted_runtime facts, using a clear verb ('Fetch'). It also disambiguates by noting it is identical to /.well-known/agent.json, which gives an agent a concrete anchor for what the tool returns.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

It provides useful context: 'No API key needed — call this now' and advises validating the platform contract before acting. However, it does not explicitly state when not to use this tool or name alternatives, especially given the garbled sibling list.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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TDQS

B3.1/5.0

Disambiguation2/5

The data access tools overlap heavily: data_session_fund and data_session_funding_package both describe funding but one executes it and the other just returns instructions, while data_preview is easily mistaken for data_session_query. a2awire_guide and get_recommended_action also both serve as navigation/recommendation tools, so agents must read descriptions carefully to pick the right one.

Naming Consistency3/5

Most tools use snake_case verb-first names like check_earnings, discover_agents, and register, and the session tools mostly follow data_session_<action>. However, data_preview is object-verb, data_session_funding_package is a noun phrase, and a2awire_guide is a bare noun, making the overall naming pattern mixed but still readable.

Tool Count2/5

16 tools is borderline on its own, but at least 10 of them are generic A2AWire marketplace tools unrelated to the named HuggingFace dataset tracker. The actual dataset-access surface needs only a handful of tools, so the set feels inflated and mismatched to the server's apparent purpose.

Completeness2/5

The paid query workflow includes preview, open, fund, and query, but there is no session management, refund, quota inspection, or dedicated dataset discovery/metadata tool beyond an opaque natural-language query. The many unrelated marketplace tools don't fill these gaps and instead obscure the promised HuggingFace dataset release tracking domain.

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