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HuggingFace New Dataset Release Tracker (hfdatasets)

onboard_start

Read-onlyIdempotent

Where am I in onboarding? Returns your registered agents, their structured capability manifests, a progress checklist, the Base Sepolia testnet config, and exactly what you can do now vs. still need.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
agentsYes
statusYes
testnetYes
owner_idYes
checklistYes
rest_authYes
can_do_nowYes
still_neededYes
integration_verifiedYes

Schema Changelog

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

  1. First observed

TDQS

A3.7/5.0
Behavior3/5

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

Annotations already provide readOnlyHint, idempotentHint, openWorldHint, and destructiveHint=false, so the safety profile is well covered. The description adds useful content context — agents, manifests, checklist, testnet config — but discloses no additional behavioral caveats such as authentication requirements, rate limits, or side effects. There is no contradiction with the 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 a single well-structured sentence that front-loads the purpose and then lists the key outputs without excessive filler. It is slightly dense but each clause adds meaningful information, so no part feels wasted.

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 read-only, zero-parameter status tool with a rich output schema and strong annotations, the description provides everything an agent needs: no inputs, derived ownership, the exact contents of the response, and the practical value ('what you can do now vs. still need'). Nothing critical is missing.

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?

There are zero parameters, so parameter semantics are largely moot. The schema itself already states 'No arguments — the owner is derived from the authenticated principal,' and the description reinforces implicit ownership with 'your registered agents.' This matches the baseline for a zero-parameter tool.

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

Purpose4/5

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

The description opens with a clear orienting question, 'Where am I in onboarding?', and then enumerates the concrete outputs: registered agents, capability manifests, progress checklist, Base Sepolia testnet config, and actionable next steps. This makes the resource and scope unmistakable. It stops short of a 5 because it never names a sibling tool or explicitly draws a boundary against alternatives.

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?

The phrasing 'Where am I in onboarding?' gives a clear contextual trigger for when to use this tool. However, it does not explicitly state when not to use it, nor does it point to a more specific sibling tool for earnings, wallet, data preview, or attachment tasks. The usage guidance is implied rather than explicit.

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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