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HuggingFace New Dataset Release Tracker (hfdatasets)

hire_and_execute

Destructive

Hire an agent from the marketplace to execute a task. Searches by capability, creates escrow, funds the escrow on-chain (USDC), executes the task, and returns the result. This is the one-call bridge for local orchestrators (Claude Code, Cursor, etc.) to use the marketplace.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
capabilityYesCapability to hire for, e.g. 'sentiment-analysis'
task_inputYesThe task to send to the hired agent
max_price_usdcNoMaximum price in USDC1.0

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
outputYes
agent_idYes
escrow_idYes
agent_nameYes
amount_paidYes
receipt_jwsNo
runtime_typeNo
invocation_idNo
compute_receiptNo

Schema Changelog

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

  1. First observed

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already flag the tool as destructive and not idempotent; the description adds meaningful behavioral detail by stating it creates escrow, funds it on-chain with USDC, and executes the task. This gives the agent a clear picture that real financial settlement occurs, which goes beyond the annotation flags.

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

Conciseness5/5

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

Two sentences with no filler: the first states the operational pipeline and the second states the intended integration context. Every clause earns its place and the most important action is front-loaded.

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

Completeness4/5

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

For a high-complexity tool involving escrow and on-chain payment, the description covers the full operation sequence and the intended caller, while the rich schema covers parameter semantics and an output schema is present for return details. It could be slightly stronger by explicitly warning about irreversible payment, but the destructive annotation covers that.

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

Parameters3/5

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

Schema description coverage is 100%, so the property descriptions already document capability, task_input, and max_price_usdc adequately. The tool description itself does not add param-level meaning, but the baseline of 3 applies because the schema carries the semantic load.

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 uses a specific verb ('hire') and resource ('agent from the marketplace'), then clearly enumerates the end-to-end pipeline: search, escrow creation, on-chain funding in USDC, task execution, and result return. It also differentiates from the lower-level sibling tools by branding this as the 'one-call bridge' for local orchestrators.

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

Usage Guidelines4/5

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

The description clearly scopes usage to local orchestrators wanting a single-call marketplace integration, implying it is the high-level alternative to composing multiple data_session_* calls. It does not explicitly name when not to use it or list alternative tools, so it falls just short of a 5.

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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