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Trending AI Papers — buy per-query in-session (hfpaperwatch)

data_session_fund

Idempotent

Buy per-query access to live data listings — first taste free via data_preview. Listing: hfpaperwatch: Trending AI Research Papers (HuggingFace Daily Papers) (0.01 USDC/query). Platform-executes funding so you can data_session_query.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
session_idYesUUID of a data session you opened (from data_session_open).

Schema Changelog

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

  1. First observed

TDQS

A3.8/5.0
Behavior3/5

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

Annotations already cover idempotency and non-destructiveness, lowering the burden on the description. The description adds that this is a paid, platform-executed funding action with a specific price, and that it enables querying. It does not disclose details like balance effects, refunds, or what happens on repeated funding, but 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.

Conciseness5/5

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

The description is only two sentences and front-loads the core purpose. It includes the relevant listing details, pricing, the free-preview alternative, and the dependent query tool without filler or redundancy.

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 single-parameter tool with full schema coverage and safety-related annotations, the description is mostly complete: it explains what the tool does, what it costs, and how it leads to querying. The only notable gap is the lack of clarification between this tool and the similar funding/escrow sibling tools, which keeps it from being fully complete.

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?

The schema fully describes the single session_id parameter, including its UUID format and origin from data_session_open. Since schema description coverage is 100%, the description does not need to add much. It provides no additional parameter-level meaning beyond what the schema already states.

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 states a specific action ('Buy per-query access to live data listings') and names the exact listing and price, making the tool's purpose concrete. It also connects the action to the downstream data_session_query tool. However, it does not differentiate this tool from closely related siblings like data_session_funding_package or data_session_attach_escrow.

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 gives some usage context: use data_preview for a free first taste, then fund access, then use data_session_query. It clearly identifies an alternative for the free tier and the intended follow-up action. It stops short of explicitly saying when not to use this tool versus the other funding-related siblings.

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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