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

data_session_open

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 (max 20 queries/session)). Open a prepaid session, then fund and query.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
listing_idNoUUID of the listing. Provide exactly one of listing_slug or listing_id.
max_queriesNo
listing_slugNoPublic listing slug (from benchmarks_get / data_directory_get). Provide exactly one of listing_slug or listing_id.
open_tx_hashNo
buyer_addressNoBuyer EVM address. Optional: defaults to your own platform wallet when omitted.
proof_escrow_idNo

Schema Changelog

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

  1. First observed

TDQS

A4/5.0
Behavior4/5

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

Annotations only mark readOnlyHint=false and idempotentHint=false; the description adds real behavioral context: this is a paid operation (0.01 USDC/query), capped at 20 queries/session, requires opening a prepaid session, and must be funded before querying. This is meaningful beyond what the annotations convey, though it could disclose return/payment details more fully.

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?

Three sentences with no wasted words: purpose, free alternative, listing identity, pricing, cap, and workflow are all packed in. The most important action ('Open a prepaid session') appears near the end but is preceded by context that earns its place.

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

Completeness3/5

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

For a six-parameter, paid, multi-step workflow with no output schema, the description gives a usable open→fund→query sequence and the schema covers listing identification and buyer default. However, it does not state what a successful open returns, and open_tx_hash/proof_escrow_id remain unexplained, leaving gaps an agent must resolve elsewhere.

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

Parameters2/5

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

Only 50% of parameters have schema descriptions, and the tool description does not compensate. It never explains max_queries, open_tx_hash, or proof_escrow_id, and the 'max 20 queries/session' phrase is a listing constraint rather than parameter guidance. The concrete slug 'hfpaperwatch' is helpful for listing_slug, but the description leaves several parameters under-specified.

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 clearly states the action ('Open a prepaid session') and the resource ('per-query access to live data listings'), and names the exact listing with price and max-queries context. It differentiates itself from data_preview ('first taste free') and from later steps ('then fund and query'), so an agent can tell it apart from sibling session tools.

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?

It explicitly directs users to data_preview for the free first taste, establishing when NOT to open a paid session. The 'then fund and query' clause orders it before data_session_fund and data_session_query, though it does not explicitly address alternatives like attach_escrow or when to stop using this tool.

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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