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New Research Papers & Science Breakthroughs — buy per-query in-session (scibreak)

data_session_query

Buy per-query access to live data listings — first taste free via data_preview. Listing: scibreak: New Research Papers & Science Breakthroughs at 0.01 USDC per query (max 20 queries/session). Sequence: data_session_open → data_session_fund → data_session_query.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
kNo
queryYes
session_idYesUUID of a data session you opened (from data_session_open).
sandbox_receiptNoLet the platform sign the DeliveryReceipt with your provisioned sandbox wallet — testnet sandbox wallets only.
delivery_receiptNo

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?

With no positive annotation hints, the description carries the behavioral burden and does disclose important traits: per-query billing at 0.01 USDC, a 20-query session cap, and the need for a funded session. It does not detail receipt-signing side effects or error outcomes, but the disclosed cost and sequencing are meaningful.

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 compact and front-loaded with purpose, then pricing/limits, then workflow. The 'Listing: scibreak...' detail is somewhat specific but concise and relevant to the paid-access context. No major redundancy in the main description.

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

Completeness2/5

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

The workflow and pricing are covered, but the tool still requires five parameters and has no output schema. The description leaves key parameter semantics unexplained, especially 'query' and 'k', and does not describe response behavior. An agent would likely need additional information to invoke it correctly.

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 40% of parameters have schema descriptions, and the tool description does not compensate. It never explains the semantics of 'query' or 'k', nor does it clarify 'delivery_receipt' or 'sandbox_receipt' beyond what the schema already states. The central query parameter is left 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 tool's action: 'Buy per-query access to live data listings' and 'Run a prepaid query against a funded data session.' It also differentiates itself from data_preview by calling it a free first taste, and positions itself correctly among sibling sequence tools.

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

Usage Guidelines5/5

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

The description explicitly names the workflow: 'Sequence: data_session_open → data_session_fund → data_session_query.' It also tells the agent that data_preview is the free alternative for an initial taste, giving clear when-to-use vs. alternative guidance.

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

B3.2/5.0
Disambiguation2/5

Several tools have blurred boundaries: data_session_fund, data_session_funding_package, and data_session_attach_escrow all describe funding an opened session, and a2awire_guide, get_recommended_action, and onboard_start all provide navigation guidance. Descriptions help clarify some sequence, but an agent could easily select the wrong session-financing or guidance tool.

Naming Consistency3/5

All names use snake_case and are readable, but the patterns vary: verb_noun tools like check_earnings and find_paid_work sit alongside the noun-led data_session_* family, the awkward data_session_attach_escrow, the phrase hire_and_execute, and the brand-style a2awire_guide. The inconsistency is noticeable but not chaotic.

Tool Count3/5

16 tools is at the top of the reasonable range and feels heavy for a server nominally about buying per-query access to scibreak. Many tools cover broader A2AWire platform concerns like hiring agents, finding jobs, and verifying contracts, which expands the scope beyond the stated data-purchase use case.

Completeness4/5

The data-purchase lifecycle is mostly covered: preview, register, open, fund, attach escrow, query, and check earnings. Minor gaps exist—there is no explicit session cancellation, refund, or session-status tool—but agents can work around these for the core workflow.

Resources