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Physics & Technology News — buy per-query in-session (physorgwatch)

data_session_query

Buy per-query access to live data listings — first taste free via data_preview. Listing: physorgwatch: Physics & Technology News 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.

  1. First observed

TDQS

A3.6/5.0
Behavior4/5

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

The description adds behavioral context beyond the annotations: it reveals per-query cost (0.01 USDC), a session cap (max 20 queries/session), and a payment implication ('buy access'). This supplements the minimal annotations (readOnlyHint false, destructiveHint false). It does not fully explain what happens on insufficient funds or how the data result is delivered, but it gives useful operational behavior not present in 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?

Three sentences and to the point. It front-loads the core action ('Buy per-query access'), then gives price and prerequisite sequence. The listing specifics are useful, though they may be subject to change; still, the structure is compact and no sentence is wasted.

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?

Given the tool has 5 parameters and no output schema, the description covers the pricing, session cap, and workflow order, which is fairly complete for calling it after having a funded session. But it does not explain what happens after the query, the return format, or how with 'delivery_receipt' factors in, leaving some practical gaps for an agent.

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?

With only 40% schema description coverage, the tool description should compensate by explaining key parameters. It does not: 'query', 'k', 'delivery_receipt', and 'sandbox_receipt' get no explanation in the description. The sequence hints at session_id, but overall the description adds little to parameter meaning beyond the schema's minimal descriptions.

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 names a specific resource (live data listings) and action (buy per-query access), and names the 'physorgwatch' listing. The explicit sequence 'data_session_open → data_session_fund → data_session_query' helps distinguish it from related session workflow tools, though the description itself leans more toward the commercial 'buy access' framing than the schema's clearer 'run a prepaid query.'

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 gives an explicit usage sequence (open → fund → query), telling the agent when this tool is appropriate in the workflow. It also points to data_preview for a free alternative ('first taste free'), providing a when-not-to-use signal. It does not cover all edge cases or exclusions (e.g., when to re-fund), but the core usage guidance is clear.

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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