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Microsoft Research Blog — AI Research Announcements (msrwatch)

data_session_fund

Idempotent

Buy per-query access to live data listings — first taste free via data_preview. Listing: msrwatch: Microsoft Research Blog — AI Research Announcements (0.01 USDC/query). Platform-executes funding so you can data_session_query.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "session_id": "<session_id>"
    },
    "name": "data_session_fund"
  }
}

Input Schema

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

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.6/5.0
Behavior3/5

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

Annotations already declare this is a non-read-only, non-destructive, idempotent, closed-world operation, so the safety profile is covered. The description adds real value beyond that by disclosing the cost (0.01 USDC/query) and that the platform executes funding rather than the caller posting escrow manually — distinguishing it from data_session_attach_escrow. It says nothing about what happens on insufficient balance, whether duplicate calls re-charge, or confirmation behavior.

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 short clauses, front-loaded with the verb and with the cost and follow-up action kept tight; every sentence carries information. The em-dash construction is slightly informal but does not obscure meaning, and nothing is wasted.

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 one-parameter tool with no output schema and full annotation coverage, the description supplies the pieces an agent actually needs: price, payment handling, the free preview path, and the follow-up call. Missing only edge-case behavior for re-funding an already-funded session.

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?

There is a single parameter and schema description coverage is 100%, with the schema already stating it is a UUID from data_session_open. The description adds no additional meaning about the session_id beyond what the schema provides. Baseline 3 applies since the schema does the heavy lifting.

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?

States a concrete verb ('Buy per-query access') plus the resource (live data listings) and ties it to the mechanics ('platform-executes funding so you can data_session_query'), naming the specific listing and price. An agent can tell this is the payment step that unlocks querying. It stops short of a crisp statement that the tool funds a specific session identified by session_id.

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?

Clearly sequences the tool: preview free via data_preview, fund here, then call data_session_query. That gives both a cheaper alternative and a stated next step. It omits the exclusion case — e.g., do not call if the session is already funded — so when-not-to-use must be inferred.

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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