Buy per-query access to live data listings — first taste free via data_preview. Listing: mitwatch: MIT Research & Science News (0.01 USDC/query). Platform-executes funding so you can data_session_query.
| Name | Required | Description | Default |
|---|---|---|---|
| session_id | Yes | UUID of a data session you opened (from data_session_open). |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already mark this as non-read-only, non-destructive, and idempotent. The description adds context that funding is platform-executed and aligns with the expected flow, but does not detail side effects like charge failures or authorization requirements. Still, it provides useful behavioral context beyond annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is compact and information-dense. Each clause serves a distinct function: stating the action, giving the specific listing and cost, and relating to other tools. No unnecessary words or redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple one-parameter tool without an output schema, the description provides all necessary context: the purpose, the exact listing and price, the relationship to preview and query tools, and the platform-executed nature. An agent has sufficient information to decide when and how to invoke it.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The sole parameter session_id is fully described in the schema (UUID of a data session opened from data_session_open). The tool description does not add additional parameter-specific information, so it meets the baseline for full schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action (buy per-query access), the specific resource (live data listings, specifically mitwatch: MIT Research & Science News), the cost (0.01 USDC/query), and distinguishes it from the free preview (data_preview) and the query tool (data_session_query). This provides a precise and unambiguous purpose.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly guides when to use this tool: after a free preview via data_preview, to enable data_session_query. It names the alternative for free access and implies the sequential flow. This gives clear usage conditions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.