Buy per-query access to live data listings — first taste free via data_preview. Listing: certfrwatch: CERT-FR (ANSSI) National Security Advisories (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?
The description adds meaningful behavioral details beyond annotations: it is a paid purchase (0.01 USDC/query), it targets a specific listing, and funding is platform-executed automatically. The annotations already cover read/write, idempotency, and destructiveness, so the additional cost and workflow context are valuable. No contradiction with 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, front-loads the action, and each clause earns its place: purpose, free-preview alternative, listing details, price, and next step. There is no redundant filler.
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 with a fully documented schema, the description covers the core purpose, cost, listing, and post-funding workflow. It does not describe return values or failure behavior, but no output schema exists and the missing details are minor for this level of complexity.
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 input schema has 100% description coverage for the single session_id parameter, so the schema already carries the parameter semantics. The tool description does not add further detail about the session_id parameter, which keeps this at baseline.
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 a specific action ('Buy per-query access'), a specific resource ('live data listings' / 'certfrwatch'), and the exact listing and pricing. It also differentiates from the free data_preview path and points to the follow-up data_session_query tool, making the tool's role easy to distinguish.
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?
It gives useful workflow context: try data_preview first for free, then use this tool to fund, then call data_session_query. However, it does not explicitly contrast this tool with sibling funding/escrow tools like data_session_funding_package or data_session_attach_escrow, so the when-not-to-use guidance is incomplete.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.