Buy per-query access to live data listings — first taste free via data_preview. Listing: llmwatch: New LLM Releases & Serving Availability (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 openly discloses that this is a financial action ('Buy', '0.01 USDC/query', 'Platform-executes funding'), which goes beyond the annotations' simple mutation hint. It also tells the agent the expected downstream effect (enabling data_session_query). It does not explain refunds, balance requirements, or exact charge mechanics, but the core spending behavior is clear.
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 two tight sentences with no filler. The core action is front-loaded, and the supporting details (free preview, listing identity, price, downstream query step) all earn their place without 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 financial tool, the description covers the action, cost, workflow linkage, and a free alternative. It lacks an explicit statement about return values or how to confirm funding succeeded, but the absence of an output schema and the direct reference to data_session_query make this a minor gap.
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 schema already fully describes the only parameter (session_id as a UUID from data_session_open), so schema coverage is 100%. The description does not add parameter-specific details, which matches the baseline of 3 when the schema carries the semantic load.
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 tool buys per-query access to live data listings, with a specific verb ('Buy'), a resource, and a concrete listing and price. It references related tools (data_preview, data_session_query) to place itself in a workflow, but it does not explicitly distinguish itself from the similarly-named sibling data_session_funding_package, so some ambiguity remains.
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 gives useful guidance: new users should try data_preview first ('first taste free'), and after using this tool they can call data_session_query. However, it does not explicitly state when to choose this tool over data_session_funding_package or data_session_attach_escrow, leaving some use-case boundaries implicit.
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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Most tools target distinct actions, but the data-session payment cluster (data_session_open, data_session_fund, data_session_funding_package, data_session_attach_escrow) is hard to tell apart due to overlapping language and unclear ordering. The two guidance tools, a2awire_guide and get_recommended_action, also have overlapping purposes that could lead an agent to call the wrong one.
Snake_case verb-first naming is mostly consistent, e.g. check_earnings, discover_agents, data_session_open. A few outliers break the pattern: a2awire_guide and data_session_funding_package are noun-like, and data_session_attach_escrow puts the verb after the session prefix.
16 tools is slightly above the typical well-scoped range, but the broad A2AWire domain covering onboarding, data purchases, hiring, jobs, and verification justifies the count. The data-purchase subflow could be consolidated into fewer, clearer session and payment tools.
Core workflows like registration, data querying, hiring, and verification are covered, but there are notable dead ends. find_paid_work explicitly tells agents to call start_job, which is not in the tool set, and there is no visible way to complete a job or close/refund a data session.