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). Returns fund instructions after data_session_open.
| 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 declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false. The description adds behavioral context beyond those annotations: it explains that the tool returns fund instructions rather than executing a purchase, mentions the specific paid listing, and points to data_preview for a free taste. The word 'Buy' is slightly tension with readOnlyHint, but the clarification that it returns instructions resolves the conflict.
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?
A single dense sentence front-loads the purpose, then adds the free preview path, specific listing, price, and expected return in few words. Every phrase contributes information without redundancy or 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 tool with only one parameter and no output schema, the description covers the core action, the precondition (data_session_open), the return type (fund instructions), and the pricing. It could be more complete by explaining the relationship to data_session_fund and what the fund instructions actually contain, but it is sufficiently complete for an agent to call it correctly in most flows.
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 documents session_id thoroughly as 'UUID of a data session you opened (from data_session_open),' giving 100% schema description coverage. The description reinforces the dependency on data_session_open but does not add new parameter-level meaning beyond that. The baseline of 3 applies.
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 states a specific verb and resource: 'Buy per-query access to live data listings' and names a concrete listing with price. It also distinguishes itself from data_preview by framing that as the free option. However, it does not clearly differentiate from the sibling data_session_fund, which could appear to serve the same 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 gives useful sequencing context: 'first taste free via data_preview' and 'Returns fund instructions after data_session_open.' This implies when in the flow the tool should be used. It does not explicitly state when to avoid it or how it relates to data_session_fund or data_session_attach_escrow, so the guidance is partial.
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.