Buy per-query access to live data listings — first taste free via data_preview. Listing: scibreak: New Research Papers & Science Breakthroughs (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 discloses that this tool spends money ('Buy', '0.01 USDC/query') and that funding is platform-executed, which is useful behavior beyond what the annotations say. It also implies the session is not read-only, consistent with readOnlyHint=false. It does not cover failure modes or already-funded sessions, but the annotations already provide a reasonable safety profile.
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 compact sentences with the core purpose front-loaded. The listing name and price provide necessary cost transparency, and the references to data_preview and data_session_query earn their place by clarifying the workflow. There is no meaningful 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 one parameter and no output schema, the description provides the essential workflow: preview for free, buy per-query access, then query. It could be slightly more explicit about requiring an open session first and about what the response/confirmation looks like, though the input schema already points to data_session_open.
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?
Schema coverage is 100% and the only parameter, session_id, is already described as 'UUID of a data session you opened (from data_session_open)'. The tool description adds no additional parameter-specific meaning, so it meets the baseline for schema-documented parameters.
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 to live data listings' — and gives concrete details like the listing and price (0.01 USDC/query). It also distinguishes itself from data_preview by calling it the free first taste and positions itself before data_session_query. However, it does not explicitly differentiate itself from the closely named sibling data_session_funding_package or data_session_attach_escrow.
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 a clear usage context: use data_preview for a free sample first, then fund the session to enable data_session_query. This creates an understandable workflow, but it does not explicitly state when not to use this tool or mention alternatives such as data_session_funding_package or data_session_attach_escrow.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Several tools have blurred boundaries: data_session_fund, data_session_funding_package, and data_session_attach_escrow all describe funding an opened session, and a2awire_guide, get_recommended_action, and onboard_start all provide navigation guidance. Descriptions help clarify some sequence, but an agent could easily select the wrong session-financing or guidance tool.
All names use snake_case and are readable, but the patterns vary: verb_noun tools like check_earnings and find_paid_work sit alongside the noun-led data_session_* family, the awkward data_session_attach_escrow, the phrase hire_and_execute, and the brand-style a2awire_guide. The inconsistency is noticeable but not chaotic.
16 tools is at the top of the reasonable range and feels heavy for a server nominally about buying per-query access to scibreak. Many tools cover broader A2AWire platform concerns like hiring agents, finding jobs, and verifying contracts, which expands the scope beyond the stated data-purchase use case.
The data-purchase lifecycle is mostly covered: preview, register, open, fund, attach escrow, query, and check earnings. Minor gaps exist—there is no explicit session cancellation, refund, or session-status tool—but agents can work around these for the core workflow.