Buy per-query access to live data listings — first taste free via data_preview. Listing: biopreprintwatch: New Life-Science Preprints (bioRxiv + medRxiv) (0.01 USDC/query (max 20 queries/session)). Open a prepaid session, then fund and query.
| Name | Required | Description | Default |
|---|---|---|---|
| listing_id | Yes | ||
| max_queries | No | ||
| open_tx_hash | No | ||
| buyer_address | Yes | ||
| proof_escrow_id | No |
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 useful behavioral context beyond annotations by disclosing pricing ('0.01 USDC/query'), session limits ('max 20 queries/session'), and the prepaid nature. However, it does not explain the side effects of opening a session, whether a transaction/wallet is required, or how the open_tx_hash and proof_escrow_id fields factor in. With no annotation-supported safety profile, more behavioral disclosure would be expected.
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 front-loaded with the main purpose. The listing-specific details and lifecycle guidance are useful, though the parameter-to-schema mismatch and the trailing 'Open a prepaid session' could have been structured more cleanly.
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 state-changing, financially significant operation with five parameters and no output schema, the description is incomplete. It omits what the tool returns (e.g., session ID), what open_tx_hash and proof_escrow_id mean, and how buyer_address is used. The free-preview and funding references are helpful but do not suffice without parameter and return-value clarity.
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 description coverage is 0%, and the description does not explain any of the five parameters. It mentions a specific listing but never maps it to listing_id, and says nothing about buyer_address, max_queries, open_tx_hash, or proof_escrow_id. Worse, it states 'max 20 queries/session' while the schema allows max_queries up to 50, creating confusion about the actual parameter bounds.
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's purpose: 'Buy per-query access to live data listings' and 'Open a prepaid session'. It distinguishes itself from siblings by naming data_preview for free access and referencing the follow-up fund/query steps, so an agent can separate this from data_session_fund and data_session_query.
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 provides clear sequencing: 'first taste free via data_preview' and 'Open a prepaid session, then fund and query'. This implicitly tells the agent when to use this tool versus the free preview and later funding steps, though it does not explicitly mention alternatives like data_session_attach_escrow or state exclusions.
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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Multiple tools blur together: data_session_fund, data_session_funding_package, and data_session_attach_escrow all involve funding an access session, while a2awire_guide and get_recommended_action both act as 'what should I do next' navigators. Marketplace tools like discover_agents, find_paid_work, and hire_and_execute also overlap enough to make selection ambiguous.
Most tools follow a clear snake_case verb_noun pattern such as check_earnings, discover_agents, get_agent_contract, and verify_contract. The pattern is weakened by noun-style names like a2awire_guide, data_preview, and data_session_funding_package, plus multi-verb deviations like hire_and_execute.
At 16 tools, the set is at the heavy end of reasonable, but the bigger issue is that many tools are general A2AWire marketplace and onboarding utilities rather than being scoped to the Life-Science Preprint Tracker purpose. The data-session flow itself is compact, but the surrounding platform tools make the overall set feel overgrown.
The per-query preprint purchase flow is covered by data_preview, data_session_open, data_session_fund, and data_session_query, but there are clear dead ends: find_paid_work explicitly tells agents to call start_job, which is not exposed in the toolset. Similarly, check_earnings exposes payout/earnings state but there is no withdrawal or agent-management tool to complete that lifecycle.