Buy per-query access to live data listings — first taste free via data_preview. Listing: fdarecall: FDA recall enforcement database (food, drug, device) (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?
Annotations provide only default negative hints (readOnlyHint: false, etc.), so the description carries most of the behavioral burden. It adds useful context: pricing (0.01 USDC/query), a session cap (max 20 queries/session), and the workflow of opening then funding/querying. However, it does not disclose important behavioral details such as whether an on-chain transaction is required, what the return value/session identifier is, or what preconditions like open_tx_hash and proof_escrow_id imply.
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-loads the core purpose: 'Buy per-query access to live data listings.' The second sentence adds listing-specific pricing and a short workflow without excessive fluff. It is somewhat dense and mixes listing metadata with tool semantics, but every sentence earns its place.
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 five parameters, no output schema, and zero schema-level parameter descriptions, the description is incomplete. It establishes the high-level workflow and pricing but omits essential invocation details: how the buyer address is used, what open_tx_hash and proof_escrow_id represent, and what the tool returns after opening a session. An agent would still need substantial inference or external knowledge to call this correctly.
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%, so the description must compensate by explaining parameters. It names the specific listing_id value 'fdarecall' and implies max_queries via 'max 20 queries/session.' It says nothing about buyer_address, open_tx_hash, or proof_escrow_id, leaving three of five parameters unexplained and making correct invocation difficult.
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 identifies the action as opening or buying per-query access to a live data listing, and the domain is specific: 'fdarecall: FDA recall enforcement database.' The phrase 'Open a prepaid session' matches the tool name and distinguishes it from later workflow steps like funding and querying. It does not explicitly name sibling tools for differentiation, but the workflow contrast with data_preview is present.
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: try data_preview first for free, then open a prepaid session, then fund and query. This implies when to use the tool relative to siblings such as data_session_fund and data_session_query. It lacks explicit 'do not use when' exclusions, but the sequential guidance is strong enough to orient an agent.
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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The tool set blends FDA recall query tools with generic A2AWire marketplace tools, making purpose boundaries unclear. Multiple tools overlap: data_session_fund, data_session_funding_package, and data_session_open all describe payment/session setup, while a2awire_guide and get_recommended_action both serve as navigational helpers.
Some tools follow a verb_noun pattern (data_session_open, data_session_query, discover_agents), but others are inconsistent or vague (a2awire_guide, check_earnings, register, verify_contract). The mix of domain-specific and platform tool naming with no coherent convention makes the surface feel disjointed.
16 tools is not inherently excessive, but most are unrelated to FDA recall alerts; they cover agent registration, onboarding, escrow, hiring, and earnings. Only a handful actually concern the stated FDA recall data domain, so the count is poorly scoped for the server's apparent purpose.
For an FDA recall alert server, the surface is severely incomplete: there is no direct recall listing, search, filtering, or detail tool, only a generic data_session_query with preview. The remaining tools are platform infrastructure, leaving the actual recall domain shallow and dependent on an opaque paid query flow.