Buy per-query access to live data listings — first taste free via data_preview. Listing: RiverWatch: USGS river levels & stream-flow gauges (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?
注解已声明 readOnlyHint=false、idempotentHint=false，描述在此基础上补充了有价值的财务行为信息：这是付费操作（0.01 USDC/query）且每次会话限 20 次查询，这些是注解未覆盖的关键上下文。但'Open a prepaid session, then fund and query' 存在内部矛盾——既称预付又说开后再注资，且未说明重复调用或失败时的行为。
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?
两句话承载了目的、免费替代品、定价、会话上限和后续流程，核心目的前置在第一句，信息密度高且无冗余。第二句嵌套括号'0.01 USDC/query (max 20 queries/session)'略显笨拙，但整体结构紧凑。
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?
该工具涉及付费与会话生命周期（open→fund→query），共 5 个参数且无输出 schema，复杂度中等偏高。描述覆盖了高层流程、定价和 listing 信息，但未说明成功打开后返回什么（后续 fund/query 需要会话标识）、open_tx_hash 与 proof_escrow_id 的语义，也未澄清预付与注资的真实顺序——代理仅凭此描述难以完整、正确地完成调用。
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 参数描述覆盖率为 0%，描述需完全承担参数解释责任。描述仅通过'Listing: RiverWatch'映射了 listing_id，用'max 20 queries/session'部分解释了 max_queries（且该值与 schema 允许的 maximum 50 存在潜在冲突）。buyer_address、open_tx_hash、proof_escrow_id 三个参数完全没有得到任何解释。
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?
描述以'Buy per-query access'和'Open a prepaid session'明确指向打开数据会话这一操作，并具体到 RiverWatch/USGS listing。'first taste free via data_preview' 直接与兄弟工具 data_preview 区分开，说明这是付费路径，区别于免费的预览工具。但'Buy'与'Open'双动词表述略微分散，且嵌入特定 listing 的价格细节，使核心用途不如单一动词+资源那样聚焦。
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?
描述给出了清晰的使用顺序：先用 data_preview 免费试尝，再用本工具打开会话，随后 fund 和 query——这隐式指定了何时使用本工具而非免费的 data_preview 或后续的 data_session_fund/query。但缺少显式的排除条件（如何时改用 data_session_attach_escrow），指引是流程式的而非条件式的。
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 occupy overlapping roles: data_session_fund, data_session_funding_package, and data_session_attach_escrow all describe funding or payment for a data session, while a2awire_guide, get_recommended_action, and onboard_start all point toward 'what to do next.' An agent could easily misroute payment or onboarding intent.
Most names follow a snake_case verb_noun pattern like data_session_open, find_paid_work, and verify_contract. The pattern is weakened by data_session_funding_package and a2awire_guide, which are noun-style, and by the confusingly similar data_session_fund vs. data_session_funding_package.
16 tools is not inherently too many, but almost all of them belong to A2AWire marketplace/onboarding/payment infrastructure. Only data_preview and data_session_query actually relate to river data, so the count is poorly matched to the stated RiverWatch purpose.
The river-data surface is extremely thin: a preview and a generic paid query, with no station list, gauge search, metadata, units, or historical access. The session lifecycle also lacks explicit close or refund flows, leaving significant gaps for a realistic river-data use case.