Search Japanese research-grant calls-for-proposals. Each hit includes firstSeenAt and ledgerVerified (hash-chain integrity).
| Name | Required | Description | Default |
|---|---|---|---|
| field | No | 研究分野 | |
| limit | No | ||
| query | No | ||
| since | No | ||
| funder | No | 配分機関 (JST/AMED/NEDO 等) | |
| status | No | ||
| amountMin | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, so the description bears full burden. It discloses that results include firstSeenAt and ledgerVerified fields, offering some transparency. However, it lacks details on pagination, sorting, error states, or rate limits.
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 (two sentences) and front-loaded with the purpose. However, it uses space to mention return fields, which could be replaced by more practically helpful details about usage.
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?
Given the complexity (7 parameters, no output schema, no annotations), the description is incomplete. It omits how to use parameters, response structure beyond two fields, and any constraints or prerequisites.
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?
With only 29% schema description coverage, the description does not compensate. It fails to explain any of the 7 parameters (e.g., query, limit, status) or their roles, forcing reliance on the sparse schema.
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 it searches Japanese research-grant calls-for-proposals, distinguishing it from sibling watch-search tools for other domains (e.g., bid_watch_search, landprice_watch_search). The verb 'search' and specific resource are explicit.
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?
No guidance on when to use this tool versus alternatives (e.g., grant_watch_get, grant_watch_timeline). No conditions or exclusions provided, leaving the agent to infer usage context.
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.
Most tools are clearly distinguished by domain prefixes (e.g., bid_watch, grant_watch) and specific action verbs. However, the high number of similarly structured watch tools could still cause confusion, though descriptions clarify exact purposes.
Every tool follows a consistent `domain_subdomain_action` pattern with underscores, e.g., `agent_audit_query`, `bid_watch_search`. Even long names like `commerce_catalog_agent_readiness_score` adhere to this structure.
With 147 tools, the server is far too broad, covering weather, carbon estimates, domain intel, and more—well beyond its stated 'Japan public-data ledgers' scope. This sheer volume overwhelms agents and dilutes focus.
The server offers many read-only tools for Japanese public data (bids, grants, licenses, etc.), but lacks create/update/delete operations for those domains. Additionally, numerous unrelated tools (e.g., carbon estimates, weather) feel tacked on, leaving gaps in core coverage.