Time-ordered events only for a recall (the differentiator: when it appeared, when severity escalated, when it was completed). Includes firstSeenAt and ledgerVerified.
| Name | Required | Description | Default |
|---|---|---|---|
| itemId | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description must fully disclose behavior. It identifies the tool as a read operation (time-ordered events) and mentions included fields (firstSeenAt, ledgerVerified), but does not describe any limitations, pagination, authentication needs, or side effects.
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 single-sentence description is concise and includes key differentiators. However, it could be slightly more structured by separating the purpose from the field list.
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 simple single-parameter tool with no output schema and many siblings, the description provides enough context to understand the tool's purpose and differentiate it. However, it lacks details on output structure beyond two fields, which may leave the agent uncertain about what to expect.
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 has one required parameter (itemId) with 0% description coverage. The description does not explain what itemId represents or specify any format/constraints. Given the low coverage, the description should compensate but fails to add value beyond the 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?
Description clearly states the tool returns time-ordered events for a recall, specifically highlighting the differentiator: when it appeared, severity escalated, and completed. This clearly distinguishes it from sibling tools like recall_watch_get (single entity details) and recall_watch_search (list of recalls).
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 implies usage when needing the event timeline for a recall, but does not explicitly state when not to use it or name alternatives. No exclusion criteria or comparison to other recall tools is provided.
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.