Verify the hash-chain integrity of a recall record (tamper detection). Returns chainValid, brokenAt (if any), checked event count, firstSeenAt and ledgerVerified.
| Name | Required | Description | Default |
|---|---|---|---|
| itemId | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so the description carries full behavioral disclosure burden. It mentions return fields (chainValid, brokenAt, etc.) but does not discuss side effects, idempotency, permissions, or whether it is read-only. The return list is helpful but insufficient for full transparency.
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 a single sentence followed by a list of return fields. It is front-loaded and free of fluff. Every part contributes to understanding the tool, though the return field list could be formatted more compactly.
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 a simple tool (1 param, no output schema, no annotations), the description covers purpose and return values adequately. However, it does not explain 'hash-chain integrity' or how to interpret 'brokenAt', leaving some gaps for a complete understanding.
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?
The sole parameter 'itemId' has no schema description (0% coverage), and the tool description only implies it identifies a recall record. No format, source, or example is given, so the description adds minimal meaning beyond the parameter name.
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: 'Verify the hash-chain integrity of a recall record (tamper detection).' It uses a specific verb ('verify') and resource ('recall record'), and the parenthetical distinguishes it from other verify_ledger tools by specifying the record type.
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., other verify_ledger tools or recall_watch_get/search). The description does not mention prerequisites, when not to use it, or context for choosing it over siblings.
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.