Recent approval / NHI-listed / price-revised events across all pharmaceutical records since the given ISO8601 timestamp. Each item includes firstSeenAt and ledgerVerified.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | ||
| since | Yes | ||
| category | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Describes the type of events (approval, NHI-listed, price-revised) and output fields (firstSeenAt, ledgerVerified), but does not disclose pagination behavior, authentication needs, rate limits, or whether it is read-only. Given no annotations, the description provides basic but insufficient behavioral context.
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 short (two sentences) and front-loaded with the core purpose. However, it sacrifices necessary detail for brevity, leaving gaps in parameter explanation and usage context.
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 tool has 3 parameters (including an undocumented 'category' string), no output schema, and no annotations, the description is incomplete. It does not explain the category parameter, the default limit, error handling, or ordering of results, leaving the agent with significant ambiguity.
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 description only indirectly references the 'since' parameter (ISO8601 timestamp) but does not explain the 'limit' parameter or the 'category' parameter at all. With 0% schema description coverage, the description adds minimal semantic value beyond what the schema already provides.
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 returns recent approval, NHI-listed, and price-revised events across pharmaceutical records. It specifies the time constraint (since ISO8601 timestamp) and mentions output fields, effectively distinguishing it from siblings like pharma_watch_search and pharma_watch_timeline.
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 explicit guidance on when to use this tool versus alternatives such as pharma_watch_search or pharma_watch_get. The description implies use for time-based recent changes but does not contrast with other tools or state prerequisites.
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 have clearly distinct purposes, especially the ledger-watch groups with domain prefixes. However, there are near-duplicate utilities such as content_authenticity_domain_reputation and domain_intel_reputation, and fx_tax_convert overlaps with price_oracle_fx_rate/convert. The sheer number of tools also increases the chance of selecting the wrong one, though descriptions are generally clear.
The naming is largely consistent with a <domain>_<action> or <domain>_<watch>_<action> pattern, and all names use snake_case. Minor deviations include standalone names like entity_search, kyb_report, verify_receipt, and the confusing singular/plural pair of sanction_watch_* and sanctions_screen_*. Overall, the pattern is predictable.
With 172 tools, this server is far beyond the typical well-scoped range. It bundles dozens of unrelated utility domains (weather, carbon, CVE, geo, etc.) alongside the Japan public-ledger watches, making it unwieldy for an agent to navigate. This extreme count is a major coherence problem.
For the core Japan public-ledger domain, coverage is excellent: each ledger has search, get, timeline, recent_changes, and verify_ledger, plus cross-ledger entity_search and temporal_query. The unrelated utility areas are also fairly complete for their own purposes, but the server's scope is so broad that some utilities are duplicated (e.g., multiple currency converters). Overall, no critical dead ends in the main domain.