Extract a normalized product (name, price, currency, availability, brand, GTIN, ...) from Schema.org / JSON-LD markup. Provide a url to fetch or raw html. Read-only; price 0.0 (free).
| Name | Required | Description | Default |
|---|---|---|---|
| url | No | Product page URL to fetch (one of url / html) | |
| html | No | Raw page HTML to parse (one of url / html) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the burden. It declares read-only and free behavior, which is helpful. However, it does not disclose error handling, rate limits, or what happens for invalid markup. The behavioral disclosure is minimal but accurate.
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 extremely concise—two short sentences. It front-loads the verb and resource, includes key details (fields extracted, input requirements), and contains no unnecessary information. Every word earns its place.
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?
Despite having no output schema, the description only partially describes the output (list of fields with ellipsis). It doesn't explain the return format (e.g., JSON), error conditions, or what happens if no markup is found. Given the tool's simplicity, this is adequate but not fully complete.
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 input schema covers 100% of parameters with descriptions, but the description adds the important constraint that exactly one of url or html should be provided (mutual exclusivity). This semantic guidance is not present in the schema, adding value.
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 extracts a normalized product from Schema.org/JSON-LD markup, listing specific fields. It distinguishes from other commerce catalog tools (e.g., availability_check, price_compare) by focusing on structured data extraction. However, it could be more explicit about its uniqueness among siblings.
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 provides context for use (when you have a URL or HTML with markup) and notes it is read-only and free. It does not explicitly state when not to use this tool or suggest alternative tools, leaving some ambiguity.
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.