Resolve product stock availability to a coarse signal (in_stock / out_of_stock / limited / preorder / unknown), from a url, raw html, or inline product. Read-only; price 0.0 (free).
| Name | Required | Description | Default |
|---|---|---|---|
| url | No | Product page URL to fetch (one of url / html / product) | |
| html | No | Raw page HTML to parse (one of url / html / product) | |
| product | No | Inline normalized product object (one of url / html / product) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description explicitly states 'Read-only; price 0.0 (free),' which is good for transparency given no annotations. However, it does not disclose behavior for unreachable URLs, invalid input, or response structure beyond the coarse signal categories. More detail about error handling or default behavior would improve the score.
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 concise sentence that packs key information (purpose, input types, output signal, behavioral traits). It could be slightly more structured (e.g., separate sentences for input constraints), but it is front-loaded with the most important action.
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 three parameters and no output schema, the description lacks critical details about the return format (e.g., JSON structure, whether it returns a string or object). It also does not specify how the output signal is presented or any constraints on the product object input. This leaves the agent guessing about how to parse the result.
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 coverage is 100% with descriptions for each parameter. The description adds high-level context ('from a url, raw html, or inline product') but does not provide additional semantic details, such as expected formats, object structures, or how to choose among the three inputs. Baseline score of 3 is appropriate.
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 specifies the tool's exact function: resolving stock availability into a coarse signal with enumerated output values (in_stock, out_of_stock, limited, preorder, unknown). It lists the three input sources (url, html, inline product), distinguishing it from sibling tools like commerce_catalog_product_extract or commerce_catalog_price_compare.
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, nor when not to use it. The description implies use for stock availability checking, but it would benefit from context like 'Use this to check product availability; for full product details, see commerce_catalog_product_extract.'
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.