Best-effort watermark and provenance-marker detection from the raw image bytes (e.g. C2PA / IPTC / XMP markers). Provide an image url. Read-only; price 0.0 (free).
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes | Image URL to inspect |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description adds 'Best-effort', 'Read-only', and 'price 0.0 (free)' – useful but incomplete. It does not disclose behavior on errors, missing watermarks, or output format, which would help an agent anticipate tool results.
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?
Two sentences, no extra words. The first states the function, the second provides usage instructions and cost. Every sentence 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?
For a simple tool with one parameter and no output schema, the description covers the essential purpose and input. It could be improved by hinting at the output (e.g., 'returns detected markers or confidence'), but overall it is sufficiently complete for its simplicity.
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 already fully describes the 'url' parameter as 'Image URL to inspect' (100% coverage). The description adds 'raw image bytes' context, but that is marginal – the baseline 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 clearly states the tool does 'watermark and provenance-marker detection' from image bytes, using examples like C2PA/IPTC/XMP. This distinguishes it from siblings like content_authenticity_ai_likelihood and content_authenticity_c2pa_inspect which focus on AI likelihood or full C2PA metadata.
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 tells the user to 'Provide an image url' and notes 'Read-only; price 0.0 (free)'. While it implicitly guides usage for watermark detection, it does not explicitly contrast with alternatives like content_authenticity_c2pa_inspect, 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.