Search Raywake AI image, video, and audio models by query, category, or modality to compare indicative starting prices in USD before requesting a quote.
Free. Search Raywake AI models; returns indicative starting prices in USD. Use get_model before quote. Modality filters category/tags locally before pagination.
| Name | Required | Description | Default |
|---|---|---|---|
| page | No | ||
| query | No | ||
| category | No | ||
| modality | No |
Changes observed during successful MCP inspections.
v0.1.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already cover read-only, idempotent and non-destructive, so the bar is lower, yet the description adds real context: the tool is free, prices are 'indicative starting prices' rather than quotes, and modality filtering happens locally before pagination. That last point is a non-obvious behavioral trait an agent would otherwise have to discover empirically.
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?
Four short sentences, front-loaded with the verb and cost signal, with no filler. The telegraphic style ('Use get_model before quote') is slightly ambiguous but earns its brevity.
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?
With no output schema, the description should say more about the shape of results; it only mentions indicative prices. It is adequate for a discovery call but leaves result fields, pagination limits and empty-result behavior unstated.
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 description coverage is 0%, so the description must carry parameter meaning. It only clarifies modality's local-filtering behavior and its interaction with pagination; query, category and page are left entirely undocumented, and it's unclear whether category is exact-match or full-text.
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?
States a specific verb and resource ('Search Raywake AI models') and what comes back (indicative starting prices in USD). It signals the search-vs-detail split with get_model, though it doesn't explicitly distinguish itself from list_categories.
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?
'Use get_model before quote' establishes a workflow around the tool, implying search is the discovery step and get_model the detail step. However, there is no explicit statement of when to prefer this over list_categories or when not to use it, so guidance is implied rather than stated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.