Search 53K+ museum artworks from Alexandria Aeternum (MET, Chicago, NGA, Rijksmuseum, Smithsonian, Cleveland, Paris). FREE. (FREE)
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Max results (1-100) | |
| query | Yes | Search query (e.g. 'impressionist landscape', 'Monet', 'Dutch Golden Age') | |
| museum | No | Filter by museum (met, chicago, nga, rijks, smithsonian, cleveland, paris) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, covering the safety profile. The description adds the specific data sources (MET, Chicago, NGA, etc.) and the volume (53K+), but does not disclose behavioral traits like rate limits, pagination, or return format. It does not contradict annotations.
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 first sentence is efficient and front-loaded with purpose. The second sentence 'FREE. (FREE)' is redundant and adds no value, a minor flaw. Overall, the description is short and mostly concise, with one piece of waste.
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?
The tool is simple with 3 well-documented parameters and full annotation coverage. The description adds the museum sources and scale, which is useful context. Without an output schema, the description doesn't need to explain return values. A small gap is that the return format is not mentioned, but schema and simplicity make this acceptable.
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 100%, so all three parameters (query, limit, museum) have descriptions in the schema. The tool description adds no extra parameter-level semantic detail beyond the schema. Baseline is 3 given high schema coverage.
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's function: 'Search 53K+ museum artworks' with a specific resource (museum artworks) and scope (the listed museums). This distinguishes it from sibling tools like get_artwork (which likely fetches a specific artwork) and search_tools (which searches for tools). The verb 'search' and the resource are explicit and unambiguous.
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 implies usage is for searching museum artworks but does not explicitly state when to use this tool versus alternatives. No exclusions or comparisons to siblings are provided. The context is clear from the name and description, but the guidance is not explicit.
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 distinct purposes, but there is some overlap between get_artwork and get_artwork_oracle, which both retrieve artwork metadata with different detail levels, potentially causing confusion. Other tools like enrich_metadata and infuse_metadata also have related but distinct functions, but descriptions help clarify differences.
Tool names generally follow a consistent verb_noun pattern (e.g., check_balance, delete_asset, resize_image), with minor deviations like mockup_image (noun_verb) and get_artwork_oracle (longer compound name). Overall, the naming is readable and predictable, though not perfectly uniform.
With 27 tools, the count is borderline high for a single server, as it covers a broad range of functionalities from artwork retrieval to image processing and compliance. While each tool seems useful, the scope feels heavy and could overwhelm agents, suggesting it might be better split into more focused servers.
The tool set provides comprehensive coverage for digital asset management, artwork analysis, and image processing, including CRUD operations (save_asset, get_asset, list_assets, delete_asset), metadata enrichment, compliance, and various image utilities. No obvious gaps are present for the stated domain.