Peekaboo MCP

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries full burden and does well by explaining capabilities (image understanding, OCR, flexible AI configuration), supported file types, and example usage. It mentions server configuration dependencies but could be more explicit about potential limitations like image size constraints or rate limits.

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 appropriately sized and well-structured with clear sections: purpose statement, usage context, capabilities list, and example. The capabilities section could be more concise, but overall it's front-loaded with essential information and every sentence adds value.

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 tool with 3 parameters, 100% schema coverage, but no annotations or output schema, the description does well by explaining capabilities, usage context, and providing concrete examples. It could be more complete by mentioning potential error cases or response format expectations, but covers most essential aspects given the complexity.

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 the baseline is 3. The description adds some value by explaining the purpose of parameters in context (e.g., 'question' parameter examples, 'provider_config' flexibility), but doesn't provide significant additional semantics beyond what's already well-documented in the schema.

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 analyzes pre-existing image files using AI models, specifying the resource (image files) and verb (analyze). It distinguishes from sibling tools 'image' and 'list' by focusing on AI-powered analysis rather than basic image operations or listing functions.

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 explicitly states when to use this tool: 'when an image already exists (e.g., previously captured, downloaded, or generated) and you need to understand its content, extract text, or answer specific questions about it.' It provides clear context for usage without needing to mention specific exclusions since the scope is well-defined.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.