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 disclosing key behavioral traits: foreground/background capture options, output methods (file path or Base64), AI analysis when question provided, window shadow/frame exclusion, and auto-selection of AI providers. It misses some details like rate limits or specific error conditions.

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 front-loaded with core functionality, though it could be slightly more concise. Every sentence adds value: first states purpose, second details targets, third covers capture modes, fourth explains output, fifth describes analysis, sixth notes exclusions, seventh lists AI providers. Minor redundancy with schema exists.

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 5-parameter tool with no annotations and no output schema, the description provides good coverage of functionality, behavior, and context. It explains capture targets, focus behavior, output formats, and AI analysis integration. It could improve by detailing response structure or error handling, but it's largely complete for the tool's 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 schema already documents all 5 parameters thoroughly. The description mentions parameters like 'app_target', 'format', and 'question' but doesn't add significant meaning beyond what the schema provides. Baseline 3 is appropriate when schema does heavy lifting.

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 captures macOS screen content and optionally analyzes it, specifying targets (entire screen, specific app window, all windows of an app) and output methods. It distinguishes from sibling tools 'analyze' and 'list' by focusing on capture functionality with optional analysis, not pure analysis or listing.

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 provides clear context for when to use the tool (capturing screen content with optional AI analysis) and implies alternatives through sibling tools, but doesn't explicitly state when not to use it or directly compare to 'analyze' or 'list'. It gives practical guidance on target selection and output formats.

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