Diagnose Error Screenshot

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It only says 'Analyze' without explaining what output to expect (e.g., a diagnosis, suggested fixes, or extracted text details). It also does not mention whether the tool performs OCR, reasons about the error, or provides step-by-step solutions. This is a significant gap for a tool with no annotations and no output schema.

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 a single, focused sentence that front-loads the core action and enumerates all relevant input types. It contains no filler words, repetitions, or extraneous details, earning its place efficiently.

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?

Despite high schema coverage and a clear purpose, the description lacks essential context for an AI agent: it does not specify what the tool returns (no output schema), whether it generates fixes or explanations, or how to handle optional parameters like question and detail. Given the tool's specialized diagnostic function, more behavioral detail is needed for complete invocation guidance.

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 parameter descriptions in the schema already document all five parameters (image, model, detail, question, max_tokens). The tool description adds no extra meaning beyond the schema, but the high coverage means the baseline score 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 uses a specific verb ('Analyze') and resource ('error screenshots, stack traces, console output, IDE errors, terminal failures, and crash dialogs'), clearly distinguishing it from general image tools like analyze_image and extract_text_from_image. It enumerates exactly what input types it handles, leaving no ambiguity about its scope.

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 the tool is intended for error-related imagery but does not explicitly state when to prefer it over siblings (e.g., extract_text_from_image for pure OCR or analyze_image for generic images). No alternative tools are mentioned or excluded, so guidance is only implicit.

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