Solve a problem from a picture
answer_picture_questionSolve the math, physics or chemistry problem shown in an image. $0.01 per image.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| image | Yes | Input image as a public https URL or a base64 data URI. |
answer_picture_questionSolve the math, physics or chemistry problem shown in an image. $0.01 per image.
| Name | Required | Description | Default |
|---|---|---|---|
| image | Yes | Input image as a public https URL or a base64 data URI. |
Changes observed during successful MCP inspections.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations declare readOnlyHint=true and openWorldHint=true, covering safety. The description adds the cost per image ($0.01) and the specific problem domains, which are useful behavioral details not provided by annotations. No contradiction.
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?
Extremely concise and front-loaded: the core purpose is stated first, followed by cost. Every sentence earns its place with no filler.
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 simple one-parameter tool with annotations covering safety, the description is adequate but lacks explicit mention of the return format or any caveats about image quality or problem types. Given no output schema, a brief note on expected response would improve completeness.
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 coverage is 100%, with the 'image' parameter clearly described as a public URL or base64 data URI. The description adds no additional parameter details, so it matches the baseline for high 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 solves math, physics, or chemistry problems from an image. This is a specific verb ('solve') with a defined resource and domain, distinguishing it from image editing or description tools among siblings.
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?
No guidance on when to use this tool versus alternatives like describe_image or analyze_image. The description gives no explicit conditions or exclusions, leaving the agent to infer appropriate usage from the problem domain.
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.