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rchanllc

PicDefense.io MCP Server

by rchanllc

picdefense_detect_face

Detect whether an image contains a human face by submitting its URL. Get a binary result to confirm presence or absence for image validation.

Instructions

Detect whether an image contains a human face. Consumes account credits.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYesPublicly accessible image URL to analyze (http/https), e.g. https://example.com/photo.jpg
Behavior3/5

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

No annotations are provided, so the description carries the burden. It discloses a key behavioral trait: 'Consumes account credits.' However, it does not mention return format, error behavior, or rate limits, and only implies a read-only operation via the verb 'detect.'

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is two sentences, front-loaded with the primary purpose, followed by a concise cost warning. No filler or repetition.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple one-parameter tool, the description covers purpose and an important side effect (credits). There is no output schema, so the return value is only implied ('whether'), but this is acceptable for a boolean-style detection tool. Missing error/edge-case details prevent a 5.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% and the parameter description is already detailed (format, example). The description adds no extra semantics beyond confirming that the image is analyzed for faces, which is not necessary given the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description uses a specific verb ('detect') and clearly identifies the resource ('whether an image contains a human face'). This distinguishes it from sibling tools such as picdefense_detect_logo and picdefense_detect_landmark.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description gives clear context for when to use this tool: when you need to determine if an image contains a human face. It does not explicitly mention alternatives or when not to use it, but the purpose is unambiguous.

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

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