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Check a portrait photo (free)

portrait_precheck
Read-onlyIdempotent

FREE analyzability check before paying for portrait_analysis: is a face detectable, is the photo quality good enough (clipping/color cast)? Deterministic, no LLM. 10/hour/IP.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
image_urlNoAbsolute http(s) URL of the image (JPEG/PNG/WebP)
image_base64NoBase64-encoded image bytes (alternative to image_url)

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
bodyYesJSON body of the underlying call (see /samples/{product} for each product's shape)
statusYesHTTP status of the underlying call (200 result, 402 payment terms, 4xx input error)
how_to_payNo
receipt_idNoset on paid results; free re-fetch via get_receipt
payment_requiredNotrue when status is 402: body holds x402 payment terms, not a result. Pay and call again with x_payment

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.7/5.0
Behavior5/5

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

Goes beyond annotations by disclosing that the check is deterministic and uses no LLM, and by stating a concrete rate limit of 10/hour/IP. Annotations already cover safety traits like read-only and idempotent, and the description adds useful operational context.

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?

Front-loads the free pre-check purpose, then tightly lists the checks, deterministic nature, and rate limit. Every clause earns its place with no redundancy.

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

Completeness5/5

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

For a simple two-parameter pre-check tool with full schema coverage and an output schema, the description covers purpose, usage routing, determinism, and rate limit. Nothing essential for correct invocation is missing.

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 description coverage is 100% and both parameters are fully documented there, so the description is not required to add parameter meaning. It does not add syntax or format details beyond the schema, which is the baseline-3 case.

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?

States a specific verb and resource: a free analyzability check on a portrait photo, including what it verifies (face detection, quality issues like clipping/color cast). It explicitly positions itself as distinct from portrait_analysis by being the pre-check before paying.

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

Usage Guidelines5/5

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

Names the alternative tool portrait_analysis and states the condition for using this one: before paying for the full analysis. This gives an agent a clear routing rule without needing to inspect either schema.

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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