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classify_text

Read-onlyIdempotent

AI topic classification of supplied text (max 24k chars). POST /x402/classify — $1.75.

Input Schema

NameRequiredDescriptionDefault
textYesText to classify, max 24k chars
labelsNoOptional caller label set
paymentNoOptional. Your x402 payment proof for this exact call — the PAYMENT-SIGNATURE value produced by settling this route's 402 challenge (USDC on Base or Solana), or an MPP 'Authorization: Payment ...' value. Omit on a first call: the tool then returns the live 402 challenge to pay against. This server relays your proof upstream and retries; it never creates or settles payments itself.
multiLabelNoAllow multiple labels

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

B3.2/5.0
Behavior3/5

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

Annotations already declare readOnlyHint/idempotentHint/destructiveHint=false, so safety is covered. The description adds useful behavioral facts — it is a paid endpoint ($1.75) hit via POST /x402/classify — which is real value. It does not disclose the 402-challenge/payment-retry flow, but that lives in the schema.

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

Conciseness4/5

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

Two tight fragments, front-loaded with purpose then endpoint and price. Slightly telegraphic, but nothing is wasted.

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

Completeness3/5

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

For a paid, multi-param tool with no output schema, the description is thin on return behavior and on what happens without payment or how labels/multiLabel interact. The schema carries the payment flow, so this is adequate but with clear gaps.

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%, so both the char limit and payment-proof semantics are already documented. The description repeats the 24k limit and cost but adds no meaning beyond the schema. Baseline 3 applies.

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

Purpose4/5

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

States a specific verb and resource — 'AI topic classification of supplied text' — with a hard input limit. It does not name a sibling, and extract_keywords is a closely related tool an agent could confuse it with. Clear but not differentiated.

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

Usage Guidelines2/5

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

No guidance on when to use this vs. extract_keywords or when-not to use it. The cost mention ($1.75) implies a paid route, but the description never says when classification is the right choice.

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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