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Agent402.Tools: pay-per-call web tools

Speech-to-text

audio.transcribe
Read-onlyIdempotent

[wallet-required, $0.030/call] Transcribe audio to text using OpenAI (gpt-4o-mini-transcribe). Provide a URL to an audio file (mp3, wav, m4a, etc.) and get back the transcript. No API key needed; pay per call via x402. Max 5 minutes of audio, 25 MB file size. Returns { model, provider, text, language, duration }. This hosted connector holds no wallet: pay it here over MPP, or run npx agent402-mcp with a funded wallet (AGENT_KEY) or prepaid card credits (AGENT402_CREDITS_KEY), or any x402 client.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYesURL of the audio file to transcribe (mp3, wav, m4a, ogg, flac, webm)
languageNoOptional ISO-639-1 language code (e.g. 'en', 'es', 'fr') for better accuracy

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
textYes
modelNo
durationNo
languageNo
providerNo

TDQS

A5/5.0
Behavior5/5

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

Annotations already declare readOnlyHint=true and idempotentHint=true, so the description is not required to repeat those. The description adds valuable context beyond them: per-call cost ($0.030), the fact that the hosted connector holds no wallet, payment methods, audio limits, and the return shape. No contradiction with annotations exists.

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 densely packed but every sentence earns its place. It leads with the most decision-relevant constraint (wallet-required and cost), then the core action, then technical limits, then return format, then payment alternatives. No filler or 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 tool that involves payment, size limits, and an external API, the description covers all essential aspects: cost, payment flow, constraints, return format, and alternative clients. An agent has everything needed to call it correctly without opening additional docs.

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

Parameters5/5

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

Schema coverage is 100% (both parameters described), but the description adds critical operational context: file size and duration limits, accepted formats, and the exact return structure ({ model, provider, text, language, duration }). This goes well beyond the schema and helps the agent decide parameters correctly.

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 states a specific action ('Transcribe audio to text'), the resource ('audio file'), and the underlying implementation ('OpenAI gpt-4o-mini-transcribe'). It clearly distinguishes the tool from siblings like web.search or catalog.find by naming the unique domain (audio transcription).

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?

Explicitly explains when to use this tool (provide a URL to an audio file), the constraints (max 5 minutes, 25 MB), and how to pay ('No API key needed; pay per call via x402'). It also names alternative invocation paths ('run npx agent402-mcp...' or any x402 client), giving clear routing guidance.

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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TDQS

A4.4/5.0
Disambiguation4/5

Tools are grouped by clear domain prefixes (web, memory, catalog, market) and mostly have distinct behaviors. web.search and web.news overlap somewhat as both return ranked live results, and catalog.find vs catalog.search require careful reading, but the descriptions do enough to disambiguate them.

Naming Consistency5/5

Every tool follows the same dotted domain.action pattern with lowercase snake_case, e.g. web.search, memory.read, catalog.find. This is highly predictable and lets an agent infer the general behavior of an unfamiliar tool from its name alone.

Tool Count4/5

Fifteen tools is at the upper edge of the well-scoped range, but each represents a distinct capability or meta-function like payment info and catalog discovery. The count feels reasonable for a pay-per-call marketplace front-end, though a few auxiliary tools (sellers.list, demand.request) are slightly peripheral.

Completeness4/5

The flagship set covers the main workflows: web search/news/answer, rendering, transcription, market quotes, memory read/write, and catalog lookup. Some referenced tools like extract and screenshot are not included as first-class tools, but the catalog.call/search/find trio and demand.request make those gaps addressable rather than dead ends.