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transcribe_audio

Convert audio challenges into text to help AI agents solve audio-based browser logins or verification tasks.

Instructions

Turn an audio challenge into text, through the operator's own command.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

C2.7/5.0
Behavior2/5

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

With no annotations, the description carries the full behavioral burden, yet it discloses no permissions, session/state prerequisites, source of the audio, or whether the result is stored or returned. The only behavioral hint is that it consumes an 'audio challenge', which is never defined.

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

Conciseness3/5

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

It is a single short sentence with no bloat, but the closing clause 'through the operator's own command' spends words without adding meaning, making the statement feel elliptical rather than concise.

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

Completeness2/5

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

For a zero-param tool with no output schema, the description should explain what the transcribed text contains and where it goes, especially given the odd phrase 'audio challenge'. Without annotations or an output schema, those gaps are not covered elsewhere.

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

Parameters4/5

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

The tool takes zero parameters, so there is nothing for the description to disambiguate beyond what the empty schema already shows. Baseline of 4 applies for a no-parameter tool.

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

Purpose3/5

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

The verb+resource are inferable ('turn an audio challenge into text' = transcribe audio), but 'audio challenge' and especially 'through the operator's own command' are cryptic and leave the actual operation ambiguous. Nothing distinguishes it from siblings like read_text or read_value.

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 when-to-use, when-not-to-use, or alternative is given. The agent cannot tell from the description when transcription is the right call versus read_text, read_value, or other extraction siblings.

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