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oruk_create_trial_key

Mint a real, temporary oruk API key with no account required: 3 requests, expires in 30 minutes, spends from a capped shared budget. Use this when no Authorization header is configured and the user wants to try transcription or tone analysis right now. Pass the returned key as the api_key argument of the audio tools. Share the signup link with the user so they can keep using oruk afterwards (7-day free trial on every plan).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observed

TDQS

A4.6/5.0
Behavior5/5

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

Beyond the annotations, it discloses the temporary nature, precise quota of 3 requests, 30-minute expiry, capped shared budget, no-account requirement, and the need to share a signup link. This is rich behavioral context for a mutating, non-destructive tool.

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?

Four sentences, each adding distinct value: key constraints, target use case, output usage, and follow-up action. No filler or repetition of the title.

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?

The description covers selection, invocation, and follow-up, including the exact quota/expiry and where to pass the returned key. The only minor gap is that it instructs the agent to share a signup link without stating where that link comes from or its URL.

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?

With zero parameters the schema is empty, but the description explains what to do with the result: pass the returned key as the api_key argument to audio tools. That adds useful semantic guidance beyond the empty schema, meeting the zero-parameter baseline.

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 pins down exactly what the tool does: mints a temporary, account-less oruk API key with a 3-request/30-minute scope. This clearly distinguishes it from the sibling audio-processing and account-checking tools.

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?

It names a concrete trigger: use when no Authorization header is configured and the user wants an immediate transcription or tone-analysis trial. It lacks an explicit 'when not to use' statement, but the trigger condition and follow-up instructions are clear.

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
Disambiguation5/5

The three audio-processing tools are sharply differentiated: transcribe_audio is words-only, analyze_tone is tone-only, and analyze_speech combines both. The supporting tools are also distinct in purpose, and the descriptions cross-reference each other to prevent misselection.

Naming Consistency5/5

All tool names follow a consistent oruk_ + verb + noun snake_case pattern, such as analyze_speech, list_models, and create_trial_key. The only mild exception is get_started, but it still clearly follows the verb-led style and does not create confusion.

Tool Count5/5

Seven tools is well-scoped for a speech analysis API MCP server: three core audio-processing tools plus four supporting tools for setup, keys, credits, and model information. Each tool has a clear purpose and none feel redundant or extraneous.

Completeness5/5

The tool surface covers the full user journey for the stated domain: getting started, obtaining a trial key, checking credits, listing models, transcribing audio, analyzing tone, and doing combined transcription plus tone analysis. There are no obvious dead ends or missing core operations for this API's scope.

Resources