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oruk Speech

by ai.oruk
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Server Details

Hosted speech-to-text + speech emotion/tone analysis for agents. No install; trial keys built in.

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Status
Healthy
Last Tested
Transport
Streamable HTTP · MCP 2025-11-25
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TDQS

A4.5/5.0

Scored across 7 tools

Disambiguation5/5

The three analysis tools (oruk_transcribe_audio, oruk_analyze_tone, oruk_analyze_speech) are the only potential overlap, but each description explicitly states its scope and cross-references the alternatives ('for words only use X; for tone only use Y'). The remaining four tools (usage, trial key, get_started, list_models) each handle a clearly distinct administrative task.

Naming Consistency5/5

All seven tools use a uniform oruk_ prefix followed by a snake_case verb_noun pattern (analyze_speech, check_usage, create_trial_key, get_started, list_models, transcribe_audio). No mixing of conventions or casing styles.

Tool Count5/5

Seven tools is well-scoped for a speech API: three core analysis operations plus four supporting meta tools (auth, discovery, usage). Nothing feels redundant or missing at the count level.

Completeness4/5

The surface covers the full lifecycle for the domain: setup/onboarding (get_started, create_trial_key), auth/limits (check_usage), discovery (list_models), and all three primary analysis modes. Minor gaps exist (e.g. no batch or async-job handling for long audio, English-only), but nothing that blocks core workflows.

Available Tools

7 tools
oruk_analyze_speechAnalyze speech (transcript + tone)A
Read-only
Inspect

Transcribe English audio AND score how it was said in one call: transcript, tagged transcript, selected scores from 15 emotion and 16 speaking-style labels, and time-local segments. Use this when the user cares about both the words and the delivery — meetings, support calls, interviews, voice notes. Accepts wav/flac/mp3/m4a/ogg/webm. Up to 30 MB via audio_url or 8 MiB decoded via audio_base64; up to 60 minutes of English speech. Returns compact summaries by default. For words only use oruk_transcribe_audio; for tone only use oruk_analyze_tone.

ParametersJSON Schema
NameRequiredDescriptionDefault
modelNooruk-resonance (full local pipeline: transcription, emotion, style, affect, analysis) or oruk-fourier (parallel transcript and native 15-label emotion, with the shared 16-label style model). Resonance is the default.
detailNocompact (default) returns top label scores and condensed segments; full preserves all returned labels, segments, and word-level timings, subject to response-size limits. It does not expose unreturned label scores.
api_keyNoOnly for temporary keys from oruk_create_trial_key. Permanent keys belong in your MCP client config as an "Authorization: Bearer <key>" header, never in tool arguments.
diarizeNoLabel speakers (oruk-resonance only; the model is switched to oruk-resonance automatically). Speaker diarization locates turns, then Resonance scores each turn with its own text, emotions, and styles. Use for calls, meetings, and interviews. Included in subscription plan minutes. Processing details: https://oruk.ai/security#processing.
filenameNoOriginal filename including extension (e.g. call.wav). Helps decoding when audio_base64 is used.
audio_urlNoPublicly fetchable audio file URL (wav, flac, mp3, m4a, ogg, webm; up to 30 MB / 60 minutes of English speech).
audio_base64NoBase64-encoded audio bytes for local files (up to 8 MiB decoded). Prefer audio_url for anything larger.

TDQS

A5/5.0
Behavior5/5

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

Annotations already include readOnlyHint: true and destructiveHint: false, and the description adds substantial behavioral detail: model switching (diarize forces oruk-resonance), what compact vs. full returns, the limitation that unreturned label scores are not exposed, and a security/processing link. No contradiction with annotations.

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 dense but every sentence earns its place: purpose, outputs, use cases, format/size limits, model/detail explanation, and sibling differentiation. It is front-loaded with the core purpose and uses a clear, scannable structure. No fluff or repetition.

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?

Despite having no output schema, the description explains output behavior (compact vs. full, diarization results, label-score limitations) and points to a processing-details URL for deeper security info. All relevant usage context—formats, size limits, language, model selection, and when to use alternatives—is covered, making the tool self-sufficient for an agent.

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?

The schema covers 100% of parameters with descriptions, and the tool description adds meaningful context beyond them—e.g., api_key usage is clarified as only for temporary keys from oruk_create_trial_key, diarize is explained as locating turns and scoring each, and audio_base64/audio_url size limits are restated with practical guidance. This enhances the schema without redundancy.

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 clearly states the tool's purpose: transcribe English audio and score how it was said, explicitly listing outputs (transcript, tagged transcript, scores, segments). It differentiates from siblings by naming oruk_transcribe_audio for words-only and oruk_analyze_tone for tone-only, so an agent knows exactly when to pick this tool.

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?

It says 'Use this when the user cares about both the words and the delivery' and lists example scenarios (meetings, support calls, interviews, voice notes). It also provides explicit exclusion guidance: 'For words only use oruk_transcribe_audio; for tone only use oruk_analyze_tone,' giving clear when-to and when-not-to usage.

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

oruk_analyze_toneAnalyze vocal tone and emotionA
Read-only
Inspect

Score how speech sounds without transcribing it: selected emotion (happy, frustrated, worried, …) and speaking-style (sarcastic, confident, hesitant, warm, …) scores per acoustic segment. Runs the Resonance encoder and affect head only — the transcription decoder is never invoked, so nothing is transcribed and it consumes the same subscription audio minutes as unified analysis. Use this when the user asks about mood, delivery, sentiment, sarcasm, or emotional dynamics in audio. Up to 30 MB via audio_url or 8 MiB decoded via audio_base64; up to 60 minutes of English speech. Labels use model-specific thresholds; the highest-scoring emotion is returned if none passes, and styles can be empty. Outputs describe delivery, not probabilities of inner state. Need the words too? Use oruk_analyze_speech.

ParametersJSON Schema
NameRequiredDescriptionDefault
modelNooruk-resonance (full local pipeline: transcription, emotion, style, affect, analysis) or oruk-fourier (parallel transcript and native 15-label emotion, with the shared 16-label style model). Resonance is the default.
detailNocompact (default) returns top label scores and condensed segments; full preserves all returned labels, segments, and word-level timings, subject to response-size limits. It does not expose unreturned label scores.
api_keyNoOnly for temporary keys from oruk_create_trial_key. Permanent keys belong in your MCP client config as an "Authorization: Bearer <key>" header, never in tool arguments.
diarizeNoLabel speakers (oruk-resonance only; the model is switched to oruk-resonance automatically). Speaker diarization locates turns, then Resonance scores each turn with its own text, emotions, and styles. Use for calls, meetings, and interviews. Included in subscription plan minutes. Processing details: https://oruk.ai/security#processing.
filenameNoOriginal filename including extension (e.g. call.wav). Helps decoding when audio_base64 is used.
audio_urlNoPublicly fetchable audio file URL (wav, flac, mp3, m4a, ogg, webm; up to 30 MB / 60 minutes of English speech).
audio_base64NoBase64-encoded audio bytes for local files (up to 8 MiB decoded). Prefer audio_url for anything larger.

TDQS

A4.7/5.0
Behavior5/5

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

Annotations already mark readOnlyHint=true and destructiveHint=false, and the description builds on this with valuable behavioral details: the transcription decoder is never invoked, nothing is transcribed, it consumes the same subscription minutes as unified analysis, labels use model-specific thresholds, styles can be empty, and outputs describe delivery rather than inner-state probabilities. This goes well beyond the structured fields and contains no contradiction.

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 front-loaded with the core purpose, then delivers behavioral guarantees, usage triggers, limits, output interpretation, and a sibling pointer in sequence. Every sentence earns its place; there is no filler or redundant restatement of the title.

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?

Even with no output schema, the description covers the essential context: input size/duration limits, language constraint, outcome shape (per-segment emotion/style scores), edge cases (threshold fallback, empty styles), and how to interpret outputs. It also routes to the correct sibling when transcription is also needed, making the tool fully understandable for correct invocation.

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%, so the input schema already documents every parameter. The description adds some useful constraints (up to 30 MB via audio_url, 8 MiB via audio_base64, 60 minutes of English speech), but these largely restate schema descriptions rather than introduce new parameter meaning. The baseline of 3 is appropriate.

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 opens with a specific verb and resource: 'Score how speech sounds without transcribing it', naming emotion and speaking-style scores per acoustic segment. It clearly marks what the tool is not (transcription) and names the sibling oruk_analyze_speech, so an agent can distinguish it without opening the schema.

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?

It explicitly states when to use the tool: 'Use this when the user asks about mood, delivery, sentiment, sarcasm, or emotional dynamics in audio.' It also gives the complementary alternative with the condition: 'Need the words too? Use oruk_analyze_speech.' No inference is required.

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

oruk_check_usageCheck API key, subscription, and usageA
Read-only
Inspect

Verify that an Oruk API key works and report the subscription, remaining audio minutes, and recent API usage. Use this after setup or to diagnose access and usage limits. Requires the Authorization header from your MCP config or a temporary api_key.

ParametersJSON Schema
NameRequiredDescriptionDefault
api_keyNoOnly for temporary keys from oruk_create_trial_key. Permanent keys belong in the Authorization header of your MCP client config.

TDQS

A4.5/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true and destructiveHint=false, and the description adds context about the authentication requirement (header vs. api_key). It does not detail error behavior or output format, but the tool is simple and read-only.

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 two sentences, front-loaded with the main action and purpose, and includes usage guidance and prerequisites without unnecessary verbosity.

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?

For a simple read-only tool with one parameter and no output schema, the description covers purpose, usage timing, and authentication. It omits explicit return details but these are likely self-evident; the information provided is sufficient for basic understanding.

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?

The single parameter 'api_key' has a clear description explaining when it is needed (temporary keys from oruk_create_trial_key) and when it is not (permanent keys in header). This fully covers the parameter's semantics.

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 clearly states the tool's purpose: verify an API key works and report subscription, remaining minutes, and recent usage. It is specific and distinct from the sibling tools (e.g., transcription, analysis).

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?

The description explicitly says to use it 'after setup or to diagnose access and usage limits' and notes the authentication requirement. It does not explicitly contrast with alternatives, but the guidance is clear and actionable.

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

oruk_create_trial_keyCreate a free trial API keyAInspect

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 self-serve plans).

ParametersJSON Schema
NameRequiredDescriptionDefault

No parameters

TDQS

A4.9/5.0
Behavior5/5

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

The description discloses important behavioral details: the key is temporary, limited to 3 requests, expires in 30 minutes, and spends from a capped shared budget. There is no contradiction with the annotations.

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 dense but well-organized, with every sentence adding useful context. It covers the trigger condition, limitations, usage instructions, and follow-up action without unnecessary verbosity.

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?

Given the tool's simplicity and lack of output schema, the description fully covers what an agent needs: when to call it, what it returns, how to use the result, and what to tell the user afterward.

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 has no parameters, so the baseline is 4. The description correctly implies no input is needed, though it could explicitly state 'no parameters required' for absolute clarity.

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 clearly states the tool's purpose: to mint a real, temporary API key with no account required. It distinguishes this tool from siblings like check_usage or list_models by focusing on credential creation.

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?

It explicitly states when to use the tool ('when no Authorization header is configured') and provides clear next steps: pass the returned key to audio tools and share the signup link for continued use.

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

oruk_get_startedGet started with orukA
Read-only
Inspect

Quickstart for the oruk Speech API and this MCP server: how to get an API key, per-client MCP configuration snippets, SDK install commands, and an optional routing rule the user can add to their agent instructions. No API key required. Use this when setting oruk up for the first time or when the user asks how oruk works.

ParametersJSON Schema
NameRequiredDescriptionDefault

No parameters

TDQS

A4.7/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true and destructiveHint=false, covering the safety profile. The description adds useful behavioral context by noting 'No API key required' and describing the kind of guidance returned. It does not go into depth about the exact output format, but that is not essential for an informational quickstart.

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 a tight two sentences. The first sentence front-loads the tool's role and lists the contents; the second adds usage timing. No wasted words.

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 parameterless, read-only informational tool, the description covers what the tool does, what it returns, and when to use it. It is complete on its own without needing an output schema.

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 schema has zero parameters, so the description does not need to explain any. The baseline of 4 is appropriate because the tool takes no input and the description correctly omits parameter details.

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 opens with 'Quickstart for the oruk Speech API and this MCP server' and lists specific deliverables (API key, MCP config snippets, SDK install commands, routing rule), making its purpose unmistakable. It clearly distinguishes itself from sibling tools that analyze speech, check credits, or create trial keys.

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?

Provides explicit guidance: 'Use this when setting oruk up for the first time or when the user asks how oruk works.' This is direct and actionable, leaving no doubt about when to invoke this tool versus the analysis or transcription tools.

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

oruk_list_modelsList models, pricing, and labelsA
Read-only
Inspect

List oruk’s speech models with lifecycle, current subscription plans, and explicitly labeled legacy reference rates, the five API tasks, the 15 emotion and 16 speaking-style labels, and audio limits. No API key required. Use this to choose a model, estimate cost before analyzing long audio, or see which labels exist.

ParametersJSON Schema
NameRequiredDescriptionDefault

No parameters

TDQS

A4.5/5.0
Behavior4/5

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

Annotations already cover readOnlyHint and openWorldHint, so the description doesn't need to restate safety. It adds useful behavioral context beyond that: no authentication is needed, the tool is a discovery/reference endpoint, and legacy rates are explicitly labeled rather than being presented as current. This gives the agent realistic expectations before invocation.

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 compact and front-loaded with the action and resource, then lists the key catalog items in one efficient sentence, followed by a short sentence on use cases and auth. Every clause adds either scope, a use case, or an operational detail; there is no filler or repetition.

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 zero-parameter listing tool with no output schema, the description is complete: it enumerates the categories of data returned, gives practical reasons to call the tool, and states the lack of an API key requirement. An agent has enough information to decide when to invoke this tool and what to expect back.

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 input schema has zero parameters, so there are no parameter semantics for the description to clarify. The description instead focuses on the richness of the returned information, which is the meaningful content for this tool. This matches the baseline for a parameterless tool.

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 begins with a specific verb ('List') and names the exact resource scope: models, lifecycle, subscription plans, legacy reference rates, API tasks, emotion/speaking-style labels, and audio limits. This enumerates what the tool returns and clearly distinguishes it from the other oruk tools, which perform analysis, transcription, or key management.

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?

The description provides explicit use cases: choosing a model, estimating cost before long audio analysis, and checking available labels. It also says no API key is required, which is directly relevant to when an agent can call this tool. It does not name sibling tools to exclude, but the use cases are specific enough for an agent to route correctly.

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

oruk_transcribe_audioTranscribe audioA
Read-only
Inspect

Transcribe prerecorded English audio to text with time-ordered segments and word timings. Use this when only the words matter. Accepts wav/flac/mp3/m4a/ogg/webm. Up to 30 MB via audio_url or 8 MiB decoded via audio_base64; up to 60 minutes of English speech. Does not score emotion or tone — use oruk_analyze_speech for transcript + tone together, or oruk_analyze_tone for tone alone.

ParametersJSON Schema
NameRequiredDescriptionDefault
modelNooruk-resonance (full local pipeline: transcription, emotion, style, affect, analysis) or oruk-fourier (parallel transcript and native 15-label emotion, with the shared 16-label style model). Resonance is the default.
detailNocompact (default) returns top label scores and condensed segments; full preserves all returned labels, segments, and word-level timings, subject to response-size limits. It does not expose unreturned label scores.
api_keyNoOnly for temporary keys from oruk_create_trial_key. Permanent keys belong in your MCP client config as an "Authorization: Bearer <key>" header, never in tool arguments.
diarizeNoLabel speakers (oruk-resonance only; the model is switched to oruk-resonance automatically). Speaker diarization locates turns, then Resonance scores each turn with its own text, emotions, and styles. Use for calls, meetings, and interviews. Included in subscription plan minutes. Processing details: https://oruk.ai/security#processing.
filenameNoOriginal filename including extension (e.g. call.wav). Helps decoding when audio_base64 is used.
audio_urlNoPublicly fetchable audio file URL (wav, flac, mp3, m4a, ogg, webm; up to 30 MB / 60 minutes of English speech).
audio_base64NoBase64-encoded audio bytes for local files (up to 8 MiB decoded). Prefer audio_url for anything larger.

TDQS

A4.2/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true and destructiveHint=false, so the safety profile is covered. The description adds useful limits (30 MB URL, 8 MiB base64, 60 minutes, English-only) and clarifies what the tool does NOT do ('Does not score emotion or tone'). It could add more about output truncation or processing behavior, but it does not contradict annotations.

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?

Three sentences, all dense with decision-relevant information. The main purpose is front-loaded, constraints follow, and the sibling distinction closes the description. No wasted words.

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?

Given 100% schema coverage, detailed annotations, and no output schema, the description covers the core usage decision (when to use, what it accepts, what it doesn't do). It could mention the response format/pagination, but the schema and annotations already handle the rest. Minor gap only.

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%, so the schema already documents all 7 parameters in detail. The description adds the overall file-format and size constraints context, but it does not need to explain each parameter because the schema does. Baseline 3 is appropriate.

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 ('Transcribe'), resource ('prerecorded English audio'), and output ('time-ordered segments and word timings'). Distinguishes itself from sibling tools by naming oruk_analyze_speech and oruk_analyze_tone and what they do differently. An agent can tell exactly what this tool does without opening the schema.

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 says 'Use this when only the words matter' and names alternatives: use oruk_analyze_speech for transcript + tone together, or oruk_analyze_tone for tone alone. This is the ideal when/when-not guidance an agent needs to select among siblings.

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

Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections.

  1. 5 tool updates
    • Changedoruk_analyze_speech4 fields changed
      • changedInput schema / properties / audio_base64 / description
        Previous value: -"Base64-encoded audio bytes for local files (up to 8 MB decoded). Prefer audio_url for anything larger."New value: +"Base64-encoded audio bytes for local files (up to 8 MiB decoded). Prefer audio_url for anything larger."
      • changedInput schema / properties / detail / description
        Previous value: -"compact (default) returns top label scores and condensed segments; full adds every label score and word-level timings."New value: +"compact (default) returns top label scores and condensed segments; full preserves all returned labels, segments, and word-level timings, subject to response-size limits. It does not expose unreturned label scores."
      • changedInput schema / properties / diarize / description
        Previous value: -"Label speakers (oruk-resonance only; the model is switched to oruk-resonance automatically). Speakers are located with pyannoteAI diarization, then Resonance scores each speaker turn, so every segment carries a speaker field with its own text, emotions, and styles. Use for calls, meetings, and interviews. Included in plan minutes; legacy metered accounts retain their agreed rates."New value: +"Label speakers (oruk-resonance only; the model is switched to oruk-resonance automatically). Speaker diarization locates turns, then Resonance scores each turn with its own text, emotions, and styles. Use for calls, meetings, and interviews. Included in subscription plan minutes. Processing details: https://oruk.ai/security#processing."
      • changedInput schema / properties / model / description
        Previous value: -"oruk-resonance (full local pipeline: transcription, emotion, style, affect, analysis) or oruk-fourier (transcript plus native 15-label emotion)."New value: +"oruk-resonance (full local pipeline: transcription, emotion, style, affect, analysis) or oruk-fourier (parallel transcript and native 15-label emotion, with the shared 16-label style model). Resonance is the default."
    • Changedoruk_analyze_tone4 fields changed
      • changedInput schema / properties / audio_base64 / description
        Previous value: -"Base64-encoded audio bytes for local files (up to 8 MB decoded). Prefer audio_url for anything larger."New value: +"Base64-encoded audio bytes for local files (up to 8 MiB decoded). Prefer audio_url for anything larger."
      • changedInput schema / properties / detail / description
        Previous value: -"compact (default) returns top label scores and condensed segments; full adds every label score and word-level timings."New value: +"compact (default) returns top label scores and condensed segments; full preserves all returned labels, segments, and word-level timings, subject to response-size limits. It does not expose unreturned label scores."
      • changedInput schema / properties / diarize / description
        Previous value: -"Label speakers (oruk-resonance only; the model is switched to oruk-resonance automatically). Speakers are located with pyannoteAI diarization, then Resonance scores each speaker turn, so every segment carries a speaker field with its own text, emotions, and styles. Use for calls, meetings, and interviews. Included in plan minutes; legacy metered accounts retain their agreed rates."New value: +"Label speakers (oruk-resonance only; the model is switched to oruk-resonance automatically). Speaker diarization locates turns, then Resonance scores each turn with its own text, emotions, and styles. Use for calls, meetings, and interviews. Included in subscription plan minutes. Processing details: https://oruk.ai/security#processing."
      • changedInput schema / properties / model / description
        Previous value: -"oruk-resonance (full local pipeline: transcription, emotion, style, affect, analysis) or oruk-fourier (transcript plus native 15-label emotion)."New value: +"oruk-resonance (full local pipeline: transcription, emotion, style, affect, analysis) or oruk-fourier (parallel transcript and native 15-label emotion, with the shared 16-label style model). Resonance is the default."
    • Removedoruk_check_credits
    • Addedoruk_check_usage
    • Changedoruk_transcribe_audio4 fields changed
      • changedInput schema / properties / audio_base64 / description
        Previous value: -"Base64-encoded audio bytes for local files (up to 8 MB decoded). Prefer audio_url for anything larger."New value: +"Base64-encoded audio bytes for local files (up to 8 MiB decoded). Prefer audio_url for anything larger."
      • changedInput schema / properties / detail / description
        Previous value: -"compact (default) returns top label scores and condensed segments; full adds every label score and word-level timings."New value: +"compact (default) returns top label scores and condensed segments; full preserves all returned labels, segments, and word-level timings, subject to response-size limits. It does not expose unreturned label scores."
      • changedInput schema / properties / diarize / description
        Previous value: -"Label speakers (oruk-resonance only; the model is switched to oruk-resonance automatically). Speakers are located with pyannoteAI diarization, then Resonance scores each speaker turn, so every segment carries a speaker field with its own text, emotions, and styles. Use for calls, meetings, and interviews. Included in plan minutes; legacy metered accounts retain their agreed rates."New value: +"Label speakers (oruk-resonance only; the model is switched to oruk-resonance automatically). Speaker diarization locates turns, then Resonance scores each turn with its own text, emotions, and styles. Use for calls, meetings, and interviews. Included in subscription plan minutes. Processing details: https://oruk.ai/security#processing."
      • changedInput schema / properties / model / description
        Previous value: -"oruk-resonance (full local pipeline: transcription, emotion, style, affect, analysis) or oruk-fourier (transcript plus native 15-label emotion)."New value: +"oruk-resonance (full local pipeline: transcription, emotion, style, affect, analysis) or oruk-fourier (parallel transcript and native 15-label emotion, with the shared 16-label style model). Resonance is the default."
  2. 5 tool updates
    • Changedoruk_analyze_speech4 fields changed
      • changedInput schema / properties / audio_base64 / description
        Previous value: -"Base64-encoded audio bytes for local files (up to 8 MiB decoded). Prefer audio_url for anything larger."New value: +"Base64-encoded audio bytes for local files (up to 8 MB decoded). Prefer audio_url for anything larger."
      • changedInput schema / properties / detail / description
        Previous value: -"compact (default) returns top label scores and condensed segments; full preserves all returned labels, segments, and word-level timings, subject to response-size limits. It does not expose unreturned label scores."New value: +"compact (default) returns top label scores and condensed segments; full adds every label score and word-level timings."
      • changedInput schema / properties / diarize / description
        Previous value: -"Label speakers (oruk-resonance only; the model is switched to oruk-resonance automatically). Speaker diarization locates turns, then Resonance scores each turn with its own text, emotions, and styles. Use for calls, meetings, and interviews. Included in subscription plan minutes. Processing details: https://oruk.ai/security#processing."New value: +"Label speakers (oruk-resonance only; the model is switched to oruk-resonance automatically). Speakers are located with pyannoteAI diarization, then Resonance scores each speaker turn, so every segment carries a speaker field with its own text, emotions, and styles. Use for calls, meetings, and interviews. Included in plan minutes; legacy metered accounts retain their agreed rates."
      • changedInput schema / properties / model / description
        Previous value: -"oruk-resonance (full local pipeline: transcription, emotion, style, affect, analysis) or oruk-fourier (parallel transcript and native 15-label emotion, with the shared 16-label style model). Resonance is the default."New value: +"oruk-resonance (full local pipeline: transcription, emotion, style, affect, analysis) or oruk-fourier (transcript plus native 15-label emotion)."
    • Changedoruk_analyze_tone4 fields changed
      • changedInput schema / properties / audio_base64 / description
        Previous value: -"Base64-encoded audio bytes for local files (up to 8 MiB decoded). Prefer audio_url for anything larger."New value: +"Base64-encoded audio bytes for local files (up to 8 MB decoded). Prefer audio_url for anything larger."
      • changedInput schema / properties / detail / description
        Previous value: -"compact (default) returns top label scores and condensed segments; full preserves all returned labels, segments, and word-level timings, subject to response-size limits. It does not expose unreturned label scores."New value: +"compact (default) returns top label scores and condensed segments; full adds every label score and word-level timings."
      • changedInput schema / properties / diarize / description
        Previous value: -"Label speakers (oruk-resonance only; the model is switched to oruk-resonance automatically). Speaker diarization locates turns, then Resonance scores each turn with its own text, emotions, and styles. Use for calls, meetings, and interviews. Included in subscription plan minutes. Processing details: https://oruk.ai/security#processing."New value: +"Label speakers (oruk-resonance only; the model is switched to oruk-resonance automatically). Speakers are located with pyannoteAI diarization, then Resonance scores each speaker turn, so every segment carries a speaker field with its own text, emotions, and styles. Use for calls, meetings, and interviews. Included in plan minutes; legacy metered accounts retain their agreed rates."
      • changedInput schema / properties / model / description
        Previous value: -"oruk-resonance (full local pipeline: transcription, emotion, style, affect, analysis) or oruk-fourier (parallel transcript and native 15-label emotion, with the shared 16-label style model). Resonance is the default."New value: +"oruk-resonance (full local pipeline: transcription, emotion, style, affect, analysis) or oruk-fourier (transcript plus native 15-label emotion)."
    • Addedoruk_check_credits
    • Removedoruk_check_usage
    • Changedoruk_transcribe_audio4 fields changed
      • changedInput schema / properties / audio_base64 / description
        Previous value: -"Base64-encoded audio bytes for local files (up to 8 MiB decoded). Prefer audio_url for anything larger."New value: +"Base64-encoded audio bytes for local files (up to 8 MB decoded). Prefer audio_url for anything larger."
      • changedInput schema / properties / detail / description
        Previous value: -"compact (default) returns top label scores and condensed segments; full preserves all returned labels, segments, and word-level timings, subject to response-size limits. It does not expose unreturned label scores."New value: +"compact (default) returns top label scores and condensed segments; full adds every label score and word-level timings."
      • changedInput schema / properties / diarize / description
        Previous value: -"Label speakers (oruk-resonance only; the model is switched to oruk-resonance automatically). Speaker diarization locates turns, then Resonance scores each turn with its own text, emotions, and styles. Use for calls, meetings, and interviews. Included in subscription plan minutes. Processing details: https://oruk.ai/security#processing."New value: +"Label speakers (oruk-resonance only; the model is switched to oruk-resonance automatically). Speakers are located with pyannoteAI diarization, then Resonance scores each speaker turn, so every segment carries a speaker field with its own text, emotions, and styles. Use for calls, meetings, and interviews. Included in plan minutes; legacy metered accounts retain their agreed rates."
      • changedInput schema / properties / model / description
        Previous value: -"oruk-resonance (full local pipeline: transcription, emotion, style, affect, analysis) or oruk-fourier (parallel transcript and native 15-label emotion, with the shared 16-label style model). Resonance is the default."New value: +"oruk-resonance (full local pipeline: transcription, emotion, style, affect, analysis) or oruk-fourier (transcript plus native 15-label emotion)."
  3. 3 tool updates
    • Changedoruk_analyze_speech2 fields changed
      • changedInput schema / properties / audio_base64 / description
        Previous value: -"Base64-encoded audio bytes for local files (up to 8 MB decoded). Prefer audio_url for anything larger."New value: +"Base64-encoded audio bytes for local files (up to 8 MiB decoded). Prefer audio_url for anything larger."
      • changedInput schema / properties / detail / description
        Previous value: -"compact (default) returns top label scores and condensed segments; full adds every label score and word-level timings."New value: +"compact (default) returns top label scores and condensed segments; full preserves all returned labels, segments, and word-level timings, subject to response-size limits. It does not expose unreturned label scores."
    • Changedoruk_analyze_tone2 fields changed
      • changedInput schema / properties / audio_base64 / description
        Previous value: -"Base64-encoded audio bytes for local files (up to 8 MB decoded). Prefer audio_url for anything larger."New value: +"Base64-encoded audio bytes for local files (up to 8 MiB decoded). Prefer audio_url for anything larger."
      • changedInput schema / properties / detail / description
        Previous value: -"compact (default) returns top label scores and condensed segments; full adds every label score and word-level timings."New value: +"compact (default) returns top label scores and condensed segments; full preserves all returned labels, segments, and word-level timings, subject to response-size limits. It does not expose unreturned label scores."
    • Changedoruk_transcribe_audio2 fields changed
      • changedInput schema / properties / audio_base64 / description
        Previous value: -"Base64-encoded audio bytes for local files (up to 8 MB decoded). Prefer audio_url for anything larger."New value: +"Base64-encoded audio bytes for local files (up to 8 MiB decoded). Prefer audio_url for anything larger."
      • changedInput schema / properties / detail / description
        Previous value: -"compact (default) returns top label scores and condensed segments; full adds every label score and word-level timings."New value: +"compact (default) returns top label scores and condensed segments; full preserves all returned labels, segments, and word-level timings, subject to response-size limits. It does not expose unreturned label scores."
  4. 5 tool updates
    • Changedoruk_analyze_speech2 fields changed
      • changedInput schema / properties / diarize / description
        Previous value: -"Label speakers (oruk-resonance only; the model is switched to oruk-resonance automatically). Speakers are located with pyannoteAI diarization, then Resonance scores each speaker turn, so every segment carries a speaker field with its own text, emotions, and styles. Use for calls, meetings, and interviews. Included in plan minutes; legacy metered accounts retain their agreed rates."New value: +"Label speakers (oruk-resonance only; the model is switched to oruk-resonance automatically). Speaker diarization locates turns, then Resonance scores each turn with its own text, emotions, and styles. Use for calls, meetings, and interviews. Included in subscription plan minutes. Processing details: https://oruk.ai/security#processing."
      • changedInput schema / properties / model / description
        Previous value: -"oruk-resonance (full local pipeline: transcription, emotion, style, affect, analysis) or oruk-fourier (transcript plus native 15-label emotion)."New value: +"oruk-resonance (full local pipeline: transcription, emotion, style, affect, analysis) or oruk-fourier (parallel transcript and native 15-label emotion, with the shared 16-label style model). Resonance is the default."
    • Changedoruk_analyze_tone2 fields changed
      • changedInput schema / properties / diarize / description
        Previous value: -"Label speakers (oruk-resonance only; the model is switched to oruk-resonance automatically). Speakers are located with pyannoteAI diarization, then Resonance scores each speaker turn, so every segment carries a speaker field with its own text, emotions, and styles. Use for calls, meetings, and interviews. Included in plan minutes; legacy metered accounts retain their agreed rates."New value: +"Label speakers (oruk-resonance only; the model is switched to oruk-resonance automatically). Speaker diarization locates turns, then Resonance scores each turn with its own text, emotions, and styles. Use for calls, meetings, and interviews. Included in subscription plan minutes. Processing details: https://oruk.ai/security#processing."
      • changedInput schema / properties / model / description
        Previous value: -"oruk-resonance (full local pipeline: transcription, emotion, style, affect, analysis) or oruk-fourier (transcript plus native 15-label emotion)."New value: +"oruk-resonance (full local pipeline: transcription, emotion, style, affect, analysis) or oruk-fourier (parallel transcript and native 15-label emotion, with the shared 16-label style model). Resonance is the default."
    • Removedoruk_check_credits
    • Addedoruk_check_usage
    • Changedoruk_transcribe_audio2 fields changed
      • changedInput schema / properties / diarize / description
        Previous value: -"Label speakers (oruk-resonance only; the model is switched to oruk-resonance automatically). Speakers are located with pyannoteAI diarization, then Resonance scores each speaker turn, so every segment carries a speaker field with its own text, emotions, and styles. Use for calls, meetings, and interviews. Included in plan minutes; legacy metered accounts retain their agreed rates."New value: +"Label speakers (oruk-resonance only; the model is switched to oruk-resonance automatically). Speaker diarization locates turns, then Resonance scores each turn with its own text, emotions, and styles. Use for calls, meetings, and interviews. Included in subscription plan minutes. Processing details: https://oruk.ai/security#processing."
      • changedInput schema / properties / model / description
        Previous value: -"oruk-resonance (full local pipeline: transcription, emotion, style, affect, analysis) or oruk-fourier (transcript plus native 15-label emotion)."New value: +"oruk-resonance (full local pipeline: transcription, emotion, style, affect, analysis) or oruk-fourier (parallel transcript and native 15-label emotion, with the shared 16-label style model). Resonance is the default."
  5. 5 tool updates
    • Changedoruk_analyze_speech2 fields changed
      • changedInput schema / properties / diarize / description
        Previous value: -"Label speakers (oruk-resonance only; the model is switched to oruk-resonance automatically). Speaker diarization locates turns, then Resonance scores each turn with its own text, emotions, and styles. Use for calls, meetings, and interviews. Included in subscription plan minutes. Processing details: https://oruk.ai/security#processing."New value: +"Label speakers (oruk-resonance only; the model is switched to oruk-resonance automatically). Speakers are located with pyannoteAI diarization, then Resonance scores each speaker turn, so every segment carries a speaker field with its own text, emotions, and styles. Use for calls, meetings, and interviews. Included in plan minutes; legacy metered accounts retain their agreed rates."
      • changedInput schema / properties / model / description
        Previous value: -"oruk-resonance (full local pipeline: transcription, emotion, style, affect, analysis) or oruk-fourier (parallel transcript and native 15-label emotion, with the shared 16-label style model). Resonance is the default."New value: +"oruk-resonance (full local pipeline: transcription, emotion, style, affect, analysis) or oruk-fourier (transcript plus native 15-label emotion)."
    • Changedoruk_analyze_tone2 fields changed
      • changedInput schema / properties / diarize / description
        Previous value: -"Label speakers (oruk-resonance only; the model is switched to oruk-resonance automatically). Speaker diarization locates turns, then Resonance scores each turn with its own text, emotions, and styles. Use for calls, meetings, and interviews. Included in subscription plan minutes. Processing details: https://oruk.ai/security#processing."New value: +"Label speakers (oruk-resonance only; the model is switched to oruk-resonance automatically). Speakers are located with pyannoteAI diarization, then Resonance scores each speaker turn, so every segment carries a speaker field with its own text, emotions, and styles. Use for calls, meetings, and interviews. Included in plan minutes; legacy metered accounts retain their agreed rates."
      • changedInput schema / properties / model / description
        Previous value: -"oruk-resonance (full local pipeline: transcription, emotion, style, affect, analysis) or oruk-fourier (parallel transcript and native 15-label emotion, with the shared 16-label style model). Resonance is the default."New value: +"oruk-resonance (full local pipeline: transcription, emotion, style, affect, analysis) or oruk-fourier (transcript plus native 15-label emotion)."
    • Addedoruk_check_credits
    • Removedoruk_check_usage
    • Changedoruk_transcribe_audio2 fields changed
      • changedInput schema / properties / diarize / description
        Previous value: -"Label speakers (oruk-resonance only; the model is switched to oruk-resonance automatically). Speaker diarization locates turns, then Resonance scores each turn with its own text, emotions, and styles. Use for calls, meetings, and interviews. Included in subscription plan minutes. Processing details: https://oruk.ai/security#processing."New value: +"Label speakers (oruk-resonance only; the model is switched to oruk-resonance automatically). Speakers are located with pyannoteAI diarization, then Resonance scores each speaker turn, so every segment carries a speaker field with its own text, emotions, and styles. Use for calls, meetings, and interviews. Included in plan minutes; legacy metered accounts retain their agreed rates."
      • changedInput schema / properties / model / description
        Previous value: -"oruk-resonance (full local pipeline: transcription, emotion, style, affect, analysis) or oruk-fourier (parallel transcript and native 15-label emotion, with the shared 16-label style model). Resonance is the default."New value: +"oruk-resonance (full local pipeline: transcription, emotion, style, affect, analysis) or oruk-fourier (transcript plus native 15-label emotion)."
  6. 5 tool updates
    • Changedoruk_analyze_speech1 field changed
      • changedInput schema / properties / diarize / description
        Previous value: -"Label speakers (oruk-resonance only; the model is switched to oruk-resonance automatically). Speakers are located with pyannoteAI diarization, then Resonance scores each speaker turn, so every segment carries a speaker field with its own text, emotions, and styles. Use for calls, meetings, and interviews. Included in plan minutes; legacy metered accounts retain their agreed rates."New value: +"Label speakers (oruk-resonance only; the model is switched to oruk-resonance automatically). Speaker diarization locates turns, then Resonance scores each turn with its own text, emotions, and styles. Use for calls, meetings, and interviews. Included in subscription plan minutes. Processing details: https://oruk.ai/security#processing."
    • Changedoruk_analyze_tone1 field changed
      • changedInput schema / properties / diarize / description
        Previous value: -"Label speakers (oruk-resonance only; the model is switched to oruk-resonance automatically). Speakers are located with pyannoteAI diarization, then Resonance scores each speaker turn, so every segment carries a speaker field with its own text, emotions, and styles. Use for calls, meetings, and interviews. Included in plan minutes; legacy metered accounts retain their agreed rates."New value: +"Label speakers (oruk-resonance only; the model is switched to oruk-resonance automatically). Speaker diarization locates turns, then Resonance scores each turn with its own text, emotions, and styles. Use for calls, meetings, and interviews. Included in subscription plan minutes. Processing details: https://oruk.ai/security#processing."
    • Removedoruk_check_credits
    • Addedoruk_check_usage
    • Changedoruk_transcribe_audio1 field changed
      • changedInput schema / properties / diarize / description
        Previous value: -"Label speakers (oruk-resonance only; the model is switched to oruk-resonance automatically). Speakers are located with pyannoteAI diarization, then Resonance scores each speaker turn, so every segment carries a speaker field with its own text, emotions, and styles. Use for calls, meetings, and interviews. Included in plan minutes; legacy metered accounts retain their agreed rates."New value: +"Label speakers (oruk-resonance only; the model is switched to oruk-resonance automatically). Speaker diarization locates turns, then Resonance scores each turn with its own text, emotions, and styles. Use for calls, meetings, and interviews. Included in subscription plan minutes. Processing details: https://oruk.ai/security#processing."
  7. 3 tool updates
    • Changedoruk_analyze_speech1 field changed
      • changedInput schema / properties / model / description
        Previous value: -"oruk-resonance (full local pipeline: transcription, emotion, style, affect, analysis) or oruk-fourier (transcript plus native 15-label emotion)."New value: +"oruk-resonance (full local pipeline: transcription, emotion, style, affect, analysis) or oruk-fourier (parallel transcript and native 15-label emotion, with the shared 16-label style model). Resonance is the default."
    • Changedoruk_analyze_tone1 field changed
      • changedInput schema / properties / model / description
        Previous value: -"oruk-resonance (full local pipeline: transcription, emotion, style, affect, analysis) or oruk-fourier (transcript plus native 15-label emotion)."New value: +"oruk-resonance (full local pipeline: transcription, emotion, style, affect, analysis) or oruk-fourier (parallel transcript and native 15-label emotion, with the shared 16-label style model). Resonance is the default."
    • Changedoruk_transcribe_audio1 field changed
      • changedInput schema / properties / model / description
        Previous value: -"oruk-resonance (full local pipeline: transcription, emotion, style, affect, analysis) or oruk-fourier (transcript plus native 15-label emotion)."New value: +"oruk-resonance (full local pipeline: transcription, emotion, style, affect, analysis) or oruk-fourier (parallel transcript and native 15-label emotion, with the shared 16-label style model). Resonance is the default."
  8. 3 tool updates
    • Changedoruk_analyze_speech2 fields changed
      • changedInput schema / properties / diarize / description
        Previous value: -"Label speakers (oruk-resonance only; the model is switched to oruk-resonance automatically). Speakers are located with pyannoteAI diarization, then Resonance scores each speaker turn, so every segment carries a speaker field with its own text, emotions, and styles. Use for calls, meetings, and interviews. Adds $0.0040 per audio minute."New value: +"Label speakers (oruk-resonance only; the model is switched to oruk-resonance automatically). Speakers are located with pyannoteAI diarization, then Resonance scores each speaker turn, so every segment carries a speaker field with its own text, emotions, and styles. Use for calls, meetings, and interviews. Included in plan minutes; legacy metered accounts retain their agreed rates."
      • changedInput schema / properties / model / description
        Previous value: -"oruk-resonance (full local pipeline: transcription, emotion, style, affect, analysis) or oruk-fourier (parallel transcript and native 15-label emotion, with the shared 16-label style model). Resonance is the default."New value: +"oruk-resonance (full local pipeline: transcription, emotion, style, affect, analysis) or oruk-fourier (transcript plus native 15-label emotion)."
    • Changedoruk_analyze_tone2 fields changed
      • changedInput schema / properties / diarize / description
        Previous value: -"Label speakers (oruk-resonance only; the model is switched to oruk-resonance automatically). Speakers are located with pyannoteAI diarization, then Resonance scores each speaker turn, so every segment carries a speaker field with its own text, emotions, and styles. Use for calls, meetings, and interviews. Adds $0.0040 per audio minute."New value: +"Label speakers (oruk-resonance only; the model is switched to oruk-resonance automatically). Speakers are located with pyannoteAI diarization, then Resonance scores each speaker turn, so every segment carries a speaker field with its own text, emotions, and styles. Use for calls, meetings, and interviews. Included in plan minutes; legacy metered accounts retain their agreed rates."
      • changedInput schema / properties / model / description
        Previous value: -"oruk-resonance (full local pipeline: transcription, emotion, style, affect, analysis) or oruk-fourier (parallel transcript and native 15-label emotion, with the shared 16-label style model). Resonance is the default."New value: +"oruk-resonance (full local pipeline: transcription, emotion, style, affect, analysis) or oruk-fourier (transcript plus native 15-label emotion)."
    • Changedoruk_transcribe_audio2 fields changed
      • changedInput schema / properties / diarize / description
        Previous value: -"Label speakers (oruk-resonance only; the model is switched to oruk-resonance automatically). Speakers are located with pyannoteAI diarization, then Resonance scores each speaker turn, so every segment carries a speaker field with its own text, emotions, and styles. Use for calls, meetings, and interviews. Adds $0.0040 per audio minute."New value: +"Label speakers (oruk-resonance only; the model is switched to oruk-resonance automatically). Speakers are located with pyannoteAI diarization, then Resonance scores each speaker turn, so every segment carries a speaker field with its own text, emotions, and styles. Use for calls, meetings, and interviews. Included in plan minutes; legacy metered accounts retain their agreed rates."
      • changedInput schema / properties / model / description
        Previous value: -"oruk-resonance (full local pipeline: transcription, emotion, style, affect, analysis) or oruk-fourier (parallel transcript and native 15-label emotion, with the shared 16-label style model). Resonance is the default."New value: +"oruk-resonance (full local pipeline: transcription, emotion, style, affect, analysis) or oruk-fourier (transcript plus native 15-label emotion)."
  9. 3 tool updates
    • Changedoruk_analyze_speech1 field changed
      • changedInput schema / properties / model / description
        Previous value: -"oruk-resonance (full local pipeline: transcription, emotion, style, affect, analysis) or oruk-fourier (transcript plus native 15-label emotion)."New value: +"oruk-resonance (full local pipeline: transcription, emotion, style, affect, analysis) or oruk-fourier (parallel transcript and native 15-label emotion, with the shared 16-label style model). Resonance is the default."
    • Changedoruk_analyze_tone1 field changed
      • changedInput schema / properties / model / description
        Previous value: -"oruk-resonance (full local pipeline: transcription, emotion, style, affect, analysis) or oruk-fourier (transcript plus native 15-label emotion)."New value: +"oruk-resonance (full local pipeline: transcription, emotion, style, affect, analysis) or oruk-fourier (parallel transcript and native 15-label emotion, with the shared 16-label style model). Resonance is the default."
    • Changedoruk_transcribe_audio1 field changed
      • changedInput schema / properties / model / description
        Previous value: -"oruk-resonance (full local pipeline: transcription, emotion, style, affect, analysis) or oruk-fourier (transcript plus native 15-label emotion)."New value: +"oruk-resonance (full local pipeline: transcription, emotion, style, affect, analysis) or oruk-fourier (parallel transcript and native 15-label emotion, with the shared 16-label style model). Resonance is the default."
  10. 3 tool updates
    • Changedoruk_analyze_speech3 fields changed
      • addedInput schema / properties / diarize
        Added value: +{
+  "description": "Label speakers (oruk-resonance only; the model is switched to oruk-resonance automatically). Speakers are located with pyannoteAI diarization, then Resonance scores each speaker turn, so every segment carries a speaker field with its own text, emotions, and styles. Use for calls, meetings, and interviews. Adds $0.0040 per audio minute.",
+  "type": "boolean"
+}
      • changedInput schema / properties / model / description
        Previous value: -"oruk-resonance (default for transcription/analysis, highest accuracy) or oruk-spectra-1 (default for tone, most efficient)."New value: +"oruk-resonance (full local pipeline: transcription, emotion, style, affect, analysis) or oruk-fourier (transcript plus native 15-label emotion)."
      • changedInput schema / properties / model / enum
        Previous value: -[
-  "oruk-spectra-1",
-  "oruk-resonance"
-]New value: +[
+  "oruk-resonance",
+  "oruk-fourier"
+]
    • Changedoruk_analyze_tone3 fields changed
      • addedInput schema / properties / diarize
        Added value: +{
+  "description": "Label speakers (oruk-resonance only; the model is switched to oruk-resonance automatically). Speakers are located with pyannoteAI diarization, then Resonance scores each speaker turn, so every segment carries a speaker field with its own text, emotions, and styles. Use for calls, meetings, and interviews. Adds $0.0040 per audio minute.",
+  "type": "boolean"
+}
      • changedInput schema / properties / model / description
        Previous value: -"oruk-resonance (default for transcription/analysis, highest accuracy) or oruk-spectra-1 (default for tone, most efficient)."New value: +"oruk-resonance (full local pipeline: transcription, emotion, style, affect, analysis) or oruk-fourier (transcript plus native 15-label emotion)."
      • changedInput schema / properties / model / enum
        Previous value: -[
-  "oruk-spectra-1",
-  "oruk-resonance"
-]New value: +[
+  "oruk-resonance",
+  "oruk-fourier"
+]
    • Changedoruk_transcribe_audio3 fields changed
      • addedInput schema / properties / diarize
        Added value: +{
+  "description": "Label speakers (oruk-resonance only; the model is switched to oruk-resonance automatically). Speakers are located with pyannoteAI diarization, then Resonance scores each speaker turn, so every segment carries a speaker field with its own text, emotions, and styles. Use for calls, meetings, and interviews. Adds $0.0040 per audio minute.",
+  "type": "boolean"
+}
      • changedInput schema / properties / model / description
        Previous value: -"oruk-resonance (default for transcription/analysis, highest accuracy) or oruk-spectra-1 (default for tone, most efficient)."New value: +"oruk-resonance (full local pipeline: transcription, emotion, style, affect, analysis) or oruk-fourier (transcript plus native 15-label emotion)."
      • changedInput schema / properties / model / enum
        Previous value: -[
-  "oruk-spectra-1",
-  "oruk-resonance"
-]New value: +[
+  "oruk-resonance",
+  "oruk-fourier"
+]
  11. 3 tool updates
    • Changedoruk_analyze_speech2 fields changed
      • changedInput schema / properties / model / description
        Previous value: -"oruk-fourier (transcript plus native 15-label emotion), oruk-resonance (full local pipeline), or oruk-spectra-1 (efficient tone analysis)."New value: +"oruk-resonance (default for transcription/analysis, highest accuracy) or oruk-spectra-1 (default for tone, most efficient)."
      • changedInput schema / properties / model / enum
        Previous value: -[
-  "oruk-spectra-1",
-  "oruk-resonance",
-  "oruk-fourier"
-]New value: +[
+  "oruk-spectra-1",
+  "oruk-resonance"
+]
    • Changedoruk_analyze_tone2 fields changed
      • changedInput schema / properties / model / description
        Previous value: -"oruk-fourier (transcript plus native 15-label emotion), oruk-resonance (full local pipeline), or oruk-spectra-1 (efficient tone analysis)."New value: +"oruk-resonance (default for transcription/analysis, highest accuracy) or oruk-spectra-1 (default for tone, most efficient)."
      • changedInput schema / properties / model / enum
        Previous value: -[
-  "oruk-spectra-1",
-  "oruk-resonance",
-  "oruk-fourier"
-]New value: +[
+  "oruk-spectra-1",
+  "oruk-resonance"
+]
    • Changedoruk_transcribe_audio2 fields changed
      • changedInput schema / properties / model / description
        Previous value: -"oruk-fourier (transcript plus native 15-label emotion), oruk-resonance (full local pipeline), or oruk-spectra-1 (efficient tone analysis)."New value: +"oruk-resonance (default for transcription/analysis, highest accuracy) or oruk-spectra-1 (default for tone, most efficient)."
      • changedInput schema / properties / model / enum
        Previous value: -[
-  "oruk-spectra-1",
-  "oruk-resonance",
-  "oruk-fourier"
-]New value: +[
+  "oruk-spectra-1",
+  "oruk-resonance"
+]
  12. 3 tool updates
    • Changedoruk_analyze_speech2 fields changed
      • changedInput schema / properties / model / description
        Previous value: -"oruk-resonance (default for transcription/analysis, highest accuracy) or oruk-spectra-1 (default for tone, most efficient)."New value: +"oruk-fourier (transcript plus native 15-label emotion), oruk-resonance (full local pipeline), or oruk-spectra-1 (efficient tone analysis)."
      • changedInput schema / properties / model / enum
        Previous value: -[
-  "oruk-spectra-1",
-  "oruk-resonance"
-]New value: +[
+  "oruk-spectra-1",
+  "oruk-resonance",
+  "oruk-fourier"
+]
    • Changedoruk_analyze_tone2 fields changed
      • changedInput schema / properties / model / description
        Previous value: -"oruk-resonance (default for transcription/analysis, highest accuracy) or oruk-spectra-1 (default for tone, most efficient)."New value: +"oruk-fourier (transcript plus native 15-label emotion), oruk-resonance (full local pipeline), or oruk-spectra-1 (efficient tone analysis)."
      • changedInput schema / properties / model / enum
        Previous value: -[
-  "oruk-spectra-1",
-  "oruk-resonance"
-]New value: +[
+  "oruk-spectra-1",
+  "oruk-resonance",
+  "oruk-fourier"
+]
    • Changedoruk_transcribe_audio2 fields changed
      • changedInput schema / properties / model / description
        Previous value: -"oruk-resonance (default for transcription/analysis, highest accuracy) or oruk-spectra-1 (default for tone, most efficient)."New value: +"oruk-fourier (transcript plus native 15-label emotion), oruk-resonance (full local pipeline), or oruk-spectra-1 (efficient tone analysis)."
      • changedInput schema / properties / model / enum
        Previous value: -[
-  "oruk-spectra-1",
-  "oruk-resonance"
-]New value: +[
+  "oruk-spectra-1",
+  "oruk-resonance",
+  "oruk-fourier"
+]
  13. 3 tool updates
    • Changedoruk_analyze_speech2 fields changed
      • changedInput schema / properties / model / description
        Previous value: -"oruk-fourier (transcript plus native 15-label emotion), oruk-resonance (full local pipeline), or oruk-spectra-1 (efficient tone analysis)."New value: +"oruk-resonance (default for transcription/analysis, highest accuracy) or oruk-spectra-1 (default for tone, most efficient)."
      • changedInput schema / properties / model / enum
        Previous value: -[
-  "oruk-spectra-1",
-  "oruk-resonance",
-  "oruk-fourier"
-]New value: +[
+  "oruk-spectra-1",
+  "oruk-resonance"
+]
    • Changedoruk_analyze_tone2 fields changed
      • changedInput schema / properties / model / description
        Previous value: -"oruk-fourier (transcript plus native 15-label emotion), oruk-resonance (full local pipeline), or oruk-spectra-1 (efficient tone analysis)."New value: +"oruk-resonance (default for transcription/analysis, highest accuracy) or oruk-spectra-1 (default for tone, most efficient)."
      • changedInput schema / properties / model / enum
        Previous value: -[
-  "oruk-spectra-1",
-  "oruk-resonance",
-  "oruk-fourier"
-]New value: +[
+  "oruk-spectra-1",
+  "oruk-resonance"
+]
    • Changedoruk_transcribe_audio2 fields changed
      • changedInput schema / properties / model / description
        Previous value: -"oruk-fourier (transcript plus native 15-label emotion), oruk-resonance (full local pipeline), or oruk-spectra-1 (efficient tone analysis)."New value: +"oruk-resonance (default for transcription/analysis, highest accuracy) or oruk-spectra-1 (default for tone, most efficient)."
      • changedInput schema / properties / model / enum
        Previous value: -[
-  "oruk-spectra-1",
-  "oruk-resonance",
-  "oruk-fourier"
-]New value: +[
+  "oruk-spectra-1",
+  "oruk-resonance"
+]
  14. 3 tool updates
    • Changedoruk_analyze_speech2 fields changed
      • changedInput schema / properties / model / description
        Previous value: -"oruk-resonance (default for transcription/analysis, highest accuracy) or oruk-spectra-1 (default for tone, most efficient)."New value: +"oruk-fourier (transcript plus native 15-label emotion), oruk-resonance (full local pipeline), or oruk-spectra-1 (efficient tone analysis)."
      • changedInput schema / properties / model / enum
        Previous value: -[
-  "oruk-spectra-1",
-  "oruk-resonance"
-]New value: +[
+  "oruk-spectra-1",
+  "oruk-resonance",
+  "oruk-fourier"
+]
    • Changedoruk_analyze_tone2 fields changed
      • changedInput schema / properties / model / description
        Previous value: -"oruk-resonance (default for transcription/analysis, highest accuracy) or oruk-spectra-1 (default for tone, most efficient)."New value: +"oruk-fourier (transcript plus native 15-label emotion), oruk-resonance (full local pipeline), or oruk-spectra-1 (efficient tone analysis)."
      • changedInput schema / properties / model / enum
        Previous value: -[
-  "oruk-spectra-1",
-  "oruk-resonance"
-]New value: +[
+  "oruk-spectra-1",
+  "oruk-resonance",
+  "oruk-fourier"
+]
    • Changedoruk_transcribe_audio2 fields changed
      • changedInput schema / properties / model / description
        Previous value: -"oruk-resonance (default for transcription/analysis, highest accuracy) or oruk-spectra-1 (default for tone, most efficient)."New value: +"oruk-fourier (transcript plus native 15-label emotion), oruk-resonance (full local pipeline), or oruk-spectra-1 (efficient tone analysis)."
      • changedInput schema / properties / model / enum
        Previous value: -[
-  "oruk-spectra-1",
-  "oruk-resonance"
-]New value: +[
+  "oruk-spectra-1",
+  "oruk-resonance",
+  "oruk-fourier"
+]
  15. 7 tool updates
    • First observedoruk_analyze_speech
    • First observedoruk_analyze_tone
    • First observedoruk_check_credits
    • First observedoruk_create_trial_key
    • First observedoruk_get_started
    • First observedoruk_list_models
    • First observedoruk_transcribe_audio

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