kurdish-tts-stt

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

With no annotations provided, the description carries the burden. It explicitly discloses that the tool is static and 'costs nothing', implying no side effects or changes. For a simple listing tool, this is sufficient transparency.

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

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

The description is two concise sentences. The first states the core purpose, the second adds the static/cost-free nature. Every word earns its place, with no redundancy.

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

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

For a simple static listing tool with one fully-documented parameter, the description plus schema provides complete context. No output schema is expected, and the tool's simplicity means no further details are needed.

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

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

The only parameter (context) is fully described in the input schema (100% coverage). The tool description adds no additional semantics about the parameter, but the schema already handles it, so the baseline of 3 applies.

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

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

The description states 'List the supported Kurdish dialects and their scripts' with a specific verb and resource, clearly distinguishing it from sibling tools that handle voices, transcription, and speech synthesis. The added 'Static capability descriptor' further clarifies its role.

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

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

The phrase 'Static capability descriptor — costs nothing' provides clear context that this is a lightweight, read-only tool for discovering dialects/scripts. However, it does not explicitly mention alternatives or when not to use it, though sibling tools are naturally distinct.

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

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

No annotations are provided, so the description carries the full burden. It discloses that this is a metadata call with no credit consumption, implying no side effects, and returns speaker IDs. While it doesn't detail permissions or rate limits, for a read-only list operation this is sufficient context.

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

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

The description is concise, with a front-loaded purpose sentence, a return-value example, and a behavioral note. Three short sentences with no wasted words.

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

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

For a simple list tool with fully documented parameters, this description covers purpose, return format via example, and cost behavior. It also connects to synthesize_speech, providing orchestration context. The lack of an output schema is mitigated by the clear example of what is returned.

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

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

Schema description coverage is 100%, so the baseline is 3. The description does not add parameter-specific details beyond the schema; it only provides example speaker values that indirectly relate to the dialect parameter. No significant extra meaning is added.

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

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

The description uses the specific verb 'List' with the resource 'available Kurdish text-to-speech voices', clearly distinguishing it from siblings like synthesize_speech and list_dialects. It also provides example speaker IDs (sorani_1, kurmanji_236), making the tool's output unambiguous.

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

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

It explicitly states that the output 'speaker IDs' are 'to use with synthesize_speech', giving clear context for when to call this tool. The phrase 'Free metadata call — no credits consumed' implies it's a safe low-cost discovery call, but it does not explicitly mention alternatives or when not to use it.

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

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

With no annotations provided, the description fully discloses important behavioral traits: immediate quota consumption, return of a websocket_url, required streaming protocol (PCM16 mono 16kHz), and session duration limits. It also warns about the side effect of consuming quota, making the tool's behavior highly transparent.

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

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

The description is appropriately sized and front-loaded: the first sentence states the core purpose, the second is a critical warning, and the third conveys necessary protocol details. Every sentence adds unique value with no fluff or redundancy, making it highly efficient.

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

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

The tool is complex (live streaming), and the description covers the key aspects: return value (websocket_url), data format (PCM16 mono 16kHz), and control messages (finalize/done). However, it does not specify what the websocket will send back (e.g., transcription events), which would be useful given no output schema. Still, it is mostly complete for an agent to start using the tool.

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

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

Schema coverage is 100%, so both parameters (dialect, context) have descriptions in the schema. The tool description does not add extra meaning for these parameters; it focuses on the overall session behavior, not parameter semantics. Thus the baseline of 3 is appropriate.

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

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

The description clearly states the tool's action ('Start a live streaming speech-to-text session') and resource, and the title adds 'Kurdish', making it specific. It is distinct from siblings like transcribe_audio, which presumably handles non-live audio, and from list_dialects/synthesize_speech, so purpose is unambiguous.

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

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

The description provides clear context for when to use the tool: 'only call it when you are ready to connect' due to quota consumption. It does not explicitly mention alternatives or when not to use it, but the warning and focus on live streaming imply appropriate usage, warranting a 4 rather than a 5.

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

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

With no annotations, the description takes on the burden and discloses the API key requirement, billing implications, character limits, and speed semantics ('speed is caller-facing (higher = faster)'). However, it does not describe the default response format (e.g., WAV or base64) or potential error behavior, which would add further transparency.

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

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

Three sentences, each earning its place: purpose, requirements/limitations, and speed note. It is front-loaded with the core action and contains no filler.

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

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

The description covers purpose, authentication, billing, character limits, and an alternative for longer texts. Since there is no output schema, a brief note on the default response format (e.g., 'returns WAV audio' or 'returns base64 audio') would make it fully complete.

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

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

Schema coverage is 100%, so the baseline is 3. The description mentions the 600-character limit and speed direction, but these are already present in the schema (maxLength=600, speed description). It adds minimal nuance beyond the structured fields.

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

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

The description states 'Convert Kurdish text (Sorani or Kurmanji) to speech audio,' which clearly identifies the operation and resource. This distinguishes it from sibling tools like transcribe_audio and start_streaming_transcription.

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

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

The description explicitly provides usage boundaries: 'Max 600 characters per call over MCP — for longer texts call POST ... directly.' It also clarifies the requirement for a TTS API key, making when-to-use vs. direct API clear.

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

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

With no annotations, the description carries the full transparency burden. It discloses the API key requirement, metered billing, and the 4MB limit—key operational traits beyond the basic function. It does not mention return format or error behavior, but the disclosed constraints are meaningful.

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

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

Three sentences, each earning its place: purpose, key requirement/billing, and size limitation with fallback. The content is front-loaded and free of filler.

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

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

Given the absence of an output schema and annotations, the description covers critical operational context (auth, metering, size limit). It stops short of describing return values or when to choose streaming over batch, but for a transcription tool it provides a solid operational picture.

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

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

Schema description coverage is 100%, so the baseline is 3. The description adds no parameter-specific detail beyond what the schema already explains (e.g., audio_base64, dialect, context). It does not need to because the schema is thorough.

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

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

The description uses a specific verb+resource: 'Transcribe Kurdish audio (Sorani or Kurmanji) to text.' It clearly differentiates from siblings like synthesize_speech (opposite direction) and start_streaming_transcription (streaming vs. file-based).

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

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

The description provides concrete usage context: it requires an STT API key, is metered per minute, and has a 4MB size limit. It also names an explicit alternative for larger files (direct API call). However, it does not contrast with the sibling start_streaming_transcription, so some guidance gap remains.

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