Kooma — Bambara AI

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

There are no annotations, so the description carries the full burden. It adds a useful behavioral fact: voice identifiers vary from one account to another and should not be hard-coded. The verb 'Liste' implies a read-only operation, though it does not explicitly state side-effect-free behavior. Still, this is sufficient for a simple listing tool.

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 sentences, front-loads the purpose, and contains no redundant wording. Every sentence earns its place: one for what the tool returns, one for when and why to call it.

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 zero-parameter listing tool with no output schema, this description is complete: it names the resource, the output fields, the relationship to the sibling TTS tool, and an important data instability caveat. An agent has everything needed to invoke it correctly.

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 tool has zero parameters and the schema is an empty object with 100% coverage. There is nothing for the description to add about parameters, so the 0-parameter baseline of 4 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 clearly states a specific verb ('Liste') and resource ('voix bambara disponibles pour la synthese vocale'), and specifies the returned fields: identifiant, nom, and genre. It also explicitly ties the tool to kooma_text_to_speech, distinguishing it from the other siblings.

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 gives explicit when-to-use guidance: 'A appeler avant kooma_text_to_speech'. It also explains why it must be called first—voice IDs vary per account and must never be hard-coded—which gives the agent a clear decision rule.

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 burden. It discloses that the tool converts text to audio and returns it, which is useful, but it does not mention length limits, latency, output format handling, or any failure modes. Adequate but shallow.

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?

Two sentences, front-loaded with the action and output, followed by the prerequisite. Every sentence earns its place and there is 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?

For a simple text-to-speech tool, the description provides the essential purpose, output, and prerequisite. The schema covers the parameters, so nothing is missing for a correct call, though behavioral caveats and explicit sibling routing could make it more 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 reinforces the voice parameter by specifying a Bambara voice and pointing to kooma_list_voices, but it adds little beyond what the schema already documents for text, voice, and format.

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 a specific action (transform text into audio), the resource (Bambara voice), and the output (returns the audio). This distinguishes it from siblings like kooma_transcribe_from_url and kooma_translate, while also pointing to kooma_list_voices as the source of valid voices.

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 gives a clear prerequisite: use kooma_list_voices to obtain a valid voice identifier. It does not explicitly state when not to use the tool versus transcription/translation, but the purpose is clear enough that an agent can infer the right context.

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 carries the behavioral disclosure burden. It reveals meaningful operational constraints: public HTTPS access, 25 MB file limit, and automatic language detection. It does not mention response format or error behavior, but the core operation and limitations are 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 three short sentences with no filler. The main action is front-loaded, and each subsequent sentence adds a necessary constraint or behavior.

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 single-parameter tool with no output schema, the description provides enough context to invoke it correctly: what input to provide, what constraints apply, and what the tool does. It could be slightly stronger by describing the output form more explicitly, but 'en texte' already implies the transcript result.

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% and the single parameter 'url' is already described in the schema as 'URL HTTPS publique du fichier audio ou video.' The description adds useful file-level context such as the 25 MB limit and audio/video support, but it does not add significant parameter-level semantics beyond the schema.

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 action ('Transcrit en texte'), the resource ('un fichier audio ou video accessible par une URL publique en HTTPS'), and the result (text). It is easily distinguishable from sibling tools like kooma_list_voices, kooma_text_to_speech, and kooma_translate, which serve different purposes.

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 gives clear conditions for use: the input must be a public HTTPS audio/video URL, the language is auto-detected, and the file cannot exceed 25 MB. It does not explicitly contrast with sibling tools or state when not to use it, but the use case is well specified.

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 carries the full behavioral burden. It adds useful scope context (supported languages and code format), but it does not disclose output format, source detection behavior, limits, or side effects. 'Traduit' implies a safe read-like transformation, so this is not a severe gap.

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?

Two tight sentences: the first states the core purpose, the second gives the essential code-format guidance. No filler or redundant repetition of schema details.

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?

Adequate for a simple translation tool, but the '13 autres langues' set is not enumerated and no reference to accepted codes is provided, so an agent may not know all valid target codes. Return behavior is implicit but not critical.

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 adds value by explaining the combined language-script code scheme with concrete examples (bam_Latn, fra_Latn, eng_Latn), helping agents construct valid source and target values.

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?

Description uses a specific verb ('Traduit un texte') and identifies the resource ('entre le bambara et 13 autres langues'), clearly distinguishing it from sibling tools like TTS, transcription, or voice listing.

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?

Usage context is implied by the translation verb and language set, but there is no explicit when-to-use statement or comparison with siblings such as kooma_text_to_speech. The optional source detection is mentioned in the schema, not the description.

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