RYLA

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

With no annotations provided, the description carries the full burden, and it clearly signals a read-only operation through the verb 'check' and the noun 'balance', implying no side effects. It also specifies that the balance belongs to the authenticated user, hinting at authentication requirements. While it lacks details like rate limits or error behavior, the simplicity of the operation means the description is sufficiently 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 a single, compact sentence that front-loads the action ('Check') and the resource ('RYLA credit balance'), followed by the user scope. It contains no filler or redundant information, making it highly concise and well-structured.

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 tool has no parameters, no annotations, and no output schema, the description adequately covers the essential context: what action is performed, on whose account, and what resource is queried. It does not specify the response format or units, but 'current credit balance' reasonably implies a numeric value, and the tool's low complexity makes this a minor gap.

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 input schema has zero parameters, so there are no parameter semantics to describe. The baseline for zero-parameter tools is 4, and the description appropriately focuses on the action and return value rather than parameters.

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 ('check') with a clear resource ('RYLA credit balance') and scope ('authenticated user'), making the tool's function immediately obvious. It is clearly distinct from the sibling tools, which are all about generation, gallery, or server info, so there is no ambiguity about what this tool does.

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 implies usage in the context of checking an authenticated user's balance before or after generation tasks, but it does not explicitly state when to use this tool over alternatives or when not to use it. No sibling tool handles balance checks, so context is inferred rather than explicitly articulated.

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 present, so the description carries the behavioral disclosure burden. 'List' conveys a read-only operation and 'authenticated user's' signals access scope, but it does not mention return shape, pagination details, or implications of the limit parameter. These gaps are moderate rather than severe for a read-only list 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?

One concise sentence with no fluff or repeated schema information. It is front-loaded with the action and resource, making it easy to scan.

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 low complexity (one optional parameter, no nested objects) and no output schema, the description gives a reasonable impression of what is returned without being overly long. It could be more complete by specifying the response format, but for this tool the description is adequate.

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 schema fully documents the only parameter (limit: min 1, max 50, default 20), so the description needs to add nothing. The description does not mention limit, but schema coverage is 100%, meeting the baseline.

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 a specific verb ('List') and resource ('the authenticated user's most recent generated images/jobs'), so its purpose is clear. It does not explicitly differentiate from siblings such as ryla_generation_status, and 'images/jobs' is slightly ambiguous, which keeps it from a 5.

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?

There is no guidance about when to prefer this tool over alternatives like ryla_generation_status or ryla_generate_image. The context implies 'when you want recent generated items,' but no explicit when-not or alternative selection is provided.

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 and does well by revealing that this is asynchronous (returns a jobId), requires Pro plan, and needs a pre-existing character. It does not mention error cases, costs, or rate limits, which prevents a higher score.

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 compact and front-loaded: it states the purpose, the plan requirement, prerequisite, and polling flow in four sentences with no filler. Every sentence contributes useful information for an agent.

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 an asynchronous tool with no output schema and no annotations, the description covers the main flow well: prerequisites, plan requirement, jobId return, and status polling. Minor omissions like error/error polling specifics and detailed failure behaviors mean it is not fully complete, but it is strong for a generation 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% and each parameter already has detailed descriptions, including constraints, defaults, enums, and the audioUrl/voiceNoteId relationship. The description adds only the idea that characterId must reference an existing character, which is mostly a usage note rather than new parameter-level semantics, so the baseline 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 a specific action and resource: generating a talking avatar video from a character face plus audio and names related workflow steps. It does not explicitly differentiate from overlapping siblings like ryla_generate_lip_sync or ryla_generate_video, so it stops short of full sibling differentiation.

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 sets clear preconditions (Pro plan required, character must already exist) and gives a workflow: use ryla_list_characters to get characterId and poll ryla_generation_status for jobId. It does not explicitly state when to choose an alternative generation tool, so it lacks an explicit exclusion or alternative comparison.

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 conveys the key asynchronous behavior: it returns a jobId rather than the image and tells the agent to poll ryla_generation_status. It does not cover credit costs or content-safety side effects, but the async pattern is a meaningful disclosure.

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 short sentences with no filler; the action and input dimensions are front-loaded and the async follow-up is stated efficiently. Every part earns its place.

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 generation tool with no output schema, the description covers the response protocol via jobId and the polling instruction, while the schema covers the inputs. Missing sibling-selection guidance and cost/safety warnings are the main gaps, but the tool remains invocable.

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?

All four parameters are already described in the schema, so the description adds no detailed parameter semantics beyond summarizing vibe/niche/promptInput. The schema carries the burden, so 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?

States a clear action — generate base character images — and the input dimensions (niche/vibe/prompt). The mention of jobId distinguishes it from direct-return generation tools, but it does not name a sibling like ryla_generate_character_sheet, so differentiation is implicit rather than explicit.

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 text implies usage for base character generation and provides a follow-up polling step. It does not state when to choose this tool over siblings such as ryla_generate_image or ryla_generate_character_sheet, nor does it give exclusions, leaving selection to inference from the name.

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 were provided, so the description carries the full behavioral disclosure burden. It correctly and explicitly discloses the asynchronous contract: the tool returns a jobId, not the final image, and requires polling via ryla_generation_status. This is the key non-obvious behavior an agent needs to know before invoking the 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 short, purposeful sentences with no wasted words. It front-loads the operation, then gives the return contract and polling step. The content is directly actionable without any 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?

For an asynchronous generation tool with no output schema and no annotations, the description covers the essential contract: it generates a character sheet, returns a jobId, and tells the agent to poll with ryla_generation_status. All four parameters are already documented in the schema, so the main missing details like valid angle presets or characterId semantics are optional and do not block correct invocation.

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 schema already documents all four parameters. The description adds only light contextual meaning, like 'from a base image' pointing to baseImageUrl and 'multi-angle' hinting at the angles parameter. This meets the baseline for good schema coverage but does not materially enrich parameter understanding.

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 verb 'Generate' with a specific deliverable ('multi-angle character sheet') and source ('base image'), so the tool's function is unmistakable. It also immediately distinguishes this from siblings like ryla_generate_image, ryla_generate_face_swap, and ryla_generate_base_image by naming the unique output type.

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 makes the usage context clear: use this when you need a multi-angle character sheet from a base image. It also provides the necessary follow-up action, 'poll with ryla_generation_status', which is important for agents to correctly complete the asynchronous flow. It does not explicitly list when-not-to-use alternatives, but the unique deliverable makes the selection fairly unambiguous.

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 of behavioral disclosure, but it only says 'Returns the generation result.' It does not disclose whether generation is asynchronous, whether credits are consumed, or what the result format looks like. The existence of ryla_generation_status suggests async behavior that this description leaves unaddressed.

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?

A single concise sentence with no filler; both the operation and the return expectation are front-loaded. Every phrase contributes meaningful information.

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?

This is a 5-parameter generation tool with no output schema and no annotations, so more context is needed about return format, async behavior, and parameter roles. The description only states a basic purpose and a vague return, which is insufficient for fully correct invocation.

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 applies. The description adds no parameter-level detail beyond repeating 'reference base image,' which is already in the baseImageUrl schema. The phrase 'Swap a character face' could mislead an agent into thinking characterId is required, when the schema marks it optional.

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 'Swap' and identifies the resource ('a character face onto a reference base image'), clearly distinguishing this tool from sibling generation tools like ryla_generate_image and ryla_generate_base_image. The return statement also sets an explicit expectation of an output.

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?

No guidance is provided on when to choose this tool over its siblings, nor are prerequisites such as having a characterId or an accessible base image URL mentioned. An agent must infer usage purely from the schema and sibling names.

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 behavioral disclosure burden. It discloses that the tool is asynchronous by returning a jobId that must be polled, and it clarifies the dependency on an existing character. It could have mentioned credit consumption or Pro restrictions, but the core operational behavior is transparent enough for correct invocation.

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 pack in the purpose, scope, primary alternative, prerequisite, and follow-up step with no wasted words. The most important differentiator, 'primary, full-featured image tool,' appears early.

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 a 25-parameter tool with no annotations and no output schema, the description covers the essential invocation lifecycle: find the character, generate, and poll the status. It also names the key alternative. It leaves some operational details like pricing or Pro gating to the schema, but the core flow is 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 description coverage is 100%, so the schema already documents all parameters thoroughly. The description adds useful context that characterId must reference an existing character and that the result is a jobId, but it does not add parameter-level format or default details 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 states a specific verb and resource: generate studio-quality images for an existing character. It also names the distinguishing property, full creative control, and explicitly positions itself as the primary full-featured image tool versus ryla_generate_base_image.

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 clearly says to prefer this tool over ryla_generate_base_image and states the prerequisite that the character must already exist, directing the agent to ryla_list_characters. It also explains the async workflow with jobId and ryla_generation_status. It does not enumerate all sibling alternatives, but the main competing image tool is explicitly covered.

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 burden of behavioral disclosure. It discloses the requirement for RYLA-hosted URLs, Pro plan, and the possibility of the feature being unavailable (with an error explanation). It does not describe the output format (e.g., video URL or job ID), whether the operation is asynchronous, or other error scenarios. This is adequate but not comprehensive for a generation 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-loaded with the core purpose, followed by critical constraints and availability caveats. Every sentence earns its place with no fluff or repetition. It is efficient and well-structured.

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 tool has three required parameters, no output schema, and no annotations, the description covers prerequisites and potential unavailability but omits key behavioral details like the return value (likely a job ID or video URL) and whether the operation is async (hinted by sibling ryla_generation_status). It does not address error handling beyond the unavailable-feature case, nor cost or time. This is a moderate gap for an agent to successfully invoke and monitor 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% and each parameter already has a description in the schema. The tool description reiterates that both URLs must be RYLA-hosted and owned, which reinforces the schema but adds no new meaning. The 'prompt' parameter is not elaborated beyond the schema's 'desired output' description. Thus, the description adds minimal value 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 tool generates a talking video via lip-syncing a portrait image to an audio track, with a specific resource and verb. It mentions the underlying tech (kie.ai InfiniTalk), making the purpose unmistakable. However, it does not explicitly name sibling tools or contrast with them, so it doesn't fully differentiate from alternatives like ryla_generate_avatar_video or ryla_generate_video.

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 explicit usage prerequisites: both URLs must be RYLA-hosted and owned, a Pro plan is required, and the feature may not be available. It implies when to use this tool (for lip-sync talking videos) and warns about potential unavailability. It does not mention alternative tools or when not to use this one, but the context is clear enough for an agent to decide.

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 disclosure burden and it does reveal the critical async behavior: returns a jobId and requires polling via ryla_generation_status. It also clarifies that the input is image-to-video on an existing character; however, it does not mention potential side effects like credit consumption or gallery storage.

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 compact clauses: purpose, prerequisite/lookup, and async result/poll. Every sentence carries necessary routing information 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 complex 9-parameter tool with no output schema, it gives the necessary invocation workflow: find an existing character, generate, and poll with jobId. It is slightly incomplete in not naming what to do when no character exists, but this is minor given the schema and named sibling tools.

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 of 3 applies; the schema already describes all 9 parameters including defaults and enums. The description adds only the contextual note that characterId must reference an existing character, but no new parameter-level meaning.

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 names the exact action and resource: 'Generate a Studio video for an existing character (image-to-video)'. This distinguishes it from sibling generation tools such as ryla_generate_image and ryla_generate_character_sheet by emphasizing the existing-character, video-specific scope.

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 the prerequisite ('Character must already exist') and points to ryla_list_characters for finding characterId, plus the follow-up ryla_generation_status polling step. It does not explicitly name an alternative when no character exists, but the routing is 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?

No annotations are present, so the description carries the full burden. It discloses the Pro plan requirement, the need for pre-existing assets (video and character), and the async behavior (returns jobId, poll with status). It doesn't cover side effects or error conditions, but for a generation tool this is reasonably 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?

Three sentences, front-loaded with the main purpose, followed by prerequisites and async flow. No fluff, every sentence earns its place.

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 tool with 7 parameters and no output schema, the description covers the essential flow: what it does, prerequisites, how to get the result (jobId + polling). It doesn't enumerate all optional parameters, but the schema already does that. Missing error handling details, but the core is 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 baseline is 3. The description adds value by clarifying that videoUrl must be an uploaded RYLA video and that the character must already exist, which complements the schema. It also notes that outfitPrompt/backgroundPrompt are only used when their enabled flags are true, though the schema already says that.

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 a specific verb and resource: 'Swap a character face into an existing video (face swap onto uploaded footage)'. It clearly distinguishes this from the sibling ryla_generate_face_swap (which likely targets images) by specifying 'existing video' and 'uploaded footage'.

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?

Provides explicit prerequisites: videoUrl must be an already-uploaded RYLA video, character must exist, and Pro plan is required. It also names the sibling ryla_list_characters for finding characterId and ryla_generation_status for polling. It doesn't explicitly state when not to use this tool, but the conditions are clear enough.

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 usefully reveals that the character must already exist and that the output is speech audio (TTS). However, it does not disclose whether generation is asynchronous, whether the result needs polling via ryla_generation_status, how credits are consumed, or what the actual return payload looks like.

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 with no filler. The primary purpose is front-loaded, and the second sentence delivers the only critical prerequisite and sibling routing needed. Every word earns its place.

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?

With no output schema and no annotations, the description must explain the full call flow. It explains what to do before the call, but never says what the tool returns or how to retrieve the generated audio. The omission is significant given that the sibling ryla_generation_status strongly suggests an asynchronous generation workflow.

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 schema already documents all six parameters in detail. The description only reinforces the importance of characterId by pointing to ryla_list_characters; it does not add semantic meaning beyond what the schema provides.

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 the specific action ('Generate speech audio (TTS)') and the exact resource ('in an existing character's voice'). This clearly differentiates it from the sibling generation tools such as ryla_generate_image, ryla_generate_video, and ryla_generate_face_swap, which all target different modalities.

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 states a prerequisite ('Character must already exist') and directly names the sibling tool to use when that prerequisite is unmet ('use ryla_list_characters to find a characterId'). This gives the agent concrete routing guidance.

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 of behavioral disclosure. It only states that a status is checked; it does not say whether the call is read-only, whether it can be polled repeatedly, what statuses can be returned, or what happens for an invalid/expired jobId.

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 a single, front-loaded sentence with no wasted words. It names the action, the target, and the required identifier immediately.

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 one-parameter status tool with no output schema, the description plus schema covers what an agent needs to invoke it correctly. It could mention expected output or polling behavior, but those are not required for basic invocation.

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%, and the single jobId parameter is already documented as coming from a ryla_generate_* tool call. The tool description adds no parameter-level detail beyond what the schema provides, so the baseline score 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 identifies a specific verb ('Check'), a distinct resource ('status of a generation job'), and the key input ('jobId'). This cleanly separates it from the sibling generation tools, which create jobs rather than report on them.

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 implies this tool is used after a generation call because it requires the jobId from a ryla_generate_* tool, but it never explicitly says when to use it or that it should be used for polling/completion checks. No alternatives or exclusions are mentioned.

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 that the operation is scoped to the authenticated user, that it only lists existing characters, and that character creation is not possible through the API. While it doesn't describe output shape or pagination, the read-only nature is clear from the verb and 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?

Two sentences, no filler, and the most important information is front-loaded. The first sentence states action, scope, and purpose; the second adds a critical caveat about creation.

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, no-output-schema tool, the description is complete enough for an agent to select and invoke it correctly. It explains why to use it, what it returns conceptually (existing characters/characterIds), and the one common misunderstanding (creation happens elsewhere).

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 coverage is 100%, so there is no parameter-level burden for the description to compensate for. The description's mention of returning a characterId for downstream tools adds useful context even though no input parameters exist.

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 ('List') with a clear resource ('the authenticated user's existing characters (AI influencers)') and a concrete purpose ('pick a characterId for the other generation tools'). This clearly distinguishes it from the sibling generation, status, and account tools.

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 when to use the tool: when you need a characterId for other generation tools. It also provides crucial exclusion guidance by noting that no tool creates characters and that creation happens in the RYLA app at app.ryla.ai, preventing the agent from searching for a non-existent sibling.

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 behavioral transparency burden. 'Get' implies a read-only operation, but the description does not disclose whether the tool makes a live connection, returns static configuration, or may expose sensitive connection details. It also does not describe the response shape.

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?

One concise, front-loaded sentence communicates the tool's purpose with no filler or redundancy. Every word adds meaning.

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 tool, invocation is simple and the description gives enough to identify the tool's purpose. However, without an output schema or annotations, 'configuration and connection info' is vague about the actual returned fields, so an agent must infer what the response will contain.

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, so there is no parameter documentation burden. The schema is trivially covered, and the description appropriately avoids inventing parameter guidance.

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 ('Get') and names the exact resource ('RYLA external MCP server configuration and connection info'). It is clearly distinct from all sibling tools, which cover generation, account credits, gallery, and character operations.

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 implies the tool is used whenever server configuration or connection details are needed, and none of the sibling tools cover that concern. However, it does not explicitly state when to use it versus alternatives or provide exclusions.

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