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Server Quality Checklist

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Latest release: v0.1.0
Disambiguation5/5
Each tool has a clearly distinct purpose: generation tools are split by modality (image, video, audio), batch operations, and raw access; job management tools cover lifecycle steps; account and workspace info tools are separate; media management is isolated. No two tools could easily be confused.
Naming Consistency4/5
Most tools use snake_case and follow a verb_noun pattern (list_models, generate_image, cancel_job), but there are inconsistencies: 'show_generations' vs 'list_jobs', 'get_aspect_dimensions' vs 'list_...', and some tools are noun_noun (workspace_wallet, media_status). The deviation is minor and does not hinder understanding.
Tool Count3/5
With 29 tools, the server is on the heavy side, exceeding the typical 3-15 range. However, the breadth of functionality (multiple generation types, batch operations, account management, job lifecycle, media library) justifies a larger surface. It is balanced and not excessive.
Completeness4/5
The tool set covers the main workflows: generation (image, video, audio, batch, storyboard), job management (check, wait, cancel, list, download), account/workspace info, cost estimation, and media upload/status. Minor gaps like media deletion or workspace creation are present but not critical for core usage.
Average 3.5/5 across 29 of 29 tools scored. Lowest: 2.4/5.
See the Tool Scores section below for per-tool breakdowns.
- 1 of 1 community issues answered or closed in the last 6 months
- 13 commits in the last 12 weeks
- No stable releases found
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI status not available
This repository is licensed under MIT License.
This repository includes a README.md file.
No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.
Tip: use the "Try in Browser" feature on the server page to seed initial usage.
Add a glama.json file to provide metadata about your server.
If you are the author, simply .
If the server belongs to an organization, first add glama.json to the root of your repository:
```
{
  "$schema": "https://glama.ai/mcp/schemas/server.json",
  "maintainers": [
    "your-github-username"
  ]
}
```
Then . Browse examples.
Add related servers to improve discoverability.

How to sync the server with GitHub?

Servers are automatically synced at least once per day, but you can also sync manually at any time to instantly update the server profile.

To manually sync the server, click the "Sync Server" button in the MCP server admin interface.

How is the quality score calculated?

The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).

Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.

Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).

Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.

Tool Scores

Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description gives no behavioral details beyond the basic read operation. Without annotations, the agent has no insight into authentication requirements, rate limits, or potential side effects.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise at one short sentence, but it is also unstructured and lacks any contextual framing. Brevity here sacrifices completeness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has an output schema (not shown) and no parameters, the description should at least hint at what the output contains. 'Workspace credit balance' is incomplete for agent decision-making.
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 zero parameters, so the input schema is fully covered (100%). The description trivially adds no parameter information, but none is needed.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Workspace credit balance.' states the tool's purpose succinctly, indicating it retrieves the credit balance. However, it lacks a verb and does not distinguish from siblings like 'workspace_usage' or 'account_info'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives such as 'account_info' or 'workspace_usage'. The description does not mention prerequisites, limitations, or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must fully disclose behavior. It mentions account scoping and 'recent' history but lacks details on ordering, filters, or state of jobs. Important behavioral traits like pagination behavior or what 'recent' means are omitted.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, concise sentence that front-loads the key purpose. It is not verbose, but may be too minimal for adequate understanding.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of sibling tools and the presence of pagination parameters, the description is incomplete. It does not clarify the sorting order, what constitutes 'recent', or how this differs from 'list_jobs', leaving ambiguity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has two parameters (limit, offset) with 0% description coverage in the schema. The description does not mention these parameters or explain how they affect the output, leaving the agent uninformed.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states it shows 'recent generation history' for your account, clearly identifying the resource and scope. However, it does not distinguish from sibling tools like 'list_jobs' which may serve a similar purpose.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives such as 'list_jobs' or 'check_job'. The context signals include many related sibling tools, but the description offers no decision criteria.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, so the description carries full burden. It discloses a side effect (saving to disk), but lacks details on permissions, file format, overwrite behavior, or what happens if the job is not completed.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely short (one sentence), which is concise but too minimal. It lacks structure and fails to convey essential details within that brevity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no annotations, 0% schema coverage, and the existence of an output schema (not shown), the description is incomplete. It does not explain what 'save to disk' entails, output format, or error conditions.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description provides no explanation of the two parameters (job_id and output_dir) despite 0% schema coverage. The agent receives no guidance on values or behavior of these parameters.
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 action: re-fetch a completed job's results and save to disk. It distinguishes from sibling tools like check_job (status check) and show_generations (listing results) by using the verb 'download'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage when a job is completed, but does not explicitly state when to use it versus alternatives. No when-not-to-use or alternative tool mentions are provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description discloses that local input_files are auto-uploaded and discusses model versioning. However, it does not mention whether the tool is destructive, whether it consumes credits, or how it handles errors/timeouts. With no annotations, this is moderate coverage.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is relatively concise with two paragraphs. The first line is front-loaded with the tool's action. The second paragraph, though dense with model names, is necessary for the model parameter. No redundant sentences.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has 15 parameters, no parameter descriptions in the schema, and an output schema exists, the description should provide more context on parameter usage. It fails to explain key parameters like negative_prompt, aspect_ratio, extra_params, leaving the agent uninformed.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, so the description should compensate. It adequately explains the 'model' parameter syntax and unlimited eligibility, but 13 other parameters (seed, account, batch_size, etc.) receive no explanation. The mention of input_files auto-upload is minimal.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The first sentence states 'Generate a single image', clearly indicating the core purpose. However, the description is cluttered with model naming details and doesn't explicitly distinguish this tool from similar ones like generate_image_batch.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus siblings. It mentions unlimited eligibility but does not compare with alternatives like generate_image_batch or generate_storyboard, nor does it specify prerequisites such as account or model availability.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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 does not mention whether the operation is read-only, any authentication needs, or what 'active workspace' means. The description adds minimal behavioral context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence, concise and front-loaded. However, it lacks depth; additional context would improve completeness without harming conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no parameters, no annotations, but an output schema exists, the description is still insufficient. It does not explain the concept of 'active workspace', how usage is calculated, or any potential restrictions. A more complete description would aid agent selection.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0 parameters and 100% schema coverage, the description adds meaning by specifying the output is a chart of credit usage. According to calibration, 0 params baseline is 4, and the description meets that baseline.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it provides a credit-usage chart for the active workspace. It distinguishes from siblings like 'account_info' and 'workspace_wallet' by focusing on credit usage in chart form. However, it could be more specific about the data included.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool compared to related tools (e.g., 'estimate_cost' or 'workspace_wallet'). Without hints, an AI agent may struggle to decide which tool to invoke.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, and the description does not mention behavioral traits like read-only nature, authentication needs, or rate limits. For a read-only info tool, this is a significant gap.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Extremely concise and front-loaded. Could be a full sentence but effectively communicates the tool's purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the output schema exists and no parameters, the description is adequate but minimal. It does not help the agent distinguish from similar info tools or provide usage hints.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With zero parameters, the description adds value by detailing the output content. Schema coverage is 100%, so no compensation needed.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool returns plan info, credit balances, and a flag. The action (retrieving) is implied. It distinguishes from siblings like unlimited_status by returning more comprehensive data.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives such as workspace_wallet or unlimited_status. The description does not specify prerequisites or context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations present, so description carries full burden. Mentions 'in-progress job' and DELETE method, but does not disclose reversibility, idempotency, or error conditions. Minimal behavioral context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence with no wasted words. Includes both purpose and HTTP method. Could be slightly more structured but effective.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given simple tool with one parameter and no annotations, description covers basic purpose. However, lacks usage guidelines and parameter details, making it minimally adequate.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0% (no description for job_id). Tool description does not add any semantics about the parameter's format, constraints, or relationship to job types.
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?
Clearly states the verb 'cancel' and resource 'in-progress job', with the HTTP method DELETE. Distinguishes from sibling tools like check_job and wait_for_job.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Implies usage for in-progress jobs but does not explicitly state when to use versus alternatives or any prerequisites. No when-not-to-use guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided. Description does not disclose behavioral traits such as read-only nature, authentication requirements, or rate limits. The term 'canonical' is undefined.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Single, concise sentence with no unnecessary words. Could possibly benefit from more detail without losing conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the simplicity of the tool and presence of an output schema, the description is barely adequate. It provides the gist but lacks parameter details and usage context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, yet description only mentions aspect ratio and resolution without defining valid values or formats (e.g., '16:9' or '2k'). Does not compensate for missing schema 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?
Description clearly states the tool returns canonical width and height in pixels for a given aspect ratio and resolution, distinguishing it from sibling tools that perform generation or other operations.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives like generate_image or list_models. Context is implied but not explicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, and the description only states the basic action. It does not disclose file type restrictions, size limits, overwrite behavior, authentication needs, or any side effects, leaving the agent underinformed for safe 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 a single, well-structured sentence that efficiently conveys the tool's action and purpose without superfluous words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite a simple tool with one parameter, the description omits essential details like valid file formats, path syntax, error scenarios, and upload behavior. An output schema exists but is insufficient to compensate for missing behavioral context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description does not explain the 'file_path' parameter format (e.g., absolute vs relative, supported file extensions). The parameter remains opaque beyond its name.
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 action (upload), the resource type (local image/video), and the purpose (use as input on subsequent generations). It distinguishes the tool from sibling generation tools and media listing tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is given on when to use this tool versus alternatives like show_medias or media_status. There are no usage conditions, prerequisites, or exclusions mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, and the description does not disclose whether this is a read or write operation, or any side effects. It simply describes what the tool returns, missing behavioral context.
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 single, concise sentence that conveys the core purpose without any fluff. It is front-loaded and every word adds value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the zero-parameter input and availability of an output schema, the description is acceptable but could benefit from specifying whether it's a getter or setter, and what the output format is beyond the values mentioned.
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?
There are no parameters, so the baseline is 4. The description adds meaning beyond the empty schema by explaining the tool's purpose and expected values (4/8/12/16).
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly indicates the tool is about the concurrent-slot tier, listing specific values (4/8/12/16). It distinguishes from siblings like auth_status or account_info by focusing on concurrency limits, though the verb (get/set) 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.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives like queue_status or unlimited_status. The description does not mention prerequisites or context for using the tool.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It mentions 'unlimited' and the model, but fails to disclose other behavioral traits like rate limits, error behavior, or output format. The statement about a 'verified contract' is vague and incomplete.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise at three lines, but the second line is cryptic and could be streamlined. No waste, but clarity could be improved.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 10 parameters, 0% schema coverage, no annotations, and an output schema not described, the description is inadequate. It fails to provide a complete picture for effective tool use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, so description must compensate. It mentions prompt (not text), model, voice_id, voice_type, but contradicts the schema (model vs tts_model). It does not explain most parameters (wait, timeout, download, account, extra_params), leading to potential confusion.
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 generates audio from text using a specific model (text2speech_v2), distinguishing it from sibling tools like generate_image or generate_video. The verb 'generate' and resource 'audio' are explicit.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides some usage context (unlimited, works with Turkish and other languages, get voice_id from list_voices) but does not explicitly state when to use this tool versus alternatives or give when-not-to-use guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. It mentions using a specific endpoint, shot prompts, and shared reference images, but lacks details on return format or potential side effects.
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?
Two concise sentences front-load core functionality with no wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With 10 parameters, an output schema, and complex behavior, the description is too brief, omitting many parameter meanings and return values.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Only shots and reference images are described; the remaining 8 parameters (wait, timeout, download, etc.) have no explanation, and schema description coverage is 0%.
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 it generates a multi-shot storyboard with character/style continuity, distinguishing it from single image or video generation siblings.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives like generate_image or generate_video, nor any prerequisites or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description implies a read-only operation ('Check status') but does not disclose additional behavioral traits such as what statuses are possible, whether it returns information for all provided IDs, or any rate limits. With no annotations, more context would be beneficial.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is very concise, consisting of a single 7-word sentence. It is front-loaded and gets straight to the point, though it could be slightly more informative without becoming verbose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (one parameter, output schema exists), the description covers the basic action and input. However, it could be more complete by explicitly stating that it accepts multiple IDs and that the output provides status information. The output schema partially compensates.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description only mentions 'by id' but does not elaborate on the meaning or format of the media_ids parameter. Since the schema has no description (0% coverage), the description should compensate but fails to explain the purpose or constraints of the IDs.
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 action ('Check status'), the resource ('media items'), and the input method ('by id'). It distinguishes itself from siblings like 'show_medias' and 'queue_status' which have different purposes.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives, nor does it mention any exclusions or prerequisites. Users have no context for selecting it over similar tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Without annotations, the description minimally hints at read-only behavior via 'info', but does not explicitly state safety, authorization needs, or side effects. For a simple parameter-less tool, this is adequate but not detailed.
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 single concise phrase with no wasted words. It is front-loaded and earns its place.
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?
With an output schema present and no parameters, the description covers the essential return fields. However, it does not clarify what 'active workspace' means, leaving minor ambiguity about scope.
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?
No parameters exist (schema coverage 100%). Baseline score of 4 applies as the description adds no param info, which is appropriate given the empty schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states that the tool provides info about the active workspace and lists specific fields (id, name, type, role). It lacks an explicit verb but is unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus siblings like list_workspaces or account_info. The description implies it is for the active workspace, but no explicit context or alternatives are provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided. Description does not disclose behaviors like read-only nature, auth requirements, rate limits, or pagination. Relies on agent inference.
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?
Two sentences, front-loaded with purpose, no redundancy. Efficient and to the point.
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?
Output schema exists to describe return values. For a simple list with one optional parameter, description is mostly complete, though lacking pagination or ordering info.
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?
Description adds meaning by mentioning possible filter values (image, video, audio) beyond schema's anyOf/null, but schema coverage is 0% and no enum is provided.
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?
Description clearly states verb 'list' and resource 'generation models', with optional filtering by category. Distinct from sibling generation tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Indicates optional filter usage but no explicit when-to-use or when-not-to-use compared to alternatives like listing jobs or workspace details.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided; the description only says 'List all your workspaces' without disclosing behaviors like pagination, rate limits, or authentication requirements.
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?
Single sentence, immediate action, 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?
A simple list with no parameters and an output schema; description is sufficient for its purpose, though minimal context about 'workspaces' could help new users.
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?
Input schema has zero parameters, and the description implies no filtering ('all your workspaces'), which aligns. Baseline 4 for 0 parameters, and description adds no extra but doesn't need to.
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 'List all your workspaces' clearly states the action (list) and resource (workspaces), distinguishing it from sibling tools like workspace_details or workspace_usage.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives like workspace_details, which might be better for detailed info on a single workspace.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description bears full responsibility. It mentions pagination (a behavioral trait) but omits critical information such as authentication requirements, rate limits, side effects, or response format. The presence of an output schema partially mitigates this, but the description adds little beyond the schema.
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 single concise sentence that conveys the core functionality. It is front-loaded with essential information and contains no extraneous 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?
The tool has a simple interface with three parameters and an output schema. The description covers pagination and optional filtering, which is sufficient for basic usage. While it does not differentiate deeply from siblings, the output schema fills in return value details.
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 0%, requiring the description to compensate. It adds that the 'kind' parameter accepts 'image' or 'video' values, which is helpful. However, 'limit' and 'offset' parameters are not elaborated upon; their meanings are inferred from pagination context but not explicitly defined.
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?
Description clearly states the verb 'show' and resource 'medias', specifies it is a paginated library, and mentions an optional kind filter. This distinguishes it from siblings like media_upload or show_generations.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for browsing the media library with optional filtering, but provides no explicit guidance on when to use this tool versus alternatives like show_generations or media_upload. No exclusions or prerequisites are mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, so description carries full burden. It reveals blocking behavior and optional download, but omits edge cases (timeout handling, failure behavior, download destination). Adds some value beyond schema but incomplete.
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?
Single sentence with two clear clauses, front-loaded with main action. No unnecessary words; perfectly concise.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given tool complexity (4 parameters, blocking, optional download, output schema exists), description is too sparse. It lacks details on timeout behavior, error handling, download specifics, and polling frequency. Insufficient for reliable agent invocation without further context.
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 has 0% description coverage; the description adds meaning for timeout (max wait), download (optional result retrieval), and interval (polling frequency) implicitly. However, it does not explicitly explain parameter semantics or format, leaving gaps.
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 blocks until a job finishes and optionally downloads results, with a specific verb 'Block' and resource 'job'. It distinguishes from siblings like check_job (non-blocking) and cancel_job.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for waiting on job completion with optional download, but does not explicitly guide when to use vs alternatives like check_job or download_job_result. No clear when-not-to-use or exclusion criteria.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations present, so description must reveal behavior. It covers concurrency, fire-and-forget vs blocking, and return of job IDs, but omits error handling, cost, or rate limits.
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?
Two tight paragraphs, front-loaded with key behavior. Every sentence adds value with no redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 11 parameters, only two are mentioned. Output schema exists but not described. Core flow is covered, but many details missing for a complete understanding.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, yet description only explains wait and max_concurrent. The other 9 parameters (model, resolution, etc.) are not described, leaving the agent to infer from their names.
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?
Description clearly states verb 'queue' and resource 'image batch', with parallel execution. Distinguishes from sibling 'generate_image' by focusing on batch and concurrency.
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?
Explicitly explains when to use wait=False vs wait=True, and mentions polling with queue_status/list_jobs. Lacks exclusions or alternatives but provides clear context for usage.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description reveals the underlying endpoint (GET /reference-elements/voices) and the output fields. It implies a read-only operation with the verb 'reads'. Since no annotations are present, the description carries the full burden and does so reasonably, though it could explicitly state idempotency or auth needs.
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 concise with three sentences. The first sentence states the main purpose, the second explains usage, and the third provides a practical example. No unnecessary words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is simple and an output schema exists, so return values are covered. However, the description fails to document the two parameters, which is a significant gap for a simple list tool. The agent would need to infer parameter meanings from context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has two parameters (size and account) with 0% schema description coverage, yet the description does not mention either parameter. Therefore, it adds no meaning beyond the schema, leaving the agent to guess the purpose of `size` and `account`.
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 it lists TTS preset voices with specific fields (id, name, gender, preview mp3) and explicitly links to the sibling tool generate_audio. It distinguishes itself from other list tools by focusing on voice presets for audio generation.
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 explains when to use the tool (before generate_audio to obtain a voice_id) and provides a specific use case for Turkish voiceover. However, it lacks explicit exclusion criteria or alternatives to other list tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so description bears full responsibility. It implies read-only behavior but does not disclose whether results are paginated, cached, or if the snapshot is instantaneous. Terms like 'in-flight' and 'pool' are ambiguous.
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 single, clear sentence with no unnecessary words. It is front-loaded and efficient for a zero-parameter tool.
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 the tool's simplicity, the description covers the core purpose. An output schema exists, so return value documentation is not required. Minor missing context about what 'snapshot' entails (e.g., real-time vs. cached) but overall adequate.
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 zero parameters, and the schema coves 100% trivially. The description does not need to elaborate on parameters. Baseline of 4 is appropriate as no parameter details are missing.
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?
Description clearly states the tool captures a snapshot of in-flight jobs across all accounts in the pool. It specifies the verb (snapshot) and resource (in-flight jobs across all accounts), distinguishing it from siblings that might focus on single jobs or specific accounts.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Description provides no guidance on when to use this tool versus alternatives. No mention of prerequisites, scenarios, or exclusions. Siblings like concurrent_state could overlap, but no differentiation is offered.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden. It mentions minting a fresh JWT, which implies a non-destructive operation, but does not disclose side effects like token invalidation or rate limits. This is acceptable but not thorough.
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 single sentence that is front-loaded with the action and resource. No wasted words or redundancy.
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 zero parameters and the presence of an output schema (which explains return values), the description is sufficient. It clearly conveys the tool's purpose and behavior for an agent to use correctly.
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?
There are zero parameters, and schema description coverage is 100% by default. The description does not need to add param info, so a baseline of 4 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 uses a specific verb ('verify') and resource ('credentials for every configured account') and clearly communicates the action of minting a fresh JWT. This distinguishes it from sibling tools like account_info or queue_status which have different purposes.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives (e.g., account_info for checking single account). There is no mention of prerequisites, when not to use, or other contextual signals that help an agent decide.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
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 the polling mechanism and the local-then-remote API fallback, which is key behavioral context. However, it does not mention idempotency or error handling.
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 single efficient sentence that conveys the action, scope, and lookup strategy with 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?
With one parameter and an existing output schema, the description captures the core functionality and fallback mechanism. It could briefly hint at the response type, but the description is sufficient for a simple poll tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the tool description does not elaborate on the 'job_id' parameter beyond the schema. The parameter is self-explanatory by name, but the description fails to add any semantic value or format guidance.
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 uses a specific verb 'poll' and resource 'single job', and clarifies the scope 'across account pool' with a fallback order 'local registry, then remote API'. This clearly differentiates it from siblings like 'wait_for_job' (blocking) and 'list_jobs' (listing many).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies polling a single job but does not explicitly state when to use this tool versus alternatives such as 'wait_for_job' (blocking) or 'list_jobs'. No direct usage guidance or exclusions are provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the burden. It adds context about session scope but lacks details on pagination, job status filters, or authentication requirements.
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?
Single sentence, direct, and front-loaded. Every word adds value with no redundancy.
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 no parameters, no annotations, and existence of an output schema, the description provides sufficient context for a simple list-all tool. Could mention job status coverage but overall adequate.
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?
Input schema has zero parameters (coverage 100%), so description is not required to add parameter info. Baseline 4 applies as no additional detail needed.
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 uses a specific verb 'List' and resource 'jobs', clearly stating the scope 'across every account in the pool (this session)'. It effectively distinguishes from sibling tools like check_job (single job) or cancel_job.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance on when to use this tool versus alternatives like check_job or show_generations. The usage is implied but not stated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It transparently reveals the tool reads three endpoints (/workspaces/unlim-activations, /subscriptions/bundle/all-unlim/status, /user) and explains the meaning of an empty activations list. This goes beyond basic description.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise with three sentences, each adding distinct information: purpose, data sources, and implication of empty list. It is front-loaded with the core purpose. A tiny improvement could be structuring the parameter explanation, but it is already efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the presence of an output schema (not shown), the description does not need to detail return values. It adequately explains the significance of an empty activations list. However, the lack of explanation for the 'account' parameter leaves a gap in completeness for a tool with one optional parameter.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has 0% description coverage, so the description should explain the 'account' parameter. However, it does not mention what the parameter is for (e.g., account identifier, workspace ID). The description adds no value beyond the parameter name, leaving the agent guessing its 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: checking which models are currently unlimited-active for the account. It uses a specific verb ('reads') and resource ('unlimited status'), and the focus on 'unlimited-active' distinguishes it from sibling tools like auth_status or account_info.
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 context on when to use the tool: to check if unlimited status is active, and notes that an empty activations list means generation costs credits, referencing estimate_cost for cost estimation. This implies when not to rely on unlimited status, but explicit 'when-not' or alternatives beyond estimate_cost are not given.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, so the description carries the full burden. It clearly notes this is a read-only operation ('WITHOUT spending credits') and specifies the endpoint. However, it omits mentioning authentication requirements or any potential rate limits, 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise with four sentences, each adding value. The core purpose is front-loaded, followed by usage context and a concrete example. No unnecessary words or repetition.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the presence of an output schema, the return shape is covered. The description includes usage context and an example, but lacks clarity on scope (all models? workspace-specific?) and doesn't mention the 'account' parameter. For a simple tool with one optional parameter, this is minimally adequate but has gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The single parameter 'account' has no description in the schema (0% coverage), and the tool description does not explain its purpose or expected values. Since the description should compensate for this gap, the lack of parameter semantics is a notable weakness.
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 provides a credit cost table per model/resolution/mode without spending credits, and even gives a concrete example. It distinguishes itself from sibling tools like unlimited_status by mentioning it should be checked first.
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 before generating on credits' and 'Check `unlimited_status` first', providing clear when-to-use and prerequisite guidance. The alternative of checking unlimited status is mentioned, fulfilling the when-not-to-use hint.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the burden. It explains key behaviors: params passed verbatim with use_unlim added, api_version endpoint selection, and input_files merging, providing sufficient transparency for the agent.
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 concise (~90 words), front-loaded with purpose, and structured to provide quick understanding without superfluous content.
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 8 parameters, nested objects, and an output schema, the description covers core functionality and key parameters, though it omits details on wait, timeout, and download. The output schema existence reduces need to describe returns.
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 coverage is 0%, so the description must add meaning. It explains params, api_version, and input_files, but does not cover kind, wait, timeout, or download, leaving gaps despite baseline of 4.
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 identifies the tool as an 'escape hatch' for calling any model with a custom params dict, listing specific use cases (face-swap, character-swap, etc.) and distinguishing it from siblings by targeting advanced/raw access.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
It explicitly states when to use the tool (for models with known schemas, specific tasks) and references external documentation, but does not explicitly exclude cases where sibling tools like generate_image would be more appropriate.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It discloses parallel execution, routing to least-busy account, 429 failover, and the two modes of operation (wait vs non-wait). It also mentions the image-to-video feature via 'input_files_per_prompt'. It does not cover error handling beyond failover or auth requirements, but the key behavioral aspects 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise at about 80 words, structured into two clear paragraphs. The first paragraph immediately states the core purpose, and the second provides usage details. Every sentence adds value without redundancy.
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 the tool's complexity (14 parameters, 1 required, no enums, with output schema), the description covers the essential parallel behavior and the two main usage modes. It explains the least-busy routing and image-to-video input. However, it does not detail other parameters like 'mode', 'model', 'duration', or their effects, which would be useful for an agent to invoke correctly. The output schema exists, so return values are covered elsewhere.
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 0%, so the description must compensate. It explains 'wait' and 'input_files_per_prompt' in detail, but other important parameters like 'mode', 'model', 'duration', 'resolution', etc. are not mentioned. With 14 parameters, only a few are clarified, so the description adds value for some but leaves many undocumented.
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 function: generating many videos in parallel across all accounts in the pool. The emphasis on 'MANY' and 'PARALLEL' distinguishes it from the single-video sibling 'generate_video'. It uses a specific verb ('Generate') and resource ('videos').
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 explains when to use this tool (for multiple accounts at once, parallel generation) and how to use it ('N prompts fan out concurrently with 429 failover'). It also distinguishes between 'wait=True' (returns when all done) and 'wait=False' (returns job ids for polling via 'queue_status'), providing clear guidance. However, it does not explicitly mention when not to use it or compare to other batch-like siblings such as 'generate_image_batch'.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description fully covers behavioral traits: it is sequential per account, resolution fallback walks 1080p -> 720p -> 480p, unlimited is capped per model, and local input_files are uploaded as start_image. It also lists unlimited-eligible models, giving the agent a clear understanding of system behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured with the purpose first, followed by key details and distinctions. It is efficient but not overly verbose; a few sentences could be tightened, but overall it communicates essential information without unnecessary fluff.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description covers core functionality and key behaviors, but given 17 parameters and no annotations, it is incomplete regarding many parameter details. The output schema exists but is not referenced to explain return values. For a tool of this complexity, more parameter documentation would improve completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. It adds meaning for a few parameters: model (lists eligible models), resolution_fallback (explains fallback order), input_files (uploaded as start_image), and aspect_ratio (default 9:16). However, many parameters (mode, seed, wait, account, timeout, download, duration, media_role, extra_params, input_images, generate_audio) are left unexplained, leaving significant gaps for the agent.
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 it generates ONE video via the v2 API with automatic resolution fallback. It specifies it is for single videos and distinguishes from the sibling tool generate_video_batch, which handles parallel generation across multiple accounts.
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?
The description explicitly tells when to use this tool versus generate_video_batch: for many videos in parallel across accounts, use the batch version. It also outlines defaults (9:16 aspect ratio for viral clips), resolution fallback behavior, and unlimited-eligible models, providing clear context for appropriate usage.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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