Script in, finished 1080p narrated video out. Pay per call in USDC via x402.
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Average 3/5 across 7 of 7 tools scored. Lowest: 1.5/5.
Most tools have clearly distinct purposes: submit, check, list, fetch, voices, and info. However, fetch_video and get_job overlap when a job is done, as get_job's result already includes video information, which could cause misselection.
Most tools follow a verb_noun pattern (fetch_video, get_job, list_jobs, list_voices, submit_video_job). But payment_info and service_info are noun-only, breaking the pattern and mixing action and informational tools.
Seven tools is well-scoped for a video generation service, covering discovery, job submission, status checking, listing, and result fetching. No unnecessary bloat or thinness.
The core workflow is complete: users can discover the service and pricing, list voices, submit a job, check status, and fetch the final video. Minor gaps exist, such as no ability to cancel or delete jobs, but these are not essential for the primary use case.
fetch_videoBInspect완성 영상의 경로와 크기. 잡이 done 일 때만 유효하다.
| Name | Required | Description | Default |
|---|---|---|---|
| job_id | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It discloses that the tool is only valid when the job is done and that it returns the path and size of the completed video. However, it does not explain error behavior, what happens if the job is not done, permissions, or any side effects, leaving gaps in behavioral understanding.
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 sentence with two clauses, providing the core output and the validity condition. It is efficient and front-loaded, with no unnecessary words. However, it is slightly too terse to cover all essential aspects, making it a 4 rather than a 5.
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 needs to explain both behavior and return values. It mentions path and size but does not specify their format, structure, or error cases. The tool is simple, but the description still leaves notable gaps, such as what happens when the job is not done or the job_id is invalid.
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 0%, and the description does not explicitly explain the job_id parameter. The phrase about the job being done indirectly references the job, but it does not describe what job_id represents, its format, or constraints. The description fails to compensate for the lack of schema documentation.
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 '완성 영상의 경로와 크기' (Path and size of the completed video) identifies the output but lacks an explicit verb such as 'fetch' or 'retrieve'. The tool name helps, but the description itself does not clearly state the action. It does distinguish from siblings like get_job by focusing on the video artifact, though this is implicit.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The phrase '잡이 done 일 때만 유효하다' (Only valid when the job is done) provides a clear condition for when to use the tool. This gives the agent a direct cue to invoke this tool only after job completion, but it does not mention alternatives like get_job for status checking, so it lacks explicit exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_jobBInspect제출한 잡의 상태. done 이면 result 에 영상 정보가 들어 있다.
| Name | Required | Description | Default |
|---|---|---|---|
| job_id | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full responsibility for behavioral disclosure. It discloses one key behavior: if the job is done, the result contains video information. However, it does not explain other job states, polling behavior, error conditions, or whether the tool is read-only. This is minimal but not completely absent.
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 short sentence that conveys the core purpose and one key behavior. It is front-loaded and contains no unnecessary words or repetition of schema fields.
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 lack of annotations and output schema, the description is incomplete. It does not explain possible job states, what happens when the job is not done, how to obtain a job_id, or the shape of the 'result' field. The description is too sparse for a tool with no structured context.
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 has one parameter (job_id) with 0% description coverage. The tool description does not mention job_id or explain its meaning beyond the schema's title 'Job Id'. Since schema coverage is low, the description should compensate, but it does not, leaving the parameter relationship implicit.
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 checks the status of a submitted job ('제출한 잡의 상태') and that on completion ('done') the result contains video information. This distinguishes it from sibling tools like list_jobs (listing jobs) and fetch_video (retrieving video), though it does not explicitly name alternatives.
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 no guidance on when to use this tool versus alternatives. It does not mention that this tool should be used to poll a job's status after submission, nor does it direct users to list_jobs or submit_video_job for other operations. The use case is implied but not stated explicitly.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
list_jobsDInspect최근 잡 목록.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No |
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 only says 'recent job list' and reveals nothing about what the tool returns, ordering, pagination, or side effects. This is essentially a label, not a behavioral description.
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 extremely short, but brevity here is under-specification rather than effective conciseness. It lacks a verb and essential context, so the short length does not serve clarity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple list tool with one parameter and no output schema, the description should at least clarify the return payload and the meaning of 'recent'. It does neither, and the presence of sibling tools makes the lack of distinction even more problematic.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The only parameter 'limit' has no schema description (0% coverage) and the tool description does not mention it. The agent receives no explanation of what 'limit' controls or how it affects results, making it impossible to use the parameter correctly.
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 is a noun phrase '최근 잡 목록' (Recent job list) that restates the tool name without a clear verb like 'retrieves' or 'lists'. It identifies the resource (jobs) and a qualifier (recent), but does not explicitly state the action, leaving the purpose ambiguous.
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 about when to use this tool versus alternatives like get_job or submit_video_job. There is no mention of contexts or exclusions, leaving the agent without direction for tool selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
list_voicesCInspect쓸 수 있는 나레이션 목소리.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden for behavioral disclosure. It only states that available narration voices exist, but does not disclose whether the operation is read-only, requires authentication, or how results are returned. This is a significant gap for a tool that presumably fetches data.
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 extremely brief, a single noun phrase. While it is concise with no wasted words, it is under-specified and would benefit from a full sentence explaining the tool's function and return value. For a trivial no-parameter tool, the brevity is acceptable but not ideal.
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 there is no output schema, the description should at least indicate what the tool returns (e.g., a list of voice identifiers or metadata). It merely states availability, leaving the agent without concrete information about the expected result format or content. The simplicity of the tool does not fully compensate for this absence.
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 is empty with zero parameters, so the baseline for parameter semantics is 4. The description need not explain parameter meanings since there are none, and it does not introduce confusion.
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 '쓸 수 있는 나레이션 목소리' translates to 'Available narration voices', clearly indicating the tool provides a list of usable narration voices. While it lacks an explicit verb, the tool name 'list_voices' and the noun phrase unambiguously convey the purpose, and it is distinct from sibling tools dealing with video, jobs, and payment.
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 no guidance on when to use this tool versus alternatives. There is no mention of prerequisites, typical use cases, or exclusions. An agent would have to infer from the tool name and sibling context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
payment_infoCInspect결제를 어떻게 받는지. 호출 전에 읽으면 좋다.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must disclose behavior. It only says 'how payments are received' without stating whether this is a read-only info tool, what it returns, side effects, or requirements. There is no behavioral transparency beyond a vague hint.
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?
While extremely short, the description is under-specified rather than concise. It lacks essential details about the tool's function, so the brevity does not serve the agent's understanding.
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 parameters, output schema, or annotations, the description is the sole source of information. It fails to explain what the tool actually returns or how it fits with sibling tools like service_info. The context provided is insufficient for 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?
The tool has zero parameters and the schema is empty, which gives a baseline of 4. The description does not need to explain parameters, and it correctly implies there are none to configure.
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 '결제를 어떻게 받는지' (how payments are received) essentially restates the tool name without specifying a clear action. It does not use a verb like 'get' or 'list' to indicate what the tool does, leaving the purpose vague and tautological.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The phrase '호출 전에 읽으면 좋다' (good to read before calling) implies it is a preliminary step, but it does not specify which calls it applies to or when to avoid using it. No alternatives or exclusions are mentioned, making the guidance minimal.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
service_infoAInspect이 서비스가 무엇을 하고 얼마인지. 호출 전에 읽으면 좋다.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
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 indicates the tool's informational nature but does not explicitly state read-only behavior or absence of side effects. The simplicity of the tool (no parameters) makes this a minor omission.
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 that concisely states the tool's purpose and provides a usage recommendation. Every word earns its place with no redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a parameterless info tool with no output schema, the description sufficiently covers what the tool does and when to use it. It does not specify the format of the returned information, but this is acceptable given the absence of an output schema and the tool's simple nature.
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 schema coverage is 100%, so there is no need for the description to clarify parameters. It correctly adds no parameter information beyond what the schema already conveys.
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 that the tool provides information about what the service does and how much it costs. This specific purpose differentiates it from sibling tools like payment_info, which likely handles payments, and fetch_video, which fetches videos.
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 advises reading before calling other tools, which provides a clear 'when to use' context. It does not explicitly name alternatives or exclusions, but the guidance to read it pre-call is sufficient for a general info tool.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
submit_video_jobAInspect대본으로 1080p 영상 제작을 시작한다. 유료 — 결제 없이 부르면 402 를 돌려준다.
script: 나레이션 본문 · title: 도입 4초 상단 표시 · voice: list_voices() 참고
| Name | Required | Description | Default |
|---|---|---|---|
| seed | No | ||
| speed | No | ||
| title | No | ||
| voice | No | female_warm | |
| script | Yes | ||
| subtitles | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full responsibility for disclosing behavior. It does include a notable behavioral trait: the paid requirement and the specific HTTP 402 error response if unpaid. Yet it omits important post-submission behavior, such as returning a job ID and how to track progress (e.g., via get_job). This is a significant gap for an async job submission 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 extremely concise: one sentence for the main purpose, one for payment, and a compact parameter list. It is front-loaded and every word adds value. There is no fluff or repetition of schema types. This is an exemplary concise structure.
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's complexity (6 parameters, no output schema, no annotations), the description provides a reasonable baseline: purpose, payment boundary, and key parameter hints. However, it lacks critical context for a job-submission tool—there is no mention of what the successful response contains, whether it is asynchronous, or that get_job/list_jobs should be used to track progress. This leaves the agent under-informed about the full 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 0%, so the description must compensate for parameter meaning. It explains three parameters: script (narration text), title (displayed top for first 4 seconds), and voice (refer to list_voices()). However, it leaves seed, speed, and subtitles unexplained. These are non-obvious (e.g., speed could mean playback speed or generation speed), and the description's partial coverage is insufficient.
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 Korean description states '대본으로 1080p 영상 제작을 시작한다' (starts 1080p video production from a script), which clearly identifies the action (submit/start) and resource (video creation). It also distinguishes from sibling tools like get_job and list_jobs, which are retrieval-focused. The deliberate mention of '1080p' adds specificity.
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 includes a key usage condition: '유료 — 결제 없이 부르면 402 를 돌려준다' (paid — returns 402 if called without payment), which tells the agent this tool should only be called after payment is ensured. It also points to list_voices() for voice selection, offering a clear alternative reference. However, it does not explicitly contrast with siblings like fetch_video, so it isn't a full 5.
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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