RunAPI Vidu MCP Server

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

No annotations are provided, so the description carries the full behavioral burden, and it does not say whether this requires authentication (a sibling named 'login' hints at an auth model that is never confirmed), whether results are cached or live, or whether any side effects occur. One sentence of pure intent leaves the agent without the operational context a zero-annotation tool needs.

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

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

A single short sentence with the purpose front-loaded and no filler or redundancy. It is arguably under-specified rather than bloated, which is penalized in other dimensions, but as written every word earns its place.

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

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

There is no output schema and no annotations, so the description must explain the shape of the result, and it does not: an agent cannot tell whether pricing is per-request, per-second of video, per endpoint, or returned as a table. For a lookup tool whose entire value is the returned pricing data, this is a meaningful incompleteness.

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

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

Schema description coverage is 100%, so both 'model' and 'action' are already documented with their defaults, making the schema the primary source of parameter meaning. The description adds only the enclosing context ('vidu model line'), which mildly clarifies the valid model space but adds no syntax or format detail beyond the schema, so the baseline 3 applies.

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

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

States a specific verb ('Look up') and resource ('RunAPI pricing') scoped to the 'vidu model line', which is enough for an agent to distinguish it from siblings like login, get_task, or image_to_video that perform entirely different jobs. It does not explicitly contrast with a sibling, but none of the listed siblings overlap in function, so differentiation is effectively achieved.

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 offers no when-to-use guidance: it never says to call this before invoking image_to_video/reference_to_video, nor whether it is a prerequisite, cacheable, or optional. There are no exclusions or named alternatives, leaving the agent to infer the tool's role in a workflow entirely on its own.

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

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

No annotations are provided, so the description carries the full behavioral burden. It discloses that the operation is a read ('Fetch') and what it returns ('current status and latest result payload'), but omits auth requirements, rate limits, error behavior, and whether calls are safe to repeat. This is a clear gap.

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

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

Single front-loaded sentence with no filler; it states the action and the two pieces of information returned. Every word earns its place.

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

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

For a simple two-parameter fetch tool with full schema coverage and no annotations, the description is largely sufficient for invocation. However, since there is no output schema, it only vaguely describes the return ('status and latest result payload') and omits polling or retry context, leaving minor gaps.

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

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

Schema description coverage is 100%, so both parameters are already documented in the schema. The description does not mention task_id or action, adding no meaning beyond the schema; the baseline of 3 applies when the schema does the heavy lifting.

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?

Specific verb 'Fetch' with a clear resource ('current status and latest result payload') and target ('vidu task'). This distinguishes it from sibling creation tools like image_to_video and reference_to_video, which start tasks rather than check them.

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

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

No explicit when-to-use guidance, no mention of polling after task creation, and no alternatives named (e.g., that this is the tool to call after image_to_video or reference_to_video). Usage is only implied by the purpose.

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

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

With no annotations, the description carries the full burden. It does disclose the asynchronous submit-task pattern and the shape of the return (task id, status, output URLs), which is real value. However, it says nothing about auth requirements, cost implications (a check_pricing sibling exists), or how wait/poll_interval_ms change behavior.

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

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

Two short sentences with zero filler; the action is front-loaded and the return contract follows immediately.

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

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

For a 10-parameter tool with no annotations and no output schema, the description does cover the return values (compensating for the missing output schema) but leaves the async/polling workflow, auth, and cost context unexplained. Adequate but with clear gaps.

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 80%, so the schema already documents most parameters including the image URL constraints and resolution values. The description adds no parameter-level detail beyond the schema, so the baseline 3 applies.

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

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

States a specific verb and resource ('Create a Vidu task ... image to video') and the parenthetical disambiguates it from the sibling reference_to_video. It stops short of explicitly routing the agent between the two video-generation siblings, but the purpose is unambiguous.

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

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

No guidance on when to pick this over reference_to_video, no mention that get_task exists for retrieving results of a submitted task, and no prerequisites (e.g. login) are stated. The agent is left to infer usage entirely.

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

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

With no annotations, the description carries the behavioral burden. It discloses the interactive browser flow and the file write side effect (config.json). However, it does not mention that it may overwrite existing credentials or that it could block waiting for user input, though these are implied.

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, well-structured sentence that front-loads the action ('Authenticate RunAPI') and provides necessary details without extraneous information.

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

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

For a simple login tool with one optional parameter and no output schema, the description covers the core purpose and side effect. It lacks an explicit statement that this is a prerequisite for other tools, but that is implied.

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

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

Schema description coverage is 100% (the only parameter 'force' has a description). The tool description adds no additional meaning about parameters beyond the schema, so the baseline of 3 applies.

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

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

The description clearly states the tool's purpose with a specific verb ('Authenticate'), target resource ('RunAPI'), method ('browser PKCE login flow'), and side effect (saving to config.json). It is distinct from sibling tools, none of which relate to authentication.

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

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

The description implies usage (to authenticate RunAPI) but does not explicitly say when to run it (e.g., before other RunAPI tools) or when to use the 'force' parameter. Since there are no alternative auth tools among siblings, 'vs alternatives' is not applicable.

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

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

With no annotations, the description carries the full behavioral burden, and it only discloses return values (task id, status, output URLs). It omits that the call is asynchronous, that wait=true (the default) blocks until a terminal status, that timeouts/poll intervals are configurable, and that the provider validates and may reject remote reference files.

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

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

Two short sentences with the core action and return shape front-loaded and no filler. It is tight but arguably too terse for a 12-parameter, async, no-annotation tool.

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 12-parameter async generation tool with no annotations and no output schema, the description leaves out the polling/wait semantics, validation failure behavior, and two undocumented params. Mentioning the return fields is a partial offset, but an agent cannot call this correctly without additional assumptions.

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 83%, so the schema already documents most parameters (audio, aspect_ratio, reference URLs with their limits, callback_url, etc.). The description adds nothing beyond that, and two parameters (timeout_ms, poll_interval_ms) are undocumented in both places. Baseline 3 applies.

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

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

States a specific verb (Create), resource (a Vidu task on RunAPI), and modality (reference to video), which implicitly separates it from the sibling image_to_video. It never names the sibling explicitly, so the differentiation relies on the reader parsing 'reference' vs 'image'.

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

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

There is no when-to-use guidance, no condition for choosing this over image_to_video, and no mention that reference_image_urls is mandatory or what happens when reference images conflict with the prompt. The agent gets no routing help from the description.

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