vivideo

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

No annotations provided, but the description fully covers behavioral traits: it's a read-only operation (no mention of side effects), returns specific fields, and is safe to call frequently. No contradictions.

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

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

Two sentences: first states purpose and return values, second gives usage guidance and confirms it's cheap. No wasted words, front-loaded with key info.

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 zero parameters, no output schema, and low complexity, the description fully explains what the tool does, what it returns, and when to use it. Complete for an info-retrieval tool.

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

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

No parameters exist, so baseline is 4. The description doesn't need to add parameter info and does not repeat anything from the empty schema.

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

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

The description clearly states the tool retrieves account plan, premium status, and remaining credit balance, with a specific verb 'Get' and resource 'account info'. It distinguishes from siblings by focusing on account-level data needed for video generation decisions.

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?

Explicitly advises when to use: to decide if the user can generate a video (needs premium plan and enough credits). Also notes it's cheap and safe to call often, contrasting with other tools that may be expensive or have side effects.

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 exist, so the description bears full responsibility. It discloses the return format ('{ configured: boolean }'), states that the tool never asks for or exposes the key, and implies it performs a read-only check. Fully transparent.

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

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

Three concise sentences, front-loaded with the main purpose. Every sentence adds value: call order, return value, and next steps. No redundant or 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 parameterless tool with no output schema, the description fully covers what the tool does, what it returns, and how to interpret the result. No gaps in information needed 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, so the description cannot add parameter-level detail beyond what the schema provides. However, it explains the purpose of the tool with no input, which is sufficient. Baseline for 0 parameters is 4.

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

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

The description uses a clear verb ('Check') and specifies the resource ('whether a Vivideo API key is present'). It uniquely identifies the tool's purpose among siblings, as other tools do not focus on API key presence.

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?

Explicitly instructs 'Call this FIRST', providing a strong usage directive. Also describes what to do if the result is false (ask user to add header) and where to obtain the key, guiding appropriate invocation.

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?

Discloses key behaviors: async return with video id and status ('processing' vs 'preview'), automatic idempotency-key handling, and rendering requiring premium plan and credits. No annotations provided, so description carries full burden and handles it well.

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?

Efficient three-sentence description that front-loads the core action. Each sentence adds value, though a bullet structure could improve readability for the workflow details.

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

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

Covers the async nature, plan restrictions, next steps, and idempotency. Missing parameter details and error handling, but given the complexity and lack of output schema, it provides a solid overview.

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 67%, and the description adds minimal new parameter context beyond the schema (e.g., brand_kit_id from list_brand_kits). It does not explain folder_id, name, or orientation, which remain undocumented.

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 it creates a video in AUTO mode where Vivideo handles scripting and production. It distinguishes from manual mode via sibling context and uses specific verbs ('creates', 'returns', 'call').

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

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

Provides clear when-to-use context: for fully automatic video generation from a prompt. Mentions next steps (call wait_for_video or get_video) and plan requirements, but does not explicitly exclude scenarios or mention alternatives beyond the sibling list.

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?

The description discloses key behaviors: operation inferred from inputs (image_url triggers image-to-video), constraints on resolution/duration/aspect_ratio, automatic idempotency handling, and return of video id and status. With no annotations, it covers essential aspects, though auth and rate limits 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.

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

The description is a single concise paragraph that front-loads the core purpose and flows logically to constraints and follow-up. Every sentence adds value without 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?

Given the tool's complexity (13 params, no output schema, no annotations), the description covers creation flow, constraints, idempotency, and next steps. It is fairly complete but could elaborate on error handling for all parameters.

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 only 23%, so the description adds meaning for key parameters like model, image_url, and constraints on resolution/duration. However, many parameters (e.g., style, negative_prompt) are unexplained, leaving gaps.

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 it creates a video in 'MANUAL mode' by sending a prompt to a specific model, distinguishing from 'create_auto_video' by emphasizing manual control and mentioning image_url for image-to-video variant.

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 says to get model ids from list_models, notes that invalid values return a 400 listing allowed values, and suggests subsequent use of wait_for_video or get_video. It provides clear context for when to use this tool, but does not explicitly exclude cases like automatic generation.

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?

Discloses that it provides an estimate, not a charge, and that the exact amount is returned upon creation. No annotations exist, so the description carries the full burden; it adequately covers the non-destructive, read-only nature.

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

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

Three sentences with no wasted words. The first sentence delivers the core purpose immediately. All sentences add unique value: purpose, clarification, and usage guidance.

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 estimation tool with no output schema, the description covers purpose, usage context, behavioral nuance, and a sibling reference. Could mention return shape, but not critical.

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

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

Schema coverage is 50% (2 of 4 parameters have descriptions). The description reiterates that model and resolution are required for manual mode, adding no new info beyond the schema. Baseline 3 is appropriate.

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

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

The description clearly states the tool estimates credits for a generation before creation using published per-model rates. It distinguishes itself from create tools by emphasizing 'BEFORE creating it' and referencing the exact charge returned later.

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?

Explicitly suggests pairing with check_account to confirm affordability. Implies usage as a pre-check before creation. Does not list specific when-not-to-use scenarios, but context is clear.

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

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

With no annotations, the description fully discloses behavior: status values, video_url meaning, refund and error on failure, and cost nature (cheap). This is comprehensive for a read 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, front-loads the purpose, and each sentence adds non-redundant value. No wasted words.

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?

The description covers the main return fields (status, video_url, error) but does not mention other possible response fields (e.g., metadata). However, for a simple status check this is likely sufficient. It references a sibling tool for polling, enhancing completeness.

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?

There is only one parameter (id) and schema coverage is 100%. The description adds minimal context (the id comes from a create call), which is helpful but not significantly beyond the schema.

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

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

The description clearly states the tool retrieves a video's status and result, listing possible status values and what each implies (video_url for completed, error for failed). It distinguishes from sibling wait_for_video by explicitly recommending it for polling.

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

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

The description provides explicit usage guidance: it is cheap and should not be called in a tight loop; instead prefer wait_for_video for polling. This clarifies when and when not to use the tool.

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 full burden. It discloses that stock avatars are 'grouped by person, each with a `looks` array', and mentions key fields. It does not mention side effects or rate limits, but as a read-only list operation, this is adequate. The structural detail adds value beyond a generic 'list avatars'.

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

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

The description is two sentences, front-loaded with the primary purpose, and contains no fluff. Every part earns its place.

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

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

The tool is simple with 3 optional params and no output schema. The description explains how the output feeds into another tool (create_auto_video), which is valuable context. It does not detail the full return structure, but for a list tool, this is reasonably complete.

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

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

Schema coverage is 67% (two of three parameters have descriptions). The description adds meaning by explaining how search and limit are used to keep responses small. It does not mention gender, but the enum provides clarity. Overall, the description complements the schema well.

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: 'List available avatars for auto-mode videos'. It specifies the resource (avatars) and the verb (list). It also distinguishes from siblings by mentioning the connection to create_auto_video and the structure of stock vs owned avatars.

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

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

The description explicitly explains when to use this tool (to obtain avatars for auto-mode videos) and how to use the results: 'pass a looks[].avatar_id (or an owned avatar's id) as `avatar_id` in create_auto_video'. It also advises on parameter use: 'Use `search`/`limit` to keep responses small'.

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, so description must cover behavior. It states the tool lists brand kits and returns brand_ref ids. However, it omits details like authentication, output structure, or whether multiple kits are returned, leaving some gaps.

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 efficient sentences with no wasted words. Front-loads the action and immediately clarifies purpose and usage.

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 no-parameter list tool, the description covers the main action and usage. Missing explicit output format (array vs object) but adequate for agent 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?

Zero parameters; schema coverage is 100% trivially. Baseline of 4 applies. Description adds value by explaining that the returned ids are used in create_auto_video.

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?

Clearly states 'List the account's brand kits' with specific resources (logo, colors, fonts, motion style) and connects to create_auto_video, distinguishing it from sibling list tools.

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

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

Explains the output is for use in create_auto_video, giving clear context for when to invoke. Lacks explicit exclusions or alternative comparisons, but context is sufficient.

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 provided, so description carries full burden. The description explains the output content (operations, durations, etc.) and that it's a read operation, but lacks details on pagination or dynamic behavior. Adequate for a simple listing.

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

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

Two sentences: first states main purpose, second adds details and usage hint. No wasted words, front-loaded.

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 no output schema, description details what the response contains and its purpose (to build a create request). Could mention if auto-generate pipeline is always present, but overall complete for a list tool with one param.

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

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

Schema coverage is 100%, and the description adds context: 'Filter with `mode` to keep the response small.' This explains the benefit beyond the schema's description.

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 lists video models for manual mode plus the auto-generate pipeline, specifying the resource and action. It distinguishes itself from sibling tools like create_* and list_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 explains when to use the tool (to get model details for building a create request) and suggests filtering with `mode` to reduce response size. However, it does not explicitly mention when not to use it or compare to alternatives.

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?

Discloses ordering behavior ('newest first') and filtering/limit functionality, but lacks details on response format or pagination, though adequate for a list tool without annotations.

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, efficient sentence with key action front-loaded; no wasted words.

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?

Complete for a simple list tool with two parameters and no output schema; covers ordering, filtering, and limit rationale.

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?

Adds value beyond the input schema by explaining that limit controls response size and status filters results, partially compensating for 50% schema description coverage.

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

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

Description clearly states 'List the account's videos, newest first' with specific verb and resource, distinguishing from sibling tools like get_video or create_manual_video.

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

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

Provides guidance on filtering by status and limiting count to keep responses small, but does not explicitly exclude scenarios or mention alternatives.

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 provided, but disclosure of 'Voice cloning is not available via the API' adds behavioral context. Also explains return value (voice ids). Adequate for a list tool.

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

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

Two sentences with no wasted words. Purpose is front-loaded; every sentence adds value.

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 4 parameters, the description covers what the tool returns, how to use filters/limit, and a key limitation. Could mention default limit behavior but not a major gap.

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

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

Schema description coverage is 50%; description adds meaning by specifying filters (language/gender/search) and limit usage, compensating for undocumented parameters like gender and search.

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

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

The description uses a specific verb-resource pair ('List available voices') and distinguishes from sibling tools (e.g., list_avatars) by specifying 'for auto-mode videos' and tying to create_auto_video.

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

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

Clear context: use when you need voice IDs for auto videos. Provides filtering options but does not explicitly state when not to use or suggest alternatives among siblings.

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?

In the absence of annotations, the description fully discloses behavior: charges run on same project, first video free, returns state if already rendering, returns upgrade_required error for free accounts. No contradictions.

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 concise, front-loaded with the key condition, and every sentence adds value. No unnecessary words.

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 single parameter and no output schema, the description adequately covers all scenarios (upgraded, already rendering, still free). It is complete for the tool's complexity.

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

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

Schema coverage is 100% with a clear description for the 'id' parameter. The tool description does not add additional meaning beyond the schema, so baseline of 3 is appropriate.

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

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

The description clearly states the tool renders a preview video for upgraded free accounts. It specifies the video must have status 'preview', distinguishing it from sibling tools like create_auto_video or get_video.

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

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

The description provides explicit context: only for free accounts after upgrade, and returns current state if already rendering/complete. However, it does not explicitly state when not to use it compared to siblings, though the conditions imply specific scenarios.

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 fully discloses behavior: it polls until terminal state, uses API-suggested interval, has a ~20-second cap per HTTP request, returns timed_out status on incomplete, and does not block indefinitely or over-poll. This is comprehensive for a polling 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?

Two sentences front-load the purpose and termination conditions, followed by detailed mechanics. Every sentence serves a clear role with no redundancy or fluff. Perfectly concise for the information conveyed.

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 no output schema, the description explains the return value for timed-out cases and implies terminal state returns the full video object. It could detail the non-timed-out return structure, but the primary purpose (waiting) is well-covered. A minor gap, but overall complete for its complexity.

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

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

Schema coverage is 50% (timeout_seconds described in schema, id not). The description does not explicitly explain 'id' but its role is implied by context ('the same id'). It adds value by stating the default timeout (20) and cap (20) for timeout_seconds, reinforcing schema info. Overall, good compensation for partial schema coverage.

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 waits for a video to reach a terminal state (completed/failed/preview) and returns it. The verb 'wait' combined with the resource 'video' and explicit terminal states provide precise purpose, distinguishing it from siblings like get_video that likely return immediate status.

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

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

The description gives explicit guidance: poll safely at API-suggested interval, timeout per call, and 'simply call it again with the same id to keep waiting'. It also clarifies what happens on timeout (returns {timed_out: true}), eliminating ambiguity on retry strategy.

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