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

With no annotations, the description conveys key behavioral traits: 'local-only' (no external calls), 'complete' (multiple outputs), and the exclusion of API calls. Could be improved by mentioning no side effects or resource constraints, but sufficient for this context.

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

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

Two sentences with front-loaded main action and subsequent listing of deliverables. No fluff; every word adds value. Well-structured for quick comprehension.

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 tool's purpose, inputs, and outputs in a general sense. Lacks specifics on return format or additional behavior (e.g., is storyboard generated as text?). But for a tool with 18 parameters and no output schema, the description provides a solid conceptual 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 coverage is 100%, so baseline 3 is appropriate. The description adds no new per-parameter details beyond the schema. It gives overall context but does not elaborate on any parameter's meaning beyond the schema's already clear descriptions.

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 the tool creates a 'local-only video ad brief' from product details, listing included components (angles, scripts, storyboard, compliance notes, AdsTurbo-ready prompt, follow-up CTA). The phrase 'No AdsTurbo API calls' distinguishes it from the sibling export_adsturbo_prompt tool, which likely makes API calls.

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?

Implied usage: use this tool for local-only brief generation when no AdsTurbo API calls are desired. However, no explicit guidance on when to choose this over siblings like generate_hooks or generate_storyboard. Lacks when-not-to-use and alternative descriptions.

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

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

With no annotations provided, the description only discloses that no AdsTurbo API calls are made, lacking information on other behavioral traits such as resource usage or output characteristics.

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 with two sentences, front-loading the main purpose and including a key behavioral note, with no unnecessary 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?

Given the tool has 18 parameters and no output schema, the description lacks sufficient context about output format or how to use the results, leaving gaps for a complex 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?

All parameters have descriptions in the input schema (100% coverage), and the description adds no additional meaning beyond what is already provided.

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

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

The description clearly states the tool generates testable ad angles with specific components like hooks, CTAs, and risk notes, distinguishing it from sibling tools that may focus on individual aspects.

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 for creating ad variation plans but does not provide explicit guidance on when to use this tool versus alternatives like build_ad_brief or generate_hooks.

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 only states 'Does not call AdsTurbo API'—a helpful behavioral note. However, it fails to disclose other traits like whether the operation is read-only, if it modifies any state, or the output format.

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, zero waste. Front-loaded with purpose, followed by key behavioral caveat. Every word earns its place.

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

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

With 18 parameters, no output schema, and no annotations, a short description is insufficient. It explains the purpose and API call behavior but omits what the returned prompt looks like and how the agent should handle the output. Adequate but leaves 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 baseline is 3. The description adds overall context but no additional semantics per parameter beyond what the schema already provides. No new insights on parameter usage or relationships.

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?

Clear verb 'export', resource 'video generation prompt', and context 'pasted into AdsTurbo for the full website generation experience'. Distinguished from siblings by specifying it's for exporting rather than generating creative content.

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 guidance on when to use this tool vs alternatives like build_ad_brief or write_ugc_script. The description implies use for AdsTurbo integration but lacks when-not-to-use or sibling differentiation.

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

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

With no annotations provided, the description must carry the full burden. It discloses one behavioral trait: the tool does not make AdsTurbo API calls. However, it lacks details on other behaviors such as whether it is generative AI, output format, or any side effects. Score 3 for partial disclosure.

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

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

The description is a single efficient sentence that front-loads the purpose and key differentiator. No extraneous information, earning a top score.

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?

Despite 19 parameters and no output schema or annotations, the description is extremely brief. It does not explain the generation process, output format, or how parameters interact. For a complex tool, this is inadequate, scoring 2.

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

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

Schema description coverage is 100%, so the baseline is 3. The description adds no additional meaning beyond what the schema provides; it only reiterates platform options. Thus score 3.

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 action ('generate'), the output ('short-form ad hooks'), and the target platforms (TikTok, Reels, Shorts, Meta, YouTube). It also adds a behavioral note ('No AdsTurbo API calls'). This distinguishes it from sibling tools like build_ad_brief or write_ugc_script.

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 when to use this tool (for ad hook generation) and includes a limitation ('No AdsTurbo API calls'). However, it does not explicitly state when not to use it or provide direct alternatives, though sibling context hints at other tools for different ad tasks.

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; the description only notes 'No AdsTurbo API calls.' It does not disclose side effects, resource creation, or state changes, leaving the agent with limited 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?

Two sentences with no wasted words, but could be structured more clearly (e.g., bullet points or explicit sections). Still efficient.

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 18 parameters and no output schema, the description is too brief. It lacks details on output structure, return format, or usage context, making it incomplete for a complex tool.

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

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

Schema coverage is 100%, so parameters are documented. The description adds marginal value by listing output components (platform, aspect ratio, etc.), but does not enhance parameter understanding 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 it generates a short-form video ad storyboard and lists key components (platform, aspect ratio, etc.). However, it does not differentiate from sibling tools like build_ad_brief or write_ugc_script.

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 use this tool versus alternatives. The description lacks context about prerequisites or appropriate 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 must carry the full burden. It lists what aspects are reviewed but does not disclose behavioral traits such as whether it modifies anything, requires authentication, rate limits, or whether it is read-only. The tool appears non-destructive but this is not stated.

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, efficient and front-loaded with specific criteria. It could be slightly more structured (e.g., bullet points) but is concise and clear.

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, the description does not explain the format or structure of the review results (e.g., a report, scores, or notes). Given the tool's complexity (multiple criteria), this omission hinders an agent's ability to parse the response.

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%, with all three parameters described in the input schema. The description adds no additional parameter semantics 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 reviews a script against specific criteria like hook, problem, demo, proof, CTA, etc. It distinguishes from sibling tools that are generative (e.g., generate_hooks, write_ugc_script) but does not explicitly differentiate from other review-like 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?

The description implies usage after a script is written, but no explicit when-to-use, when-not-to-use, or alternative tools are mentioned. Sibling tools like generate_hooks suggest when to use alternatives, but the description lacks guidance.

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

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

With no annotations, the description must disclose behavioral traits. It states it writes scripts and does not call AdsTurbo API, but fails to mention other important aspects such as generation approach, latency, cost, or whether it mutates state. The description adds little beyond the name and schema.

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 long, contains zero filler, and conveys the core purpose and a key constraint. Every sentence earns its place.

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

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

Given the tool has 18 parameters and no output schema, the description is too sparse. It does not explain the return format, pagination, or how the script content is structured beyond listing components. For a complex generation tool, this is insufficient preparation 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 input schema covers 100% of parameters with descriptions, so the baseline is 3. The tool description mentions the output structure (hook, problem, etc.) but does not add meaning or context to any specific parameter beyond what the schema provides.

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

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

The description clearly states that the tool writes three UGC-style ad scripts with specific components (hook, problem, demo, proof, CTA, on-screen text, shot notes). It identifies the resource and action, but does not explicitly differentiate from sibling tools like generate_hooks or build_ad_brief, which produce related but distinct outputs.

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 'No AdsTurbo API calls' which is a constraint, but provides no guidance on when to use this tool versus alternatives like build_ad_brief or generate_storyboard. There is no mention of prerequisites, typical use cases, or when not to use it.

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