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

With no annotations, the description carries the behavioral burden. It discloses supported formats (.mp4, .webm) and names the analysis outputs, which is useful. However, it does not mention whether the tool fetches remote URLs, handles large videos, or is read-only, and no error or limitation behavior is described.

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, dense sentence with no filler. The core purpose and output types are front-loaded, making it easy to scan and understand quickly.

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 clearly lists expected outputs and supports formats, but it does not explain that at least one of video_url or video_path must be supplied, despite both parameters being formally optional. With no output schema and no annotations, this missing invocation constraint leaves the description slightly incomplete.

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 schema already documents all three parameters well. The description adds some conceptual context by mapping outputs to analysis areas, but it does not provide additional parameter-level meaning beyond what the schema already states.

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 names a specific verb ('Analisa') and resource ('vídeo de referência'), and enumerates concrete extraction outputs: movement choreography, spring physics, bezier curves, and transition timing. This makes the tool's purpose unmistakable and easily distinguishable from its unrelated siblings.

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 clearly implies the tool is for video reference analysis and lists the supported formats, but it does not explicitly state when to prefer this tool over alternatives or when not to use it. Since all sibling tools are clearly unrelated, the usage context is still evident.

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 burden of behavioral disclosure. It does not mention any side effects, prerequisites, limitations, or whether the operation is read-only or destructive. For a generation tool, it fails to clarify what happens with invalid inputs or what the output format is, leaving significant behavioral 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?

The description is a single sentence that is front-loaded with the role ('ATUA COMO ARQUITETO E DIRETOR DE ARTE') and immediately states the purpose and deliverables. It is concise and efficiently packs information, though it could be broken into two sentences for readability. No redundant content.

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 lists the components of the generated plan, which is useful, but it does not describe the return format or any constraints on inputs (e.g., whether style_preference is optional). Given the tool's complexity and the lack of an output schema, more context about what the agent should expect as output would improve completeness, but it is adequate for a basic understanding.

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 provides clear descriptions for all three parameters, covering 100% of them. The description mentions 'nicho ou objetivo' which aligns with the niche and goal parameters, but adds no additional meaning beyond what the schema already states. Since schema coverage is high, the 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 states a specific verb ('gera') and a clear resource ('plano arquitetural completo'), and lists the specific components it produces (storytelling, template selection, design system, stack, multi-agent roles). This makes the tool's purpose unmistakable and distinct from siblings like get_template or list_design_systems, which are retrieval tools for individual items.

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 it is for generating a whole plan rather than retrieving specific templates or design systems, but it does not explicitly state when to use this tool versus the sibling tools, nor does it mention any exclusions or alternative conditions. The guidance is implied rather than explicit.

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 present, so the description carries the full disclosure burden. It only says the tool 'returns' various animation types, signaling a read operation, but it does not disclose the output format, whether the result is a code snippet string or object, or any side effects or prerequisites.

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 compact sentence with no filler and is easy to scan. It front-loads the returned artifact types, though it could be slightly more structured by explicitly naming the output as an animation snippet.

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: one required parameter, no nested objects, and the schema fully documents that parameter. However, with no output schema and no annotations, the description should more clearly state what form the returned animation snippet takes; the current list only hints at it. It is minimally adequate for selecting and invoking the 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 description coverage is 100% and the schema already enumerates all preset IDs, so the baseline is 3. The description paraphrases those presets in human-friendly terms, which adds some selection context, but it provides no syntactic or behavioral detail beyond what the schema already offers.

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 states a concrete verb ('Retorna' – returns) and enumerates the artifact types it provides: spring physics, mouse-following spotlight, 3D tilt, particle canvas, and Lenis scroll. This is enough to distinguish it from sibling tools that deal with vaults, templates, prompts, and design systems, though it never explicitly names the resource as an 'animation snippet' or 'preset'.

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 when-to-use guidance, exclusions, or alternative tool routing is provided. The purpose must be inferred entirely from the content list and tool name, with no direct statement about when an agent should choose this tool over its 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?

With no annotations, the description carries the full burden of behavioral disclosure. The verb 'returns' implies a read-only operation, but it doesn't explicitly state that it's non-destructive or require any permissions. It also doesn't mention any rate limits, pagination, or error behavior. For a simple get tool, this is adequate but not thorough.

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

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

The description is a single, efficient sentence in Portuguese that immediately states what the tool returns. There is no fluff or redundancy—every word contributes to the purpose.

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 tool with one parameter fully documented in the schema, the description provides a clear high-level overview of the return value (tokens, fonts, Tailwind config). It lacks explicit notes on output structure or prerequisites, but given the tool's simplicity and lack of output schema, it covers the essential information an agent needs to call it correctly.

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 description covers 100% of the parameter (system_id) by listing all valid values. The tool description adds no additional meaning beyond what the schema provides—it doesn't explain the concept of a system ID or how to choose one. Since the schema is complete, a baseline score 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 states a clear verb ('returns') and specific resources (HEX tokens, Google Fonts typography, Tailwind configurations) for a particular visual aesthetic. It does not explicitly distinguish itself from sibling tools like list_design_systems, but the specificity of what it returns makes its purpose evident.

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 doesn't mention that list_design_systems should be used to discover available systems or that this tool is for retrieving details of a specific system. The agent must infer usage from the 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.

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

No annotations are provided, so the description carries the full burden. It discloses the output type (source code) but does not mention error behavior, permissions, rate limits, or side effects. For a simple get operation this is minimal and leaves important behavioral details unstated.

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, efficient sentence that front-loads the action and contains no unnecessary words. It is concise and communicates the core purpose without filler.

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 (one parameter, no output schema), and the description adequately notes the return type. However, it omits possible failure modes, prerequisites, or how the source is returned, leaving some gaps for an agent to infer.

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 already provides 100% description coverage for the only parameter (template_id), including example values, so the baseline is 3. The tool description adds no parameter-specific meaning beyond what the schema supplies.

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 states a specific action ('Carrega' / loads) and a clear resource ('código-fonte React 19 completo... de um componente visual'), which identifies the tool as returning source code for a template. It implicitly differentiates from list_templates by focusing on source retrieval, but 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 tool name and description imply usage for fetching a specific template's source code, but there is no explicit guidance on when to use this tool versus siblings like list_templates or search_vault. No exclusions or alternative conditions are given, leaving usage to inference.

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 of behavioral disclosure. It does state that the tool returns content and specifies the output language/format (English prompt plus translated description), which is useful. However, it does not mention side effects, error behavior, or how lookup by 'exact title' behaves, though as a simple get operation the risk is low.

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 that front-loads the action and object, with no filler or repeated information. It is appropriately concise for the tool's simple scope.

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 one-parameter lookup tool, the essential information is present and the schema covers the parameter. However, with no annotations and no output schema, the description could be more complete by explaining the response format, possible errors, and how this tool differs from get_template or search_vault. The slight ambiguity between 'modelos' and 'prompts' also leaves room for confusion.

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 already fully documents the single parameter: 'ID do prompt (1 a 328) ou título exato do modelo' with 100% coverage. The description adds the collection size of 328 but does not provide meaningful semantic detail beyond what the schema already states.

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 ('Retorna') and clearly identifies the resource: the official full prompt in English and the translated description from one of 328 models. It also states the purpose ('para orientar a geração de código'), making the tool's function clear, though it does not explicitly differentiate it from sibling tools like get_template.

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 instead of alternatives such as search_vault, list_templates, or get_template. The phrase 'para orientar a geração de código' implies a purpose, but there are no explicit conditions, exclusions, or references to sibling tools.

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 of behavioral disclosure, and it delivers: it reveals non-obvious behaviors like suppressing cookies/modals, scrolling to trigger animations, and producing Retina 2x screenshots. It does not mention network side effects, auth requirements, or failure modes, but the described behavior goes well beyond the tool's name.

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 states the core purpose in caps and then lists each capability in a logical sequence with no filler. Every phrase earns its place: cookie suppression, smooth scroll, Retina 2x, and token extraction.

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 should clarify what the agent receives back. It mentions extracting design tokens, which implies a return value, but it does not state whether screenshots are saved to destination_dir, what the token format is, or what the overall response structure looks like. This is a meaningful gap for a tool that produces multiple artifacts.

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 100% coverage for both parameters (url and destination_dir), so the schema already carries the parameter documentation. The description adds no parameter-specific detail beyond the schema, so the baseline score 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 opens with a specific verb+resource pair — 'INSPEÇÃO FORENSE HD DE QUALQUER URL' — and then enumerates concrete actions: suppressing cookies/modals, smooth scrolling to load animations, taking Retina 2x screenshots, and extracting real design tokens. This clearly distinguishes it from sibling tools like search_vault, list_templates, or get_design_system, which are repository/blueprint oriented rather than URL-inspection oriented.

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 makes the intended use-case explicit: use it when you need a forensic, high-definition inspection of any URL with clean screenshots and real design tokens. It does not explicitly name alternatives or when-not conditions, but none of the sibling tools perform URL inspection, so the context is clear enough without exclusions.

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 burden of behavioral disclosure. It states that the tool lists design systems with calculated HEX palettes, but does not disclose the return format, whether results are paginated or sorted, or whether this is a read-only operation. For a simple listing operation this is a moderate gap, but with zero annotation coverage the description should do more.

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, efficient sentence that packs genuine value: it names the exact design systems available and the HEX palette feature. The enumeration of seven design systems is useful content, not filler. No wasted words, though it is a bit long-winded with the parenthetical list.

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 0-parameter listing tool with no output schema, the description covers the essential 'what' — the design systems and their HEX palette feature. It does not describe the output shape or whether the list is exhaustive. Given the simplicity of the tool, this is adequate but could add a note about output format to fully close the 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?

The tool has 0 parameters, so the baseline is 4. There is nothing the description needs to explain about parameters since the schema is empty and fully covered. The description adds the meaningful semantic detail of what the output contains (the specific design systems), which is valuable given no params exist.

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 (Lista) and resource (Design Systems de elite) with HEX palettes, and enumerates the exact design systems available. It clearly distinguishes the list operation from the sibling get_design_system by implication, though it doesn't explicitly name the alternative. The action and scope are 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 use this vs the sibling get_design_system. The list-vs-get distinction is implied by naming, but there is no explicit statement of when to choose one over the other, nor any prerequisites or context for selecting this tool. An agent must infer the usage pattern.

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 burden of behavioral disclosure. It only states that it lists available components, without mentioning return format, pagination, whether it returns metadata or full code, or any side effects. Minimal disclosure beyond the core action.

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 sentence that front-loads the action and scope, then provides a parenthetical enumeration of examples. Every word earns its place; no filler or 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?

The tool is simple (one optional param, no annotations, no output schema). The description adequately states purpose and gives examples, but it does not describe the return structure, ordering, or any filtering nuance beyond the schema's category list. For a listing tool this is a modest gap, but a complete agent might need more detail about the output.

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% for the 'category' parameter, so baseline is 3. The description adds value by enumerating concrete component types (Navbars, Heroes, Tabs, etc.) that implicitly map to category values, giving an agent a better understanding of what each category likely includes.

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 ('Lista') and resource ('componentes de código React 19 + Tailwind + Framer Motion/GSAP'), and enumerates example component types (Navbars, Heroes, Bentos, etc.). It clearly distinguishes this from sibling tools like get_template (fetch one) and list_design_systems (design systems).

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 verb 'Lista' implies its usage (when you want to list all components), and the schema documents the optional category filter. However, the description gives no explicit guidance on when to use this over alternatives like search_vault, nor does it state when not to use it. Usage is only implied.

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 burden. It states the scope (328 official prompts, Free+Premium) and the search dimensions, but does not disclose non-obvious behaviors like whether it modifies anything, rate limits, ordering, or pagination. As a search tool, it is presumably read-only, but this is not explicit.

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 sentence that front-loads the action and scope. It is efficient with no redundant wording, making it easy for an agent to parse quickly.

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 search tool with optional parameters and no output schema, the description provides enough context: what it searches, the collection size, and example categories. It does not explicitly describe the return format, but this is largely inferable. The absence of a required parameter and the presence of a limit param are covered by the schema, so the description is sufficiently complete for an agent to invoke it correctly.

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 schema already documents all four parameters (type, limit, query, category). The description adds examples of search terms but does not provide additional semantics beyond what the schema states. Baseline of 3 is appropriate given high 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 it searches a specific collection (328 official MotionSites prompts) by niche, effect, or technique, with concrete examples. It is unambiguous and distinguishes itself from siblings like get_vault_prompt (retrieves a single prompt) and list_templates (lists templates) by focusing on search/filter capability.

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 finding prompts via keywords, but does not explicitly state when to prefer this over alternatives such as get_vault_prompt or list_templates. It lacks direct guidance on when not to use it or what distinguishes it from sibling search-like tools.

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