distribea-mcp

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

With no annotations provided, the description carries full burden. It discloses the generation behavior (never generic photo, consistent with site style), the return format (CDN URL + img tag), and the ability to add illustrations. It does not mention auth or error cases but adequately describes core 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?

The description is concise with three sentences, each serving a purpose: first states main function, second adds return info and input methods, third explains the illustrations parameter. 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?

Given 8 parameters, no output schema, and no annotations, the description covers main behavior, parameter usage, and constraints. It does not cover edge cases like conflicting inputs or error handling, but it is sufficiently complete for typical use.

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 value by explaining how article_text and article_url are alternative inputs, and that illustrations adds N images inside the article. It also clarifies that title overrides the read title and product/character lock specific features.

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 a 16:9 cover for editorial articles from a specific topic, not a generic photo, and adds illustrations. This distinguishes it from sibling tools like generate_image or edit_image, which are more generic.

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 specifies that the article can be provided via article_text or article_url, and that illustrations:N adds images. While it gives clear context on how to use the tool, it does not explicitly state when not to use it or compare it with alternatives like generate_image.

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?

Despite no annotations, the description discloses that the tool returns outputs (logo as img, favicon files as base64 plus head tags, og:image meta tags) and that it can derive favicons from a given logo. It does not mention destructiveness or permissions, but the tool appears safe and idempotent. The description adds useful behavioral context beyond the 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 a single paragraph that efficiently conveys the core functionality, action options, and return values. It front-loads the purpose and then lists details. While it could benefit from bullet points for clarity, it is still well-structured and concise.

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 and no annotations, the description covers all necessary aspects: what each action produces, the return format (img, base64 files, head/meta tags), and optional parameter usage. It mentions specific file names (favicon.ico, apple-touch-icon, etc.) and conditions like deriving favicons from a logo. This completeness supports correct agent usage.

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 is 3. The description adds context: explains that 'title' is required for social_image, 'tagline' for logo, 'subtitle' for social_image, and 'image_url'/'image_base64' for favicons. It clarifies the role of 'project' as a site identifier and the default action. This additional meaning merits a 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 clearly states the tool's purpose: generating a brand finishing pack including logo, favicon pack, and social image. It distinguishes each component and specifies that action 'all' chains them, while individual pieces can be requested. This specificity differentiates it from sibling tools like blog_cover or site_style.

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 the default action and how to request single pieces, with examples like 'logo', 'favicons', 'social_image'. It also mentions optional derivation from an existing logo. However, it does not explicitly state when to prefer this tool over alternatives or when not to use it, so it gets a 4.

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 describes the default behavior (replace existing images unless user asks to keep) and workflow. It clarifies that it only proposes and returns data, not generates images. It could mention if any state changes occur, but overall it is 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?

The description is detailed but every sentence is necessary. It is front-loaded with the core purpose, and the structure flows logically from purpose to workflow to 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?

Given no output schema, the description adequately explains what the tool returns: proposed spots with anchors and a list of existing img tags. The workflow is fully described, making the tool's role clear in the broader process.

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 coverage is 100% with clear descriptions for both parameters. The description adds context, such as how to use page_text ('pass the page's current code') and the default for project. This adds meaning 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's purpose: making an existing page feel alive by proposing new image spots and returning existing img tags for replacement. It distinguishes itself from sibling tools like generate_image by stating it should be used before that tool.

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 says when to use this tool: 'Use this BEFORE generate_image whenever a page's imagery is missing or off-brand.' It also provides a detailed workflow. However, it doesn't explicitly state when not to use it, but the positive guidance is strong.

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 the free cost, preferred image input method (base64), and the effect of registering a reference for later use. It does not mention rate limits or idempotency, but covers key behaviors for a mutation 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 a single dense paragraph. It packs all information but could be better structured with bullet points or clearer separation of core usage, parameter roles, and follow-up steps. Adequate but not optimally concise.

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 7 parameters (mostly optional), 100% schema coverage, no output schema, and no sibling overlap, the description sufficiently covers purpose, parameter semantics, and workflow context. It explains the crucial follow-up step, making the tool's role clear for an agent.

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%, but the description adds significant value beyond schema definitions: it explains the semantic purpose of each kind, the workflow linkage to generate_image, and the bulk registration capability via items. This enrichment justifies a score above baseline.

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 registers a real photo for identical reuse in generated images. It distinguishes three kinds (character, product, place) and explains each, making it distinct from sibling tools like generate_image or blog_cover.

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?

It provides explicit when-to-use guidance, including the follow-up call to generate_image with the registered name. It also notes free credits and bulk registration via items, but lacks explicit when-not-to-use 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?

Discloses billing, return format (CDN URL + img tag), and per-action behavior. However, lacks details on error handling, rate limits, or whether the original image is preserved.

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 well-organized paragraph front-loads purpose, then details each action. No redundant sentences.

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 all parameters and return values. Missing error cases or validation details, but adequate for a tool with comprehensive schema.

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 context beyond schema (e.g., default action 'edit', examples of plain-language instructions, apply_style specifics). Schema coverage is 100%, so description enhances understanding.

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 retouches existing images with specific actions (edit, redo, remove_background, upscale, extend). It distinguishes from sibling tools like generate_image by focusing on editing rather than creation.

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 describes when to use each action (e.g., 'remove_background' for transparent cutout, 'upscale' for ×4) and warns that it's billed and only for explicit user requests.

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?

Describes what is wiped (memory) and what is not (page), and that it's free. No annotations provided, so description handles behavioral disclosure well, though could note irreversibility.

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 clear front-loading and no wasted words. Every sentence adds value: action, scope, 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?

Given low complexity (1 param, no output schema), description fully covers purpose, usage, parameter meaning, and behavioral impact. No missing information.

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?

Only one parameter 'project' with description including default value 'lovable'. Schema coverage is 100%, but description adds context beyond schema's basic 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?

Title says 'Forget a project's memory (start fresh)' and description specifies wiping saved memory (locked style, characters, products) while leaving page untouched. Distinguishes from siblings like site_style or list_projects.

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 states 'Use when a reused project carries over unwanted style or products' and notes it's free. Does not list when not to use or mention alternatives, 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 provided, the description must fully disclose behavior. It reveals that the tool generates one image, returns specific outputs, and auto-switches for certain subjects. However, it does not mention side effects (e.g., storage, idempotency), rate limits, or potential variation in style consistency, leaving moderate transparency 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 two sentences, front-loading the core purpose and output, then adding key behavioral nuance. Every sentence is informative with no waste.

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 complexity (7 params, no output schema), the description covers main behavior and parameter nuances. It does not detail error handling or style inheritance, but it is sufficient for an agent to understand the primary functionality and constraints.

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 all 7 parameters (100% coverage), but the description adds meaning beyond the schema by explaining automatic behavior (review subjects trigger selfie), the 'none' option for character to force no face, and cross_site_unique behavior for avatars.

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 ONE image consistent with the site's style and returns a CDN URL and ready-to-paste img tag. It also mentions automatic switching for review/testimonial/avatar subjects, distinguishing it from sibling tools like blog_cover or edit_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?

The description includes 'Ideal for heroes, about, sections, cards…' which gives usage context. However, it lacks explicit when-not-to-use guidance or direct comparisons to sibling tools, though the behavioral details (auto-switch for review subjects) implicitly guide proper use.

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 pricing (billed at regular site price) and output format (CDN URLs and img tags). Without annotations, it carries the burden well, though it could mention authentication or rate limits. Still, it provides useful behavioral 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?

Three succinct sentences covering purpose, usage guidance, and auxiliary info (list_models, returns). Every sentence earns its place; no fluff.

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 6 parameters and no output schema, the description adequately covers core behavior, when to use, and returns. Could mention handling of multiple images or error scenarios, but directs to list_models for options, so 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 100%, so baseline is 3. Description adds minimal extra meaning beyond schema, merely echoing 'quality/format/number of images' and recommending list_models for valid ids. No significant additional semantic value.

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 the tool generates an image with a specific model and settings, and distinguishes it from the sibling tool generate_image by labeling it as advanced/manual mode with explicit control over quality, format, and count.

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 tells when to use this tool (user names a model or wants quality/format/count control) and when to use the alternative generate_image (auto robot), plus advises to get valid IDs from list_models.

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, but the description transparently describes the tool as a read operation that returns catalog data. It does not mention side effects or auth, which is acceptable for a simple list.

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 concise sentences with no wasted words. The first sentence lists return content, the second provides usage guidance. Key info is 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 zero parameters and no output schema, the description fully covers the tool's purpose, return content, and when to use it. It even notes 'Image only for now' for future-proofing.

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 are no parameters, so the description need not add parameter info. It adds value by detailing the return fields, which compensates for the absence of an output 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 returns the catalog of image models with specific fields (id, name, best uses, etc.) and explicitly instructs to call it BEFORE generate_with_model, distinguishing it from sibling 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 provides explicit usage context: call this before generate_with_model when picking a model. It lacks exclusions or alternatives but is clear enough for the intended use.

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 should disclose behavioral traits. It fails to mention if the operation is read-only, safe, or requires authentication. The word 'Free.' is ambiguous. Listing what fields are returned is helpful but insufficient.

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, mostly concise. The inclusion of 'Free.' is unnecessary and slightly distracts. The structure could be improved by separating parameter instructions.

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?

No output schema exists, but the description only lists fields without explaining return structure, pagination, or error conditions. The parameter ambiguity and lack of comparison with sibling tools make it incomplete for an agent to use 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 coverage is 100%, but the description's interpretation of the parameter ('reuse its name') conflicts with the schema description ('current site identifier'). This adds confusion rather than clarity, reducing the value 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 verb 'List' and the resource 'projects' with details like name, brand, image count, and products. However, the mention of 'Free.' is irrelevant and the parameter description in schema contradicts the tool description (project name vs current site identifier), slightly reducing clarity.

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 limited guidance: it tells to reuse the project name in the parameter to continue working. However, it does not compare with siblings like forget_project or specify when to use this tool versus others.

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 but only says 'Shows' implying read-only. No disclosure of authentication requirements, rate limits, or other behavioral traits.

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?

Description is one sentence plus 'Free.' which is unnecessary. Could be more concise without the extraneous note.

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 status tool with one optional param and no output schema, the description adequately lists the key data displayed. Missing details about return format but acceptable given simplicity.

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 well-documented optional parameter. The description adds no additional meaning 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 shows multiple specific pieces of information (credit balance, locked style, known characters/products/avatars, latest generated images), making the purpose 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 tool vs siblings (e.g., site_style). No when-not or alternative suggestions, leaving the agent to infer usage.

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 the two main actions and their effects: 'setup' locks the style from a brief/URL, and 'refine' records a rule to be honored by subsequent images. It does not address whether repeated calls overwrite, potential destructive effects, or any rate limits. Given no annotations, the description partially shoulders the transparency burden.

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: two sentences, each dedicated to one main action. It front-loads the core concept ('The site's art direction') and provides clear, actionable details. It could be more organized (e.g., bullet points), but it is efficient and free of 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 nine parameters and no output schema, the description covers the primary actions and key parameters (brief, site_url, feedback) but does not explain the roles of 'force', 'project', 'moodboard', 'image_url', or 'image_base64'. The schema documents them, but the description alone leaves gaps for an agent to infer complete usage 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?

With 100% schema coverage, the baseline is 3. The description adds value by explaining the purpose of 'action', 'brief', 'site_url' (for setup), and 'feedback' (for refine) in a narrative that goes beyond the schema's parameter descriptions. It omits specifics for 'force', 'project', 'moodboard', 'image_url', and 'image_base64', but the overall context aids understanding.

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 manages the site's art direction, with specific actions 'setup' and 'refine' that lock or adjust the style. It distinguishes itself by focusing on site-wide visual branding rather than individual image generation, making its purpose concrete and distinct from 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 advises to 'run this FIRST for consistent images' for the 'setup' action, providing clear sequencing guidance. It also explains the 'refine' action's role for adjustments. However, it does not explicitly exclude when not to use this tool versus alternatives like 'brand_pack' or 'generate_image', limiting full discrimination.

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