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generate_background

Generate production-ready CSS background patterns matched to your industry and selected theme, with pattern types like geometric, gradient, noise, organic, or blob for subtle atmospheric effects.

Instructions

Phase 4 — Generate a CSS background pattern that matches your industry and theme.

Returns: production-ready CSS for subtle, professional background patterns.

Pattern types: "geometric" (dot grids, line grids — tech/corporate), "gradient" (soft mesh gradients — startups/creative), "noise" (grain texture — luxury/editorial), "organic" (wave dividers — health/education), "blob" (animated shapes — creative/SaaS).

Pattern is auto-selected based on industry. All patterns are barely noticeable — atmosphere, not distraction.

IMPORTANT: Run design_theme first so colors match your palette.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
styleNoPattern style override. Options: "geometric", "gradient", "noise", "organic", "blob", "dots", "grid", "mesh", "wave", "grain"
themeYesTheme mode
industryYesBusiness industry for pattern selection
Behavior3/5

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 that patterns are 'barely noticeable' and auto-selected based on industry, and lists pattern types. However, it doesn't detail response format (e.g., whether it returns a CSS string or file), potential errors, or performance implications. 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.

Conciseness4/5

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

The description is front-loaded with the tool's purpose, followed by return value, pattern types, and important note. It is concise without unnecessary verbosity. The 'Phase 4' label might be slightly redundant but doesn't detract significantly.

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

Completeness4/5

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

Given the input schema covers all parameters and there is no output schema, the description adequately explains the tool's function, auto-selection logic, and prerequisite. It could be more complete by describing edge cases (e.g., invalid industry) but is sufficient for most use cases.

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

Parameters4/5

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 meaning by explaining how pattern types correspond to industries (e.g., 'geometric' for tech/corporate) and that style is an override on auto-selection. This contextualizes the parameters beyond the schema's brief descriptions.

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

Purpose5/5

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

The description clearly states it generates a CSS background pattern matching industry and theme, specifying it's production-ready CSS for subtle patterns. It distinguishes from siblings by mentioning 'Phase 4' and the prerequisite of design_theme, making its role in the sequence explicit.

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

Usage Guidelines4/5

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

The description provides clear usage context: it's Phase 4 and requires design_theme to be run first so colors match. It lists pattern types and their associations, guiding when each might be appropriate. However, it doesn't explicitly state when not to use this tool or mention alternatives beyond the prerequisite.

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

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