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brand_export

Generate portable brand files for AI chats, code configs, team guidelines, email summaries, or PDF guides. Choose target format and optionally embed the logo.

Instructions

Generate portable brand files for any environment — Chat, Code, team sharing, or email. Target 'chat': self-contained markdown to upload to any AI conversation (Claude, ChatGPT, Gemini). Target 'code': MCP config + CLAUDE.md/.cursorrules snippet. Target 'team': clean brand guidelines for designers and writers. Target 'email': concise 500-word summary for Slack or email. Writes to .brand/exports/ and returns the full content. Use when the user wants to share their brand system or set up a new tool.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
targetYesWhere this export will be used. 'chat': upload to AI conversation (Claude/ChatGPT/Gemini). 'code': paste into CLAUDE.md or .cursorrules. 'team': share with designers/writers. 'email': send via Slack or email. 'claude-skill': persistent Claude skill file with embedded logo + brand rules. 'pdf': brand guide PDF with color swatches, typography, visual rules, and voice summary — no browser needed.
include_logoNoEmbed logo SVG/data URI in the export. Set false to reduce file size. Default: true.
Behavior2/5

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

The description mentions writing to .brand/exports/ and returning full content, but lacks details on side effects (e.g., whether files are overwritten), authorization needs, or idempotency. With no annotations, the description carries the full burden and is insufficient for a file-writing tool.

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 well-structured with a clear first sentence summarizing the purpose, followed by concise per-target explanations and a usage note. It is moderately concise and front-loaded, though some repetition could be trimmed.

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 2 parameters and no output schema, the description covers key aspects: target variations, file location, and usage context. It does not detail the return content structure, but overall it 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 coverage is 100%, providing baseline 3. The description adds meaningful context beyond the schema, especially for the 'target' enum, describing each output format's use case. This enhances understanding 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 the tool's purpose: generating portable brand files for various environments (chat, code, team, email, etc.). It distinguishes from sibling tools like brand_audit or brand_init by focusing on export and sharing.

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 explicitly says 'Use when the user wants to share their brand system or set up a new tool', providing clear context. It does not list when not to use or alternatives, but the context is sufficient for appropriate selection among siblings.

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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