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Brand-System

@brandsystem/mcp

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brand_enrich_skill

Augment auto-generated SKILL.md with brand governance from .brand/ YAML files — additive only, no rewrites.

Instructions

Take a Claude Design-style auto-generated SKILL.md, diff it against this project's .brand/governance/ YAML (narrative-library, valid-proof-points, anti-patterns, application-rules, taste-codes), and return an enriched SKILL.md with missing governance content injected, cited by governance ID, and grouped into canonical sections. Additive only — never rewrites existing content. Requires a .brand/ directory with at least one governance file. The typical flow: Claude Design auto-generates a SKILL.md during onboarding → pass it to this tool → replace the original with the enriched version → every subsequent generation grounds on governed narratives, Active/Watch proof points, hard-rule anti-patterns, and taste signals. This is the low-friction wedge for putting Brandcode governance into any Anthropic-product generation surface.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
skill_mdYesThe auto-generated SKILL.md content to enrich. Paste the full file (including frontmatter) as a single string. Maximum 128 KB.
max_per_sectionNoCap injected bullets per governance section. Default 12, max 24. Raise for dense libraries; lower for minimal enrichment.
include_application_rulesNoInclude the Application rules section summarizing content-type → framework routing. Default: true.
Behavior4/5

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

No annotations provided, so description carries full burden. It clearly states the tool is additive only, never rewrites existing content, and cites governance IDs. Discloses the enrichment process without contradicting any missing annotations.

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

Conciseness5/5

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

Two sentences plus a flow paragraph; all information is front-loaded. Every sentence adds value, no redundancy.

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 complexity (transformation with multiple governance files), the description covers purpose, prerequisites, flow, and parameters. No output schema, but return type is described. Minor missing details about diffing logic, but sufficient for tool selection.

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

Parameters3/5

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

Schema coverage is 100% with descriptions for all three parameters. The description adds usage context (e.g., max_per_section cap, default true) but does not significantly extend beyond the schema's own parameter 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 verb ('take... diff... return... enrich') and specific resource (SKILL.md), with enough detail to distinguish from siblings that audit or check compliance.

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?

Explicitly describes the typical flow ('Claude Design auto-generates... pass it to this tool... replace') and prerequisite (.brand/ directory with governance file). No explicit when-not or alternative tools, but the context is clear.

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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