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Brand-System

@brandsystem/mcp

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by Brand-System

Get task-scoped brand context

brand_context
Read-onlyIdempotent

Select a task-scoped brand context for writing in brand voice. Returns governed rules relevant to the specific task type and audience.

Instructions

Select a task-scoped brand context from the compiled runtime. THE tool to call first when the user says 'write this in our voice', 'write this LinkedIn post in our brand voice', 'make an on-brand social graphic', or 'build a landing page' — it returns only the governed rules relevant to that task instead of the full runtime. Deterministic: task_type maps to sections via a fixed table, audience matches governed personas exactly or reports no-match — no inference. Returns data.context (the selected brand slices), matched_selectors (what was chosen and why), and no_governed_match. NOT for reading the entire runtime (use brand_runtime) or checking finished content (use brand_check).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
budgetNo'standard' returns the selected sections in full. 'compact' returns identity colors/typography plus hard rules only (anti-patterns + never_say) — for tight sub-agent contexts.standard
channelNoOptional channel label (e.g. 'LinkedIn'). Recorded in matched_selectors for the agent; does not alter governed rules.
audienceNoOptional audience label (e.g. 'security leaders'). Matched against governed persona names by normalized substring — an explicit no-match is returned rather than guessing.
task_typeYesWhat is being created. Deterministically selects runtime sections: visual tasks (code-ui, image-graphic) get identity+visual; copy tasks (blog-article, email, video-script) get voice+strategy; mixed tasks get both.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
errorNo
contextNo
approvalNo
_metadataYes
matched_selectorsNo
no_governed_matchNo
Behavior5/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false. The description adds deterministic mapping behavior, audience exact matching, and return value structure, going beyond the annotations without contradiction.

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?

The description is concise and well-structured: first sentence states purpose, then usage guidance, then behavior, then return fields, then exclusions. Every sentence adds value with no redundancy.

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

Completeness5/5

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

Given the presence of an output schema (documenting return values), the description covers purpose, usage, behavior, and limitations adequately. The tool is read-only and deterministic, and the description fully captures its role.

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 description coverage is 100%, so baseline is 3. The description does not add substantial parameter meaning beyond what the schema provides; it mentions behavioral context for budget and audience but not new semantic details.

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 selects a task-scoped brand context, provides concrete example user intents ('write this in our voice'), and explicitly distinguishes from sibling tools brand_runtime and brand_check. Purpose is specific and unambiguous.

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

Usage Guidelines5/5

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

The description explicitly says 'THE tool to call first' for specific commands and includes negations like 'NOT for reading the entire runtime (use brand_runtime) or checking finished content (use brand_check).' This gives clear when-to-use and when-not-to-use guidance.

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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