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Glama

Update a brand's brand book (brand_md)

update_brand_md
Destructive

Updates a saved brand’s Markdown brand book and optional tone of voice so on-brand generations stay grounded in current brand DNA; resolves by ID, slug, or default.

Instructions

Update a saved brand's brand book Markdown (brandMd) — the brand DNA used to ground on-brand generations — and optionally its tone of voice. Resolves the brand by id, slug, or the default saved brand. Editing brandMd bumps its version.

Input Schema

NameRequiredDescriptionDefault
brandIdNoThe brand id from list_brands.
brandMdYesThe full brand book Markdown to save (replaces the existing brandMd).
brandSlugNoSlug of a saved brand workspace.
toneOfVoiceNoOptional short tone-of-voice description to update alongside brandMd.
useDefaultBrandNoUpdate the most recently ready saved brand when no id/slug is given.

Output Schema

NameRequiredDescriptionDefault
brandYes
profileNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.6.0

TDQS

A3.8/5.0
Behavior3/5

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

Annotations already flag destructiveHint=true and readOnlyHint=false, so the risk profile is known from structured data. The description adds two genuinely useful traits — brand resolution precedence and 'Editing brandMd bumps its version' — but it never warns that the supplied Markdown wholesale overwrites the existing brand book, which is the actual destructive behavior an agent should be told about.

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 dense sentences, front-loaded with the primary action and followed by resolution and side-effect details. No filler, no repetition of the title.

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?

An output schema exists, so return values need no explanation, and the description covers scope, target resolution, and the version-bump side effect. It stops short of the overwrite semantics and any readiness/precondition constraint on the default brand, which would make a mutation tool fully self-describing.

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%, including the crucial 'replaces the existing brandMd' note, so the schema does the heavy lifting. The description only restates the id/slug/default resolution order and the optionality of toneOfVoice, adding little beyond what the schema already documents.

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?

States a specific verb (update) and resource (a saved brand's brandMd Markdown), and explains what brandMd is ('the brand DNA used to ground on-brand generations'), which unambiguously separates it from create_brand, get_brand, and update_skill. The secondary scope (optional tone of voice) is also called out.

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

Usage Guidelines3/5

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

Implies when to use it (you have a saved brand and new brand book content) and how the brand is targeted ('id, slug, or the default saved brand'), but never says when NOT to use it or points to an alternative — e.g. fetch with get_brand first, or use create_brand for a new brand. Guidance is inferred rather than stated.

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