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Regenerate brand guide section

regenerate_brand_guide_section

Regenerates one section of a draft brand guide (identity, voice, audiencePersonas = who it's for, offers, doList, or dontList), optionally steered by feedback. Use this instead of generate_brand_guide when the guide exists but the website scan was thin and you have real detail to add — generate_brand_guide only re-runs off the scan and would reproduce the same result. This rewrites the whole section from the website scan; to change specific lines and keep the rest exactly as written, use update_brand_guide instead.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
brandIdYesThe brand's id, from list_brands.
guideIdYesThe guide's id, from get_brand_guide.
sectionYesWhich section to regenerate. Only this section changes — the rest of the guide is untouched.
feedbackNoSteer the regeneration — e.g. what the brand actually sells, who buys it, a tone correction. Use this when the website scan came back thin and you have real detail to add, instead of generate_brand_guide (which only re-runs off the scan and would produce the same thin result).

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.5/5.0
Behavior4/5

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

Annotations already declare the mutation profile (readOnlyHint=false, idempotentHint=false, destructiveHint=false), and the description adds real behavioral context beyond that: the whole section is rewritten from the website scan and the rest of the guide is untouched, and feedback can steer the output. It does not discuss whether regeneration is costly, requires auth scopes, or is reversible, but with annotations covering the safety profile this is solid.

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?

Front-loads what the tool does before the routing guidance, and the three sentences are dense with decision-relevant content. There is mild redundancy: the 'feedback vs generate_brand_guide' rationale appears both in the description body and repeated in the feedback parameter description.

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?

For a non-idempotent mutation with no output schema, the description covers when to choose it, the overwrite semantics (whole section rewritten, rest untouched), and the steering parameter. It does not describe what the call returns or any cost/time implication, but nothing needed to invoke it correctly is missing.

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%, so the baseline is 3, but the description adds genuine meaning: it clarifies that feedback steers regeneration (with example content such as what the brand sells or a tone correction) and that the rewrite is scoped to the named section. The section enumeration in the description names a subset of the schema enum (missing imagery, capabilities, limitations), a minor inconsistency.

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+resource+scope ('regenerates one section of a draft brand guide') and enumerates the section names, so an agent knows exactly what unit of work this performs. It also explicitly separates itself from generate_brand_guide and update_brand_guide by naming the alternative tools.

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?

Gives explicit routing rules: use this instead of generate_brand_guide when the guide exists but the scan was thin and real detail is available, and use update_brand_guide instead when only specific lines should change. When-to-use, when-not, and the alternative for each condition are all named.

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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