PostNitro

Update Brand

postnitro_update_brand

DestructiveIdempotent

Update an existing brand kit. All seven fields are required by the API.

name, handle, and image are only overwritten when a non-empty value is sent; the boolean display flags (isCompanyDetail, showName, showHandle, showImage) are always applied.

Tip: call postnitro_get_brand first to read current values, then send them back with your changes.

Input Schema

TableJSON Schema

Name	Required	Description
`name`	Yes	Brand display name (required)
`image`	Yes	Logo image URL (required)
`handle`	Yes	Social handle, e.g. '@postnitroai' (required)
`brandId`	Yes	The brand ID to update (get from postnitro_list_brands)
`showName`	Yes	Render the name on slides
`showImage`	Yes	Render the logo on slides
`showHandle`	Yes	Render the handle on slides
`isCompanyDetail`	Yes	Treat as a company brand (vs personal)

Output Schema

TableJSON Schema

Name	Required	Description
`brand`	Yes	The brand after the update
`message`	Yes	Confirmation message
`success`	Yes

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

First observedSep 7, 2026

TDQS

A4.8/5.0

Behavior5/5

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

The description discloses important behavioral details beyond annotations: name, handle, and image are only overwritten with non-empty values, while boolean display flags are always applied. This informs the agent of side effects and required care when updating.

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, front-loaded with the main purpose, and each sentence adds value. The tip is short and actionable, with no unnecessary fluff.

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?

The description is largely complete for an update operation, including behavior and a practical tip. It falls short slightly because of the incorrect field count, which could mislead an agent into omitting a required parameter. Otherwise, it adequately explains the update semantics and prerequisites.

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?

The schema already covers all parameters with descriptions, so baseline is 3. The description adds valuable semantic context about conditional overwriting of name/handle/image and unconditional application of booleans. However, the statement 'All seven fields are required' is inaccurate—there are eight required parameters—which slightly undermines clarity about required fields.

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 updates an existing brand kit, distinguishing it from create or list operations. The verb 'update' and the resource 'brand kit' are 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 provides explicit usage guidance by advising to call postnitro_get_brand first to read current values and send them back. This directly tells the agent when and how to use the tool correctly, especially given the conditional overwrite behavior.

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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TDQS

A4/5.0

Disambiguation4/5

Most tools are clearly separated by verb and noun (generate_carousel vs generate_image vs generate_video, import_* vs generate_*). The generic convenience names like generate_and_wait and import_and_wait are slightly ambiguous, but their descriptions and the _wait/_schedule suffixes make them distinguishable.

Naming Consistency4/5

All tools share the postnitro_ prefix and snake_case verb-first convention. A few compound names (generate_and_schedule, import_and_wait) break the strict verb_noun pattern, but the convention is otherwise consistent and predictable.

Tool Count2/5

With 35 tools, the surface exceeds the rubric's 25+ 'too many' threshold. Many entries are convenience wrappers (_wait, _and_schedule) around the same core operations and could be consolidated to reduce overload.

Completeness4/5

The domain is well covered: generation, import, output retrieval, scheduling, brands, social accounts, audio, templates, presets, and defaults. Minor gaps remain (no delete_brand, no upload/connect for audio/social accounts), but those are largely external or non-critical.

Resources

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