Niche — Editorial Intelligence

Update brand kit

niche_brand_kit_update

Set specific BrandKit fields by name. The write path for the structured fields (tagline / boilerplate / voice_notes / forbidden_phrases / signature_phrases / endcard preferences / video voice preference / colors / fonts) without going through the ingest engine. Use after niche_brand_kit_ingest fills the easy stuff, or to commit values the user answered through niche_brand_kit_guided_setup.

Only fields you pass are touched; fields you omit stay at their current value. Lists replace the current value (they do not append). Response includes a diff[] of fields that changed and the full updated kit.

Archiving: pass archive=true to archive a brand (soft and reversible; it disappears from every list but is not deleted), or archive=false to restore one. The default/active brand can't be archived (promote another to default first). A brand with published history won't archive unless you also pass acknowledge=true. Use archive_scope='test' to archive every scratch brand at once (never the default). There is no hard delete here; archive is the removal verb agents have.

Input Schema

TableJSON Schema

Name	Required	Description
`name`	No	Rename an existing brand's display name (its brand_id is unchanged).
`accent`	No
`archive`	No	true archives the brand (soft, reversible; hidden from every list, not deleted); false restores it. Refuses the default/active brand and refuses a brand with published history unless acknowledge=true.
`tagline`	No	Brand tagline (5-12 words).
`brand_id`	No	Which brand slot to update. Omit for default; pass a slug to target a specific brand kit (for multi-brand accounts).
`cta_text`	No	One-line call to action appended to generated posts, e.g. 'DM to commission'.
`logo_url`	No
`brand_name`	No	Display name when creating a new brand_id slot.
`primary_bg`	No	Primary background color (#rrggbb).
`acknowledge`	No	Required (true) to archive a brand that has published history, confirming the user means to remove it from the roster even though it shipped work.
`boilerplate`	No	Brand boilerplate (one paragraph, ≤350 chars).
`voice_notes`	No	Voice direction in plain prose. A string or a list of strings (the guided-setup text_list form); a list is joined server-side.
`external_url`	No	Canonical brand URL (homepage).
`headshot_url`	No
`secondary_bg`	No
`text_primary`	No
`wordmark_url`	No
`archive_scope`	No	With archive=true, 'test' archives every scratch brand in one call (never the default). Returns the list of brands archived; each is reversible with archive=false.
`text_secondary`	No
`body_font_family`	No
`endcard_template`	No
`forbidden_phrases`	No	Phrases never to use in generated copy. Max 16; trimmed beyond.
`signature_phrases`	No	Phrases the brand uses. Max 16.
`endcard_outro_text`	No
`headline_font_family`	No
`video_voice_preference`	No
`endcard_mark_preference`	No

TDQS

A4.8/5.0

Behavior5/5

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

The description reveals key behaviors beyond annotations: partial-field updates ('Only fields you pass are touched'), list replacement semantics, response shape (diff[] and full updated kit), and soft-reversible archiving ('soft and reversible; no hard delete'). These details are critical for a mutation tool with destructiveHint=false, adding context annotations don't provide.

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?

The description is lengthy but efficiently organized: purpose first, then update semantics, then archiving. Each sentence adds value, and the length is justified for a tool with 27 parameters and complex archiving behavior. It avoids redundancy and front-loads the core action.

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?

Despite no output schema, the description states the response includes a diff and full kit, covering the main expected return. It addresses edge cases for archiving (default brand, published history, archive_scope='test') and alternative usage flows via siblings, making it comprehensive for the tool's complexity.

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?

With schema coverage at 52%, the description compensates by grouping fields (tagline, boilerplate, voice_notes, etc.) and explaining behavior patterns like list replacement and omit-preserves-current-value. It also clarifies archiving parameters and their consequences, though it doesn't enumerate every parameter individually.

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 opens with 'Set specific BrandKit fields by name', clearly identifying the write path and distinguishing it from the ingest engine and guided setup. It enumerates the structured fields, making the resource scope explicit and differentiating it from sibling tools like niche_brand_kit_ingest.

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?

Explicitly states when to use: 'Use after niche_brand_kit_ingest fills the easy stuff, or to commit values the user answered through niche_brand_kit_guided_setup.' It also provides exclusion conditions for archiving (default/active brand can't be archived, published history requires acknowledge=true), offering clear guidance over alternatives.

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

A4.2/5.0

Disambiguation4/5

Tools are mostly distinct across the pipeline—discovery, brand setup, drafting, rendering, publishing, session management—and descriptions are detailed. Minor overlap exists between niche_signal_scan and niche_intelligence_query (both discovery) and between niche_add_output and niche_draft_create (both generate outputs), but the descriptions clearly differentiate them. Overall, an agent can reliably select the right tool.

Naming Consistency3/5

All tools share the `niche_` prefix and snake_case, but the verb/noun order is inconsistent: some are verb-first (add_output, render_image_card, list_sessions) while many are noun-first (angle_propose, brand_kit_ingest, draft_create, session_cancel). This mixed convention requires the agent to learn each name individually rather than predict the pattern.

Tool Count3/5

25 tools is on the heavy side but appropriate for the platform's scope—full editorial intelligence from discovery to publish. No redundant tools, and each covers a distinct aspect, but the count is high enough that it feels dense and may require orientation (which niche_whoami addresses).

Completeness4/5

The toolset covers the full workflow: discovery, angle proposal, drafting, revision, publishing, rendering, asset attachment, brand setup, and session management. Minor gaps exist, such as no direct read tool for the current BrandKit (only via ingest status) and no hard-delete tool (session_cancel mentions the REST endpoint instead), but these are edge cases and agents can work around them.

Update brand kit

Input Schema

TDQS

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TDQS

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