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Create Brand Tool

create-brand-tool

Create a brand in a project, ahead of Pineprompt discovering it from an AI response. Segment membership is what makes a brand a competitor, so pass segment_ids to start tracking it right away; without them the brand starts out discovered. When aliases are omitted, the brand is seeded with its display name. Display names are unique per project, case-insensitive, so a name that collides with an existing brand's display name or alias returns an error. To designate a brand as the project's own brand, pass its id as brand_id on the update-project tool instead.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
aliasesNoThe names Pineprompt matches against when it attributes a mention to the brand. Aliases are stored as sent and compared while ignoring casing and punctuation. On update the list replaces the current one; on create it defaults to the display name.
domainsNoThe domains Pineprompt matches against when it attributes a citation to the brand. Full URLs are accepted and reduced to bare lowercase hosts. On update the list replaces the current one.
project_idYesThe numeric id of the project the brand belongs to.
segment_idsNoThe numeric ids of the project segments the brand should join. Membership makes the brand a competitor; omit the list to create the brand as discovered.
display_nameYesThe name the brand is shown under (2 to 255 characters). Display names are unique per project, case-insensitive, and may not collide with an alias of another brand.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.8/5.0
Behavior5/5

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

Annotations only declare the generic mutation profile (readOnly=false, idempotent=false, destructive=false). The description adds substantive traits: display names are unique per project case-insensitively, and a collision with an existing name or alias returns an error. It also explains that segment membership is what makes a brand a competitor, which is behavior the annotations cannot convey.

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-loaded with the core action, then conditions and error behavior. It is dense but each clause carries distinct information (defaults, uniqueness, alternative route). Slightly long, but no sentence is filler.

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?

For a 5-param, no-output-schema mutation tool, the description covers defaults, uniqueness/error behavior, and the alternative path for designating the project's own brand. With the schema fully documenting each parameter, an agent has everything needed to call it correctly.

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. The description goes beyond the schema by explaining the semantic consequence of `segment_ids` (membership makes a brand a competitor) and the cross-tool role of a brand id on update-project, which is not derivable from this tool's schema.

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 and resource ('Create a brand in a project') and distinguishes the outcome from the automatic discovery path ('ahead of Pineprompt discovering it from an AI response'). An agent can tell this apart from update-brand-tool and attach-brand-to-segment-tool without opening either schema.

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 conditional guidance: pass `segment_ids` to start tracking as a competitor, omit them to create as discovered, and omit aliases to seed with the display name. It also routes the own-brand case to a named alternative ('pass its id as `brand_id` on the update-project tool instead'), which is exactly the when-not/alternative guidance the dimension rewards.

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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