list_backgroundsBrowse the catalog of background structures. Optionally filter by a free-text query, tag or mood word. Returns name, one-line summary, mood, use cases and a preview URL for each.
| Name | Required | Description | Default |
|---|---|---|---|
| tag | No | ||
| mood | No | A mood word, e.g. dark, playful, minimal, retro. | |
| limit | No | ||
| query | No | Free text, e.g. "calm waves" or "geometric poster". |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already cover safety with readOnlyHint and idempotentHint. The description adds useful behavior beyond that: it supports filtering by query, tag, or mood, and specifies the return shape (name, summary, mood, use cases, preview URL), which is valuable since no output schema exists. No contradiction with annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences with no filler: purpose is front-loaded, optional filters are summarized in a compact list, and return fields are enumerated. Every phrase earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a read-only, all-optional-parameter list tool with no output schema, the description covers purpose, filters, and return content sufficiently for an agent to make a correct call. Minor gaps like pagination behavior and limit defaults are not blocking given the simple catalog-browsing context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema documents mood and query but not tag or limit, leaving 50% coverage. The description adds that tag and mood serve as filters, which helps clarify tag, but it does not explain the limit parameter or the acceptable tag values. It partially compensates for the schema gap but not fully.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description has a specific verb and resource: 'Browse the catalog of background structures.' It also enumerates the returned fields. It is naturally distinct from describe/generate siblings, but it does not explicitly differentiate from suggest_backgrounds, so it falls short of a 5.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The purpose is implied through 'browse the catalog' and the optional filtering flags, but there is no explicit guidance on when to use this tool versus describe_background or suggest_backgrounds. No exclusions or alternative routing are provided, leaving some selection to inference.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Each tool targets a distinct task: browsing catalog, inspecting a structure, generating output, listing palettes, listing brand kits, and suggesting options. list_brand_kits and list_palettes are the only superficially similar pair, but their descriptions clearly separate saved account kits from built-in palettes.
All tools use the same verb_noun snake_case convention: describe_, generate_, list_, and suggest_. Pluralization is consistent within each verb's usage, making the naming predictable and easy to infer.
Six tools is well-scoped for a background generation service. Discovery, description, generation, suggestion, and color inputs are each represented without redundancy or excessive surface area.
The tool set covers the full consumer workflow: browse backgrounds, understand a structure, generate an image, and supply palettes or brand kits. The only potential gap, managing brand kits, is outside the server's stated purpose.