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get_content_pattern

Read-onlyIdempotent

Retrieve content design patterns for error messages, empty-state copy, notifications, and form validation. Each pattern provides do's, don'ts, good/bad examples, evidence, and a checklist.

Instructions

Get content design patterns — copy recipes for error messages, empty-state copy, notifications, and form validation. Returns do's, don'ts, good/bad examples, evidence, and a checklist.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
typeYesContent pattern type

Schema Changelog

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

  1. First observedv2.2.9

TDQS

A4.5/5.0
Behavior4/5

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

Annotations already establish that this operation is read-only, idempotent, and non-destructive, so the description only needs to add value beyond safety. It does by describing the return content (do's and don'ts examples, evidence, checklist), which is particularly helpful because there is no output schema. No hidden behaviors, side effects, or constraints are missing.

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 two sentences long with no filler and front-loads the key noun phrase. It includes only the essential facts: what patterns are available and what the response contains. Every sentence contributes useful context.

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 one-parameter, read-only tool with no output schema, this description is complete. It gives the agent the full scope of the parameter, describes the result contents, and relies on annotations to communicate the safe, idempotent nature of the call. There is little missing information that would prevent a correct invocation.

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 input schema already fully covers the parameter, so the baseline is 3. The description adds value by framing the type as copy recipes and listing the four domain categories in natural language, helping an agent reason about what value to pass beyond the raw enum labels. It doesn't repeat schema list verbatim, but it does make the parameter's meaning and expected content clearer.

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 uses a specific verb ('Get') and a specific resource type ('content pattern'), and details the exact copy recipe categories covered (error messages, empty-state, notifications, form validation). It also clarifies what the returned content includes, separating it from more general tools like get_principles or get_pattern. This is enough for an agent to know what this tool is for.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description clearly indicates when to use the tool: when the agent needs copy recipes for these specific UI content categories. It gives a strong use context, but it does not explicitly mention alternatives or exclusions relative to sibling tools like get_content_principles, which keeps it just below an explicit 5.

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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