Return the full rule pages for a given category. Each rule includes the title, description, markdown body explaining the rule, and any HTML/CSS code examples from the playbook. Use this to teach a model the exact patterns for a specific concern (e.g., responsive layout).
| Name | Required | Description | Default |
|---|---|---|---|
| category | Yes | Which rule category to fetch. |
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?
With no annotations, the description carries the burden of behavioral disclosure. It explains the return content but does not explicitly state that it is read-only, idempotent, or mention potential errors or permissions. The description adds useful context about the rule structure but lacks a full behavioral profile.
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?
The description is two sentences, front-loaded with the purpose and followed by a concrete use case. Every sentence adds value, and there is no redundancy or fluff.
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 simple one-parameter tool with no output schema or annotations, the description adequately communicates what is returned and when to use it. It could go further by listing the enum values or clarifying error behavior, but the schema covers the category choices.
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 input schema already provides full coverage for the 'category' parameter with an enum and description. The description adds an example ('responsive layout') but does not materially enhance the schema's parameter semantics. Baseline 3 is appropriate given schema coverage is 100%.
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 clearly states the tool 'Return the full rule pages for a given category' and specifies the content of each rule. It distinguishes itself from siblings like get_component by focusing on rule pages with markdown and code examples for teaching.
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 description provides a clear use case: 'Use this to teach a model the exact patterns for a specific concern'. It does not explicitly exclude alternatives or name sibling tools, but the intended context is evident.
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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