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Clerk SDK snippet

clerk_sdk_snippet

Get Clerk SDK code snippets and patterns.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
slugNoSDK snippet slug (e.g. "use-user", "use-auth") OR bundle name (e.g. "b2b-saas", "organizations").b2b-saas

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
textYesRequested Clerk SDK snippet or bundle in Markdown.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • changedOutput schema / (root)
      Previous value: -nullNew value: +{
      +  "$schema": "https://json-schema.org/draft/2020-12/schema",
      +  "additionalProperties": false,
      +  "properties": {
      +    "text": {
      +      "description": "Requested Clerk SDK snippet or bundle in Markdown.",
      +      "type": "string"
      +    }
      +  },
      +  "required": [
      +    "text"
      +  ],
      +  "type": "object"
      +}
  2. Changed2 schema fields changed
    • changedInput schema / $schema
      Previous value: -"http://json-schema.org/draft-07/schema#"New value: +"https://json-schema.org/draft/2020-12/schema"
    • removedInput schema / additionalProperties
      Removed value: -false
  3. First observed

TDQS

B3.2/5.0
Behavior2/5

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

The annotations provide no helpful safety hints since all three hints are false, so the description carries the transparency burden. It only says 'get' and adds no context about side effects, authentication, rate limits, or the fact that a whole bundle may be returned rather than a single snippet.

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 a single, front-loaded sentence that immediately communicates the core action. It contains no filler or unnecessary detail, though it does repeat 'Clerk SDK' from the title.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a low-complexity tool with one optional parameter, a detailed slug schema, and an output schema, the definition is mostly sufficient for invocation. The main gap is that it does not point the agent to list_clerk_sdk_snippets for discovering valid slugs, though the schema already covers the default value.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema already documents the 'slug' parameter thoroughly with examples of both snippet slugs and bundle names, so schema description coverage is 100%. The tool description adds no parameter-specific meaning beyond this, making the baseline score appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a clear action ('Get') and a resource ('Clerk SDK code snippets and patterns'), so the basic purpose is understandable. However, it does not specify that a particular snippet or bundle is retrieved by slug, which leaves it less distinct from the sibling list_clerk_sdk_snippets.

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

Usage Guidelines2/5

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

There is no guidance on when to use this tool instead of list_clerk_sdk_snippets, or that the sibling should be used to discover available slugs. An agent must infer the intended usage entirely from the tool name and schema.

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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