create_recipes_test_scrape_url
Test recipe scraping by providing a URL to parse and extract structured recipe data.
Instructions
Test Parse Recipe Url
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes | ||
| useOpenAI | No | ||
| accept-language | No |
Test recipe scraping by providing a URL to parse and extract structured recipe data.
Test Parse Recipe Url
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes | ||
| useOpenAI | No | ||
| accept-language | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It does not mention side effects (e.g., actual recipe creation), error conditions, authorization needs, or output behavior. The description is completely silent on expected behavior beyond the tool name.
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 only four words, which is under-specification rather than conciseness. It omits critical information and does not earn its brevity. Every sentence should add value, but here no value is added beyond the tool name.
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?
Given the tool has 3 parameters with no schema descriptions, no output schema, and no annotations, the description is highly inadequate. It does not cover what the tool returns, how to use its parameters, or what to expect after invocation. The agent would be left guessing about essential behavior.
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?
Schema description coverage is 0%, and the description adds no meaning to the parameters. 'url', 'useOpenAI', and 'accept-language' are left unexplained. For example, what format does the URL require? Does 'useOpenAI' affect parsing strategy? The description fails to clarify these essential details.
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 'Test Parse Recipe Url' vaguely indicates testing/parsing a recipe URL, but it does not clearly state what the tool does (e.g., whether it scrapes and creates a recipe or just tests parsing). It also fails to distinguish from siblings like 'create_recipes_create_url' which likely perform similar actions.
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?
No guidance is provided on when to use this tool versus alternatives. The description does not mention any prerequisites, intended use cases, or scenarios where this tool should be preferred over other 'create_recipes' tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
We provide all the information about MCP servers via our MCP API.
curl -X GET 'https://glama.ai/api/mcp/v1/servers/djwmarcx/better-mealie-mcp'
If you have feedback or need assistance with the MCP directory API, please join our Discord server