get_llms_index
Fetch https://slate.electrik.dev/llms.txt — the curated AI index for Slate.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Fetch https://slate.electrik.dev/llms.txt — the curated AI index for Slate.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Changes observed during successful MCP inspections.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, so the description must carry the burden. It says 'Fetch' which indicates a read operation, but it does not disclose potential side effects, caching behavior, error responses, or any other behavioral traits beyond the basic action.
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 a single concise sentence with no redundancy. It states the action and the target clearly without unnecessary words.
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 simplicity of the tool (no parameters, no output schema), the description sufficiently conveys what it does. It mentions the content type ('AI index') which adds context, though it does not specify the return format explicitly, but that is not required when no output schema exists.
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?
There are zero parameters, so the schema provides no information to cover. The baseline for zero parameters is 4, and the description does not need to explain any parameter semantics, though it also adds no extra detail.
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 fetches a specific URL (llms.txt) for Slate, which is a precise action and distinguishes it from sibling tools that handle component docs or list operations.
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 does not explicitly say when to use this tool over alternatives. It implies it is for retrieving the AI index, but lacks direct guidance on context or comparison with get_docs_page or list_components.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.