LearnMCP Server

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 states the tool adds URLs for extraction and summarization, implying a write operation, but doesn't cover critical aspects like required permissions, whether changes are reversible, rate limits, or what happens on success/failure. This is a significant gap for a mutation tool.

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, efficient sentence that front-loads the core purpose without unnecessary details. Every word earns its place, making it easy to parse and understand quickly.

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's complexity as a mutation operation with no annotations and no output schema, the description is incomplete. It lacks behavioral context (e.g., side effects, error handling) and doesn't explain return values, leaving the agent with insufficient information for reliable invocation.

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 100%, so the schema already documents both parameters (project_id and urls). The description adds minimal value by specifying that URLs are for content extraction and summarization and listing allowed types (YouTube, PDF, articles), but doesn't provide syntax or format details beyond what the schema implies. Baseline 3 is appropriate when schema does the heavy lifting.

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 action ('Add') and resource ('learning sources (URLs) to a project'), specifying the purpose as adding URLs for content extraction and summarization. It distinguishes from siblings like delete_learning_sources or list_learning_sources by focusing on addition, though it doesn't explicitly contrast with process_learning_sources which might involve similar resources.

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 no guidance on when to use this tool versus alternatives like process_learning_sources or get_learning_summary. It mentions the purpose but lacks explicit context, prerequisites, or exclusions, leaving the agent to infer usage from tool names alone.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.