mymedi-ai-mcp-server

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

With no annotations provided, the description carries full burden for behavioral disclosure. It mentions the tool 'identifies... with confidence scores' which hints at output behavior, but doesn't disclose important traits like whether this is a read-only operation, potential rate limits, authentication requirements, error conditions, or what happens with invalid input. For a tool processing clinical text with no annotation coverage, this leaves significant behavioral gaps.

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 extremely concise and front-loaded with all essential information in two efficient sentences. The first sentence establishes the core purpose, and the second sentence provides valuable detail about what entities are extracted. There is zero wasted language or redundancy.

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 moderate complexity (2 parameters, no output schema, no annotations), the description provides adequate but incomplete coverage. It clearly states what the tool does and what it extracts, but lacks guidance on usage context and behavioral details. Without annotations or output schema, the description should ideally provide more information about what the tool returns and its operational characteristics.

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 fully. The description mentions 'clinical text' which aligns with the 'text' parameter, and '12 entity types' which relates to the 'entityTypes' parameter, but adds no additional semantic context beyond what the schema provides. This meets the baseline expectation when schema coverage is complete.

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's purpose with specific verbs ('extract', 'identifies') and resources ('medical named entities', 'clinical text'), listing 5 specific entity types (ICD-10 codes, CPT codes, dates, medications) plus 12 entity types with confidence scores. It distinguishes itself from sibling tools focused on claims, codes, compliance, drugs, market analysis, prior authorization, and providers by focusing specifically on entity extraction from clinical text.

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. While it's clear this is for extracting medical entities from clinical text, there's no mention of when to use it instead of sibling tools like drug_enrich, provider_enrich, or code_lookup that might handle related but different tasks. No prerequisites, exclusions, or comparative context is provided.

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