mymedi-ai-mcp-server

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions scanning for PHI exposure and returning findings, but lacks details on permissions required, rate limits, whether the operation is read-only or modifies data, error handling, or performance characteristics. For a compliance audit tool with no annotation coverage, this leaves significant gaps in understanding its behavior.

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 front-loaded and efficient, using two sentences to convey purpose and output. Every sentence earns its place by specifying the audit type, what it scans for, and what it returns. However, it could be slightly more structured by separating usage context from behavioral details.

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 (compliance auditing with pattern matching), lack of annotations, and no output schema, the description is moderately complete. It covers the core purpose and output format but misses behavioral traits and detailed usage guidelines. It's adequate for basic understanding but insufficient for full operational clarity without additional context.

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 ('data' and 'auditType') with descriptions and enum values. The description adds minimal value beyond the schema—it implies 'auditType' might default to 'hipaa' based on context, but this isn't explicitly stated. Baseline 3 is appropriate since the 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 tool's purpose with specific verbs ('Scans data for PHI exposure') and resources ('HIPAA compliance audit'), and it distinguishes itself from sibling tools by focusing on compliance auditing rather than claims validation, code lookup, or other healthcare-related functions. It specifies what patterns it looks for (SSN, MRN, DOB) and what it returns (findings with severity, score, recommendations).

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. It doesn't mention any prerequisites, constraints, or comparisons with sibling tools like 'claims_validate' or 'ner_extract', which might also process healthcare data. The context is implied (HIPAA compliance), but explicit usage scenarios or exclusions are missing.

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