gleif-mcp-server

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

Annotations already declare readOnlyHint=true and idempotentHint=true, indicating safe, repeatable operations. The description adds valuable behavioral context beyond annotations by specifying failure conditions (invalid LEI format, missing relationships) and referencing get_reporting_exceptions for troubleshooting, though it doesn't detail rate limits or authentication needs.

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 well-structured and front-loaded with the core purpose, followed by usage guidelines and failure conditions. Each sentence adds essential information without redundancy, such as clarifying relationship types and referencing sibling tools, making it efficient and easy to parse.

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, lack of output schema, and rich annotations, the description is largely complete. It covers purpose, usage, failure modes, and references alternatives, though it could benefit from brief examples of return values or pagination details to fully compensate for the missing output schema.

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?

With 100% schema description coverage, the schema fully documents both parameters (LEI code with format constraints, relationship type with enum values). The description adds minimal semantic context by listing relationship types and LEI format requirements, but this largely repeats schema information, meeting the baseline for high coverage.

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 ('Get corporate ownership and fund relationships') and resources ('for an entity'), distinguishing it from siblings like validate_lei or search_by_isin that handle different entity-related queries. It precisely defines the scope of relationships retrieved.

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 explicit usage guidance with 'USE WHEN' examples (e.g., 'who owns X?', 'parent company') and 'FAILS WHEN' conditions (e.g., invalid LEI format, no relationships exist). It also references an alternative tool (get_reporting_exceptions) for handling missing ownership data, clearly differentiating when to use this tool versus others.

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