meridian-edge-mcp

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 explains what the tool returns ('Formatted list of divergence opportunities ranked by score') and provides some behavioral context about what divergence opportunities represent. However, it doesn't disclose important behavioral traits like rate limits, authentication requirements, error conditions, or pagination behavior that would be helpful for an agent.

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 clear sections for arguments and returns. Every sentence earns its place by providing essential information without redundancy. The formatting with clear section headers (Args, Returns) enhances readability while maintaining conciseness.

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, 3 parameters with 0% schema coverage, no annotations, but with an output schema, the description is mostly complete. It thoroughly documents all parameters and explains the tool's purpose and context. The main gap is lack of behavioral details like rate limits or error handling, but the output schema reduces the need to describe return values in detail.

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 0% schema description coverage, the description fully compensates by providing comprehensive parameter documentation. It explains all three parameters (min_score, sport, limit) with their purposes, default values, valid ranges, and specific sport options. The description adds significant value beyond the bare schema, which only provides titles and types without any semantic meaning.

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 events') and resources ('prediction markets'), explaining what divergence opportunities are and how they're scored. It distinguishes from sibling tools like get_consensus, get_markets, get_settlements, and get_signals by focusing specifically on events with market disagreement rather than consensus, market listings, settlements, or signals.

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 clear context for when to use this tool ('events where prediction markets show notable divergence' and 'where information is still being incorporated'), but doesn't explicitly state when not to use it or name specific alternatives among the sibling tools. The context is sufficient to understand its application without explicit exclusions.

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