meridian-edge-mcp

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

With no annotations provided, the description carries full burden. It discloses key behavioral traits: real-time nature, aggregation from multiple regulated markets, and what data is returned (probabilities, trends, confidence/spread). However, it doesn't mention rate limits, authentication needs, error conditions, or whether this is a read-only operation (though 'get' implies it).

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: purpose first, then returns explanation, followed by parameter details in a clear Args/Returns format. Every sentence adds value with no redundancy. The length is appropriate for a tool with 2 parameters and clear functionality.

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 with 0% schema coverage, no annotations, but with output schema present, the description is reasonably complete. It explains what consensus means, what parameters do, and what data is returned. The output schema means return values don't need explanation, but some behavioral context (like rate limits) is missing.

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 0%, so the description must compensate. It fully explains both parameters: 'sport' with specific enum values (NBA, NFL, MLB, NHL, MLS, POLITICS) and behavior when omitted, and 'limit' with range (1-20) and default. This adds significant meaning beyond the bare schema, though it doesn't cover all possible edge cases.

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: 'Get real-time prediction market consensus probabilities' with specific details about what consensus means (aggregated from multiple regulated markets). It distinguishes from siblings by focusing on consensus rather than raw markets, opportunities, settlements, or signals. However, it doesn't explicitly contrast with each sibling tool.

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 implies usage through parameter explanations (filter by sport or get all active events), but doesn't explicitly state when to use this tool versus alternatives like get_markets or get_opportunities. The context is clear (real-time prediction market consensus), but no explicit guidance on tool selection among siblings is provided.

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