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 adds context about what signals represent ('notable directional moves in prediction market consensus') and details on direction and status, which is useful. However, it lacks information on potential rate limits, authentication needs, or error handling, leaving gaps in behavioral understanding for a tool with no annotation coverage.

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 appropriately sized, with a clear purpose statement followed by details on signals, parameters, and returns. Each sentence adds value, such as explaining signal indicators and parameter specifics, without unnecessary fluff. It could be slightly more concise by integrating the 'Args' and 'Returns' sections more seamlessly, but overall it's efficient.

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 (1 parameter, no annotations, but with an output schema), the description is fairly complete. It covers the purpose, parameter semantics, and return format, and the presence of an output schema means it doesn't need to detail return values extensively. However, it lacks usage guidelines and some behavioral context, which slightly reduces completeness for effective agent use.

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?

The description adds significant meaning beyond the input schema, which has 0% description coverage. It explains the 'limit' parameter's purpose ('Number of signals to return'), range ('1–10'), and default value ('default 5'), effectively compensating for the schema's lack of descriptions. This provides clear semantic context for the single parameter.

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 recent market signals showing direction of price moves.' It specifies the verb ('Get') and resource ('market signals'), and distinguishes them as 'notable directional moves in prediction market consensus.' However, it doesn't explicitly differentiate from sibling tools like get_consensus or get_markets, which likely provide related but different market data.

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 mentions what signals indicate, but doesn't specify scenarios for using get_signals over sibling tools such as get_consensus or get_markets, nor does it outline any prerequisites or exclusions for its use.

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