meridian-edge-mcp

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

No annotations are provided, so the description carries the full burden. It discloses that the tool returns 'active prediction markets currently being tracked' and 'markets that are open and being monitored for consensus,' which adds context about filtering and monitoring status. However, it lacks details on permissions, rate limits, or error handling, which are important for a read operation 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 appropriately sized and front-loaded: the first sentence states the purpose, followed by usage guidance, and then structured sections for Args and Returns. Every sentence earns its place with no wasted words, making it easy to scan and understand quickly.

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 (simple read operation with 2 parameters) and the presence of an output schema (which handles return values), the description is fairly complete. It covers purpose, usage, parameters, and return format. However, with no annotations, it could benefit from more behavioral context like error cases or performance hints, but the output schema reduces the need for extensive return value explanation.

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 adds meaning beyond the schema by specifying that 'sport' filters by listed sports (NBA, NFL, etc.) or can be omitted, and 'limit' has a range (1–20) with a default of 10. This provides clear semantics, though it doesn't fully detail all possible values or constraints beyond the basics.

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 active prediction markets currently being tracked' specifies the verb (get) and resource (active prediction markets). It distinguishes from siblings by mentioning 'before querying consensus' which hints at get_consensus, but doesn't explicitly differentiate from all siblings like get_opportunities or get_settlements.

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 implied usage guidance: 'Use this to see what events are currently available before querying consensus' suggests when to use this tool (to see active markets) and hints at an alternative (get_consensus). However, it doesn't explicitly state when not to use it or mention other siblings like get_opportunities or get_settlements, leaving some ambiguity.

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