alderpost-mcp

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

With no annotations provided, the description carries full burden for behavioral disclosure. It mentions pricing ($0.50 USDC on Base) which hints at a paid service, but doesn't describe authentication requirements, rate limits, error conditions, or what happens when the tool is invoked. The description doesn't contradict any annotations (none exist), but provides minimal behavioral context beyond the commercial aspect.

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 reasonably concise but has structural issues. The first sentence clearly states the purpose, but the second sentence about pricing feels tacked on and doesn't help the AI agent understand tool functionality. While not verbose, the description isn't optimally front-loaded with only the most essential information for tool selection.

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?

For a tool with 2 parameters, no annotations, and no output schema, the description is insufficient. It doesn't explain what the AI-generated analysis includes, how standings and odds are presented, or what format the output takes. The pricing information doesn't compensate for these gaps in understanding the tool's behavior and output.

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 100%, so the schema already fully documents both parameters (sport with allowed values, team as filter). The description adds no parameter-specific information beyond what's in the schema. The baseline score of 3 reflects adequate parameter documentation through the schema alone, with no value added by the description.

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: providing pre-game sports intelligence including standings, odds, and AI-generated analysis. It specifies the resource (sports data) and verb (intelligence gathering), but doesn't differentiate from sibling tools since all siblings appear to be in different domains (company, compliance, health, etc.). The mention of pricing is extraneous but doesn't obscure the core purpose.

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. While the domain is clearly sports-related, there's no mention of specific use cases, prerequisites, or comparisons to other sports data tools that might exist elsewhere. The pricing information hints at a commercial context but doesn't constitute usage guidance.

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