Katzilla MCP

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

Annotations already cover read-only, non-destructive, idempotent, and open-world hints, so the description adds valuable behavioral context beyond that: it specifies the data source (CoinRanking, Public), update frequency (real-time), and return format (Katzilla envelope with quality scores and citation details including SHA-256 hash for audit). No contradiction with annotations.

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 front-loaded with core functionality, uses efficient sentences without waste, and structures information logically (purpose, features, source, return format). Every sentence adds value, such as specifying the Katzilla envelope details.

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 (5 parameters, real-time data), rich annotations, and the presence of an output schema (implied by mention of return format), the description is complete. It covers purpose, usage, behavioral traits, source, and output structure, leaving no significant gaps for an AI agent.

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 fully documents all parameters. The description adds minimal parameter semantics by mentioning filtering by tier and sorting options, but this is largely redundant with the schema. Baseline 3 is appropriate as the schema carries the burden.

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 live cryptocurrency prices and market data') and resources ('for 2,000+ coins from CoinRanking'), distinguishing it from sibling tools like crypto__coinpaprika or crypto__coinlore-stats by specifying the data source and scope.

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 usage ('Filter by tier, sort by market cap, price, or 24h change') and implies when to use it for real-time cryptocurrency data. However, it does not explicitly state when not to use it or name specific alternatives among siblings, such as crypto__blockchain-stats for different data types.

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