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

Annotations already cover read-only, non-destructive, idempotent, and open-world properties. The description adds valuable behavioral context beyond annotations: 'intelligent caching for performance', 'pagination for large datasets exceeding token limits', and 'returns only essential identifier fields for efficient browsing'. 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 purpose in the first sentence, followed by supporting details. Every sentence adds value: scope of models, return format, performance features, and pagination support. No wasted words or redundancy.

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 (list operation with pagination), rich annotations, and 100% schema coverage, the description is largely complete. It explains the tool's optimization approach and caching behavior. The main gap is lack of output schema, but the description partially compensates by stating 'returns only essential identifier fields'.

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%, providing full parameter documentation. The description adds minimal extra semantics, mentioning 'highly optimized responses' and 'intelligent caching' which relate to overall tool behavior rather than parameter specifics. 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 verb ('fetch all records') and resource ('single Metabase resource type'), specifying the exact models supported (cards, dashboards, tables, databases, collections). It distinguishes from siblings like 'search' by emphasizing 'complete lists' for 'overview purposes' rather than filtered results.

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 when to use this tool ('for overview purposes', 'efficient browsing', 'highly optimized responses'), but does not explicitly state when not to use it or name alternatives like 'search' or 'retrieve' from the sibling list. It implies usage for bulk retrieval vs. specific lookups.

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