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

Annotations already mark it readOnly/idempotent/non-destructive; the description goes far beyond by explaining timezone handling, retention windows, bot inclusion/exclusion, null-vs-zero semantics, plan-dependent detail levels, and truncation flags. 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 first sentence front-loads the core purpose and identifier options, and every subsequent sentence adds non-obvious decision-relevant detail such as retention limits, previous_period null behavior, and plan differences. It is dense but not redundant; the length is proportional to the tool's complexity.

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, the description is unusually complete: it covers calling conventions, timezone/date behavior, plan tiers, retention, bot filtering, uniqueness semantics, truncation flags, and content-type definitions. The output schema further covers return structure, so nothing needed for correct selection or invocation appears missing.

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?

Input schema covers all parameters, so baseline is 3, but the description adds real value: it explains the live/daily distinction for range values, the inclusive from/to pairing, and which prior calls produce valid publication_id values. This is above baseline, though the schema already documents the basic parameter shapes.

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?

States a specific action ('Get ... analytics') and resource ('bucket website's analytics'), and shows two identifier routes (bucket_id or publication_id). The description clearly separates it from sibling get/list tools by focusing on analytics, so an agent can tell it apart without opening the schema.

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?

Gives clear invocation context: use bucket_id or supply publication_id from bucket_get, bucket_publish, or bucket_publication_list. It does not explicitly list when-not-to-use or name alternative analytics tools, but the identifier provenance and window semantics make selection unambiguous.

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