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

With no annotations, the description fully discloses behavioral traits: permanent storage, indefinite growth, 20-record minimum, 60 req/min rate limit, 5-min cache, no authentication required. This exceeds expectations for a tool with no 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 the core purpose and is structured logically: purpose, fields, exclusion rule, data source, limitations. Every sentence adds value without redundancy, achieving high information density while remaining readable.

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?

Despite no output schema, the description exhaustively lists return fields and explains the aggregation, exclusion criteria, rate limits, and cache duration. An AI agent has sufficient information to correctly invoke and interpret the tool's 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?

The tool has no parameters, so the description does not need to describe any. According to guidelines, baseline is 4 for zero parameters, which is appropriate as the description adds no parameter info but also has no gaps.

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 that the tool returns a permanent monthly archive of Golden Alert activity, aggregated from daily snapshots. It lists specific fields (e.g., totalCount, highCount, mediumCount, lowCount, topTokens), distinguishing it from sibling tools like 'golden_alerts_history' and 'golden_alerts_snapshot'.

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 implies usage for long-term trend analysis but does not explicitly state when to use this tool versus alternatives (e.g., golden_alerts_history). It provides context on exclusions (months with <20 daily records) and data source, which aids decision-making, but explicit alternatives are missing.

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