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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint. The description adds significant behavioral detail: 'this tool never raises a protocol error — it returns an error object with fix instructions' and 'Every call is read-only and idempotent, so after correcting the input it is always safe to retry.' No contradictions 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 well-structured: purpose statement, premium note, example, usage guidelines, error handling. It is front-loaded with the main action. The example, while helpful, adds a bit of length; overall it is concise without unnecessary repetition.

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?

With only 2 parameters, rich annotations, and an output schema, the description covers all essential aspects: purpose, usage context, behavioral traits (idempotent, read-only, error handling), parameter semantics, and output format (trend_per_period, r_squared, forecast, caveat). It leaves no gaps for an agent to misunderstand.

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 baseline is 3. The description provides a typical input example that demonstrates proper parameter usage and includes error handling details that clarify validation behavior (e.g., minimum 4 values). This adds value beyond the schema's parameter descriptions.

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 'Forecast future periods with a linear trend and honest fit quality,' specifying the verb (forecast), resource (future periods), and method (linear trend). It includes a typical input/output example, distinguishes from the sibling 'growth_rates' by noting it's not for measuring already observed growth, and sets expectations with 'For quick planning, not statistical modeling.'

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?

Explicitly says 'Use when a series is roughly linear and fit quality matters as much as the projection. Not for seasonal or cyclical data, and not for measuring growth already observed (growth_rates).' This provides clear when-to-use and when-not-to-use guidance, and names an alternative tool (growth_rates).

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