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

Annotations already declare readOnlyHint, openWorldHint, and idempotentHint, so the safety profile is known. The description adds valuable behavioral context with the caveat that 'last_backtest timestamp indicates tuning freshness' and clarifies that data is 'derived from real backtest outcomes'. This goes beyond the annotations without contradicting them.

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 with labeled sections (Purpose, Triggers, When to call, Prerequisites, Next steps, Caveats, Args, Disclaimer) and front-loads the purpose. However, it is somewhat verbose with extensive trigger examples and a boilerplate disclaimer, which could be trimmed without losing essential information.

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 an output schema present, return values are covered. The description provides purpose, triggers, usage sequence, prerequisites, caveats, and parameter explanations, making it highly complete for a read-only, idempotent tool. The caveat about timestamp freshness is a nice contextual addition.

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 input schema provides only type and default for each parameter (category, target_market) with zero description coverage. The description adds 'Optional category filter' and 'Optional target market filter', which confirms they are optional filters but doesn't elaborate on allowed values or formats. This is minimal compensation for the schema gap.

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: 'Continuous self-calibration evidence' showing auto-tuned lag_hours and sensitivity per cell derived from real backtest outcomes. It uses a specific resource (backtest tuning state) and distinguishes itself from sibling tools like get_signal_calibration and get_prediction_accuracy.

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?

Provides explicit 'When to call' context after get_prediction_accuracy, lists 'Prerequisites' and 'Next steps' (get_monthly_accuracy_trend), and includes a comprehensive list of trigger phrases. This gives clear guidance on when to use the tool and how it fits into a sequence, even though it doesn't name an alternative tool to avoid.

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