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

Annotations already declare readOnly, idempotent, and non-destructive behavior; the description adds meaningful behavioral detail beyond that: metrics come only from real rows, a strategy with no runs returns a note rather than fabricated numbers, and the two measurement windows are explicitly different. 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 dense and mostly efficient, with every sentence contributing. The backtick-heavy second sentence is slightly run-on and could be broken up, but it contains necessary distinctions rather than filler.

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?

For a single-parameter, read-only tool with no output schema, this description covers inputs, return semantics, the difference between two measurement windows, and the no-data failure behavior. An agent has enough information to invoke the tool correctly and interpret its response.

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?

Although schema coverage is 100%, the description adds significant semantic value beyond the schema: it explains the difference between concept ids and leaderboard slugs, gives concrete examples of each, and clarifies which window each metric covers. This meaningfully improves an agent's ability to supply the correct parameter.

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?

Clearly states the tool returns grounded backtest metrics (ROI/Sharpe/win-rate/drawdown) for a strategy concept, with explicit differentiation between latest_metrics.period and leaderboard headline_period. This distinguishes it from other backtest-related sibling tools and makes its purpose unmistakable.

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 clear context on when to use it and exactly what inputs are accepted (concept id or leaderboard slug) with examples. It doesn't explicitly name sibling alternatives or exclusion conditions, but the usage scope is well-defined and not misleading.

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