f1_predict_pit_strategy

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

Annotations already cover the safety profile (readOnly, idempotent, non-destructive, open-world), so the bar is lower. The description still adds real value: it discloses the regulation-distance fallback for total_laps, the INVALID_INPUT failure mode on unknown circuits, explicit-wins precedence, and that expected_finish_position is always None — an honest limitation disclosure. It does not mention cost or latency, but nothing material is hidden.

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?

Front-loaded with a one-sentence purpose, then Args/Returns/Example in a scannable structure. The Returns section is long but each field is load-bearing for interpreting results. Slight repetition between the Args text and the schema descriptions is the main inefficiency.

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 predictive tool with four parameters and an output schema, the description covers inputs, the fallback logic, key output fields, a caveat field, and two concrete call examples. An agent can call it correctly from this alone; the only gap is routing guidance against related strategy tools.

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 coverage is 100%, so the schema already documents all four parameters and the description's Args block is largely a restatement. The only marginal addition is the default-1 meaning 'full race ahead', which is close to what the schema says. Baseline 3 is appropriate.

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 verb and resource: predicting an optimal pit-stop strategy for a named driver in a recorded race session. The scope ('session + driver + current lap') is precise enough to distinguish it from data-retrieval siblings like f1_get_lap_times. However, it never names or contrasts itself with strategy-adjacent siblings such as f1_undercut_window, f1_tyre_degradation, or f1_weather_strategy_impact.

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 the usage context ('recorded race', 'use f1_get_drivers' to obtain driver numbers), which gives the agent a prerequisite hint. But it offers no guidance on when to choose this tool versus f1_undercut_window, f1_tyre_degradation, or f1_weather_strategy_impact — the alternatives an agent would most plausibly confuse it with.

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