calculate_readiness_score

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It adequately describes what the tool does (calculates a readiness score) and its practical application, but doesn't disclose important behavioral aspects like how the calculation algorithm works, what happens with missing data, whether the score is cached or real-time, or what format the output takes. The description doesn't contradict any annotations since none exist.

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 perfectly structured and concise - the first sentence clearly states the tool's purpose and practical application, while the Args section efficiently documents the single parameter with format and default information. Every sentence earns its place with no wasted words.

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?

Given the tool's moderate complexity (calculating a readiness score from multiple factors) and the absence of both annotations and output schema, the description is adequate but has gaps. It explains what the tool does and its practical application, but doesn't describe the output format (just mentions it returns a 1-10 score) or address edge cases like missing data. For a calculation tool with no structured output documentation, more detail would be helpful.

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 description adds significant value beyond the input schema, which has 0% description coverage. It explains that target_date is an 'ISO date string (YYYY-MM-DD)' and 'Defaults to today,' providing format details and default behavior that aren't in the schema. Since there's only one parameter and the description covers it well, this earns a high score despite the schema's poor coverage.

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 with specific verb ('calculate') and resource ('readiness score'), and explicitly lists the three input factors (sleep quality, resting heart rate, prior-day exertion). It distinguishes this from sibling tools like get_health_summary or propose_schedule by focusing specifically on readiness scoring rather than general health data or scheduling.

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 provides explicit guidance on when to use this tool ('to decide when to schedule demanding tasks') and distinguishes it from alternatives by focusing on readiness scoring rather than raw data retrieval (query_raw_logs), task management (get_tasks), or scheduling generation (propose_schedule). The practical application context is clearly stated.

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