get_cycle_context

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

Annotations already declare readOnlyHint and idempotentHint, and the description adds meaningful behavioral detail beyond those: the phase-label rule, the derived-not-predictive nature, and the observed-midpoint method. It also discloses that no ovulation estimate is made, which is important for an agent considering this tool for health data interpretation.

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 a compact, information-dense two-sentence definition. It front-loads the core purpose and source, then adds necessary behavior constraints and parameter behavior. Each sentence earns its place with no filler, though the organization could be slightly tighter.

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 read-only, zero-required-parameter tool with no output schema, the description covers the important context: input semantics, default behavior, derivation source, and the exact output dimensions. The return values are sufficiently described at a high level (day-in-cycle and phase label) to make the tool usable.

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 schema description coverage is 100% for the single date parameter, and the description enriches it further: the date is optional, it applies to a single day, and the default behavior returns per-day context for the last cycle. This gives the agent a complete understanding of parameter behavior beyond the bare YYYY-MM-DD schema.

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 names a specific resource (user-logged period starts), a specific output (day-in-cycle and phase label), and the source file (health-cycles.json). It also distinguishes itself by explicitly noting it is derived from logged periods only and never predictive, which separates it from potential ovulation or prediction tools even without naming them.

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 gives a clear context for use: it is for cycle context based purely on logged period starts, and it explicitly excludes predictive or ovulation-estimation use cases. It does not explicitly name sibling tools or provide direct when-to-use-alternative language, but the scope and exclusions are strong enough to guide an agent.

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