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

Annotations declare readOnlyHint=true, so the safety profile is covered. The description adds valuable context beyond that: the return format ('compact overview of peak + dip windows, today's current level, calibration state, not an hourly dump'), the personalization basis (sleep + caffeine + logged energy levels), the empty-state behavior (nudge to log sleep), and the distinction between future (habitual forecast) vs past (actual logged sleep via schema). This is rich behavioral disclosure.

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?

Four sentences, all substantive, front-loaded with the core purpose. The description is efficient but packs in purpose, differentiation, return format, defaults, and edge-case behavior. Slightly dense but earns each word; minor point off for the length relative to what could be trimmed.

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, single-parameter tool with no output schema, this description is complete: covers when to use, what it returns, default behavior, prerequisite failure mode, and personalization source. No output schema increases the burden to describe the return shape, which it does (compact overview, peak/dip windows, current level, calibration state). Nothing important is missing.

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 baseline is 3. The description adds meaning: 'Defaults to today' and 'pass date (ISO YYYY-MM-DD) for another day.' The schema itself also carries strong semantics about future vs past day behavior. Combined, parameter meaning is well-covered with description reinforcing the key default behavior.

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 verb+resource ('Get the user's forecast energy curve') and its purpose (scheduling by alertness). It explicitly distinguishes from siblings: 'get_schedule and show_day don't include energy, so use this when energy matters or the user asks about it.' This is specific and well-differentiated.

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-use guidance: 'use this when energy matters or the user asks about it', names alternatives (get_schedule, show_day) and why they fall short. Also covers the default (today) and prerequisite condition ('Needs at least one logged night of sleep; with none it returns a short nudge to log sleep first').

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