propose_schedule

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It describes the scheduling logic (energy-aware, placing high-energy tasks when readiness supports them), which adds useful context beyond basic functionality. However, it lacks details on critical behaviors: it doesn't specify what 'readiness score' means, how tasks are prioritized, whether the schedule is saved or tentative, or what the output format is. For a tool with no annotations and no output schema, this leaves significant gaps in understanding its operation.

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 appropriately sized and front-loaded: the first sentence clearly states the purpose, and the second adds key behavioral context. The Args section is concise and adds necessary parameter details without redundancy. Every sentence earns its place, with no wasted words or under-specification.

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 complexity (scheduling based on energy and readiness), no annotations, 0% schema coverage, and no output schema, the description is partially complete. It explains the core logic and parameter default, but it doesn't cover the output format, how 'readiness score' and 'task list' are obtained or structured, or error conditions. This leaves the agent with gaps in understanding how to invoke and interpret results, though it's adequate for basic usage.

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 meaningful semantics beyond the input schema. The schema has 1 parameter with 0% description coverage, only listing 'target_date' as an ISO date string with a default. The description compensates by explaining that 'target_date' defaults to today and that the schedule is based on 'today's readiness score and the task list,' clarifying the temporal context and implied dependencies. However, it doesn't detail the format or constraints of 'readiness score' or 'task list,' which are not in the schema but are critical inputs.

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: 'Propose an energy-aware daily schedule based on today's readiness score and the task list. High-energy tasks are placed when readiness supports them.' This specifies the verb (propose), resource (daily schedule), and key inputs (readiness score, task list). It distinguishes from siblings like 'calculate_readiness_score' or 'get_tasks' by focusing on scheduling rather than calculation or retrieval. However, it doesn't explicitly contrast with all siblings (e.g., 'get_health_summary' might overlap in energy context).

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 usage context: it should be used when you have a readiness score and task list to create an optimized schedule. However, it doesn't explicitly state when to use this tool versus alternatives (e.g., whether to use 'calculate_readiness_score' first or how it differs from manual scheduling). No exclusions or prerequisites are mentioned, leaving some ambiguity about the required inputs beyond the parameter.

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