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

Without annotations, the description fully discloses the tool's behavior: it samples the window, scores by closeness and applying aspects, optionally penalizes void-of-course Moon, and returns top moments with matched aspects. No side effects are expected, and the disclosure is sufficient for an agent to understand implications.

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 concise (4 sentences) and well-structured: it starts with the purpose, explains the mechanism, notes the return value, and ends with a crucial limitation. Every sentence serves a purpose without redundancy.

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 of electional search and the absence of an output schema, the description adequately explains the return format (top moments with matched aspects) and the sampling step (step_hours). It also warns about angle aspects, making the tool's use context complete for an agent.

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 meaning beyond the input schema by explaining that 'wanted' aspects must be body-to-body, and that scoring favors tighter and applying aspects. This contextualizes the parameters, especially the 'wanted' array, and clarifies the tool's scope beyond the schema's field descriptions.

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 ranks moments in a time window for electional purposes, sampling and scoring by aspect satisfaction. It distinguishes itself from sibling tools like 'find_aspect_dates' (which finds exact dates) and 'void_of_course' (which detects void Moon only), as it combines multiple criteria for electional selection.

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 explicitly notes that this tool handles body-to-body aspects only, directing users to compute charts for angle aspects separately. However, it does not explicitly contrast with other electional-related tools like 'aspect_patterns' or 'chart_signature', leaving some ambiguity about when to prefer this over them.

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