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

Without annotations, the description effectively explains key behaviors: maximal patterns (grand cross hides T-squares), orb usage ('worst defining-aspect orb'), and structured output like apex naming. It lacks an explicit statement about read-only nature but covers relevant details.

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?

Two concise sentences front-load the purpose and then detail behavioral nuances with zero wasted words. Every sentence adds essential value.

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 no output schema, the description adequately describes return structure (structured objects with bodies, orb, apex for some). It covers pattern selection rules and geometry. Missing perhaps an example or format spec, but sufficient for understanding.

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 only repeats the need for date, lat, lon already in required fields, adding no new parameter meaning. Parameter details are sufficiently covered by the 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 clearly identifies the tool as providing 'classical aspect configurations' listing specific patterns (T-squares, grand trines, etc.). It distinguishes itself from sibling tools like chart_facts or natal_chart by focusing solely on these pattern definitions.

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 states the tool provides 'pure geometry, no interpretation' implying use when raw pattern data is needed. However, it does not explicitly state when to avoid this tool or mention alternatives among siblings.

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