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

Annotations already declare readOnly, idempotent, non-destructive, closed-world, so safety is covered. The description usefully adds the credit cost (10 credits, Tier 1) and confirmed required inputs, but says nothing about output shape or any operational constraints beyond cost.

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?

It is short and the bracketed metadata is well-structured and front-loaded. However, the single content sentence is pure tautology and the rest is boilerplate, so brevity here reflects under-specification rather than efficiency.

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 16-parameter specialized astrology endpoint, the description omits what the tree output represents and how the optional flags modify it. An output schema exists so return values needn't be explained, but the operational and semantic gaps remain too large.

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 description coverage is only 31% across 16 parameters, so the description must compensate and does not. It merely echoes the four required fields already in the schema and ignores ambiguous params like withTnp, cosmogram, and name entirely.

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 core sentence 'Tree per personal point' essentially restates the title 'Personal Point Tree' without stating what the tool actually computes or returns. The bracketed metadata gives group and endpoint but never defines what a 'personal point tree' is or how it differs from siblings like sensitive_points or midpoint_pictures.

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 [Required] line lists the inputs but gives no when-to-use context, no prerequisites, and no distinction from the many sibling cosmobiology tools. An agent is left to guess which of the 40+ siblings is appropriate.

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