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

Annotations already cover read-only, idempotent, non-destructive, closed-world, but the description adds traits they do not carry: deterministic output, 'mean, without nutation' (a substantive modeling choice), the credit cost and 10-call block billing, and that failed calls are free and sandbox keys return a fixed sample. That is genuine behavioral value beyond structured fields.

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?

Front-loaded with what is returned, then cost, determinism, and a concrete example. Four short lines, each carrying distinct information; no filler or restatement of the title.

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?

An output schema exists, so return formatting need not be explained. The description covers scope, supported systems, input format, determinism, cost, and error behavior. The only real gap is sibling differentiation — nothing tells the agent when ayanamsa is the right ephemeris call versus angles or positions.

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% — the single datetime parameter already documents ISO 8601 with Z/offset, the accepted UTC range, and the invalid_datetime refusal. The description's example argument only illustrates the format the schema already defines, so it earns the baseline 3 rather than more.

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?

States the resource precisely — ayanamsa values — and enumerates the four supported systems (Lahiri, Raman, Krishnamurti, Fagan–Bradley) with the qualifying 'mean, without nutation'. However, it never differentiates itself from the other ephemeris siblings (get_ephemeris_angles, get_ephemeris_positions, get_ephemeris_series), so an agent must infer which one it wants.

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?

Usage is implied by the name and the listed systems, but there is no explicit when-to-use or when-not-to-use statement relative to the other ephemeris tools, and no exclusions. The billing/sandbox note is operational context rather than selection guidance.

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