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

With no annotations, the description carries the full behavioral burden. It usefully discloses that output is deterministic and not LLM-narrated, and that it shares a compute path with POST /api/b2b/forecast. It does not state read-only status, authorization needs, rate limits, or error behavior.

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 purpose is front-loaded and the sentences are dense but mostly purposeful, moving from output summary to parameter conditions to engine behavior. The final API-path sentence may be extraneous for agent use, and the em-dash list is slightly choppy, but overall it is efficiently sized.

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 six-parameter tool with a nested required birth_data object, no output schema, and no annotations, the description is only partially complete. It names some return components but does not fully describe the forecast output shape, and it omits guidance on alternatives or failure modes.

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 only 50%, but the description compensates well for the key conditional parameters: it explains that date applies to daily, year+month to monthly, year to yearly, and that lang defaults to en. This adds meaning beyond the raw enum and schema descriptions, though nested birth_data fields remain undocumented in prose.

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 a specific resource and its scope: a structured personalized forecast from birth data, with named output elements (per-area tones, day calendar, ingresses, dasha standing). It is clear what the tool does, but it does not explicitly differentiate itself from siblings like get_dasha despite mentioning dasha standing as an output component.

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 by specifying deterministic engine output and no LLM narration, which helps distinguish it from a conversational sibling like ask_jyotish. However, it never states when to prefer this tool over alternatives such as get_dasha or get_panchang, nor any prerequisites or exclusions.

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