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

Annotations already mark the tool as read-only, idempotent, and non-destructive, and the description adds valuable behavior beyond that: it discloses that full-sentence inputs are rejected upstream and surface as MCP INTERNAL_ERROR at the tool layer. It also clarifies that PrashnaInput locally enforces date/time/lat/lon/ayanamsa patterns and points to the full error contract, giving agents a realistic model of failure 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 description is structured with clear, purposeful sections: summary, workflow, input contract, and sibling disambiguation. Each sentence carries operational value, and the most important scoping and validation details are front-loaded before the disambiguation notes and documentation link.

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 a nested input object, a required enumerated question set, multiple validation patterns, and an output schema available, the description covers the full calling contract: what to pass, what values are allowed, what validation happens where, what will be returned, and where to find the full error contract. Nothing essential is missing for correct invocation.

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?

Although the schema documents patterns, ranges, and enums, it only defines 'question' as a minLength-1 string. The description adds the critical semantic constraint that question must be exactly one of the listed topics, and warns that full sentences are not validated locally. This materially changes how an agent should construct the call and compensates for the schema's weak question typing.

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 opens with a specific verb and resource: 'Casts a Prashna chart for the query instant using supplied date, time, place, and a single-topic keyword', and names the concrete outputs: houses, Moon diagnostics, verdict, and cusps. It clearly differentiates from sibling tools by naming asterwise_get_natal_chart and asterwise_get_kp_chart and explaining what each alternative requires.

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 'DO NOT CONFUSE WITH' section explicitly identifies when not to use this tool and what alternatives to choose instead, contrasting query-moment prashna with birth-data-based natal charts. The 'WORKFLOW' section confirms this is standalone for horary with no prerequisites or follow-ups, leaving no ambiguity about invocation context.

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