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 does not contradict them. Beyond annotations, it discloses behavioral constraints: range capped at 60 days, natal reference computed once, per-day snapshot contents enumerated, and no scoring/'best date' selection. It could have added rate-limit or pagination details, but the disclosed behavior is substantive.

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 a solid paragraph, front-loaded with the core purpose and most decision-relevant detail. The list of included data is long but largely earned because it tells the AI what's available for reasoning. A slight reduction could be made by skipping some enumerations, but the structure is clear and purposeful.

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 complex tool returning bulk per-day data with no output schema, the description explains the input, the safety profile (via annotations), the range cap, the optional enrichment behavior, and how this differs from the rule-based alternative. It does not detail the exact output JSON shape, but the enumerated contents give a solid mental model of what is returned.

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 100%, and the input schema thoroughly explains every parameter such as date, time, place, gender, include, and coordinates. The description does not repeat parameter docs, but it does tell the agent that the range is capped at 60 days (relevant to from_date/to_date) and that 'include' defaults to all enrichment sections. Baseline 3 applies because the schema already does the heavy lifting.

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 names a specific verb and resource ('Raw transit details for EVERY day in a date range') and distinguishes it from the closest sibling by naming get_muhurta and get_gochara. It clearly states the unique value: one-call bulk retrieval for an 'AI decides' flow, with no scoring.

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?

Explicitly states when to use: when the AI should reason over raw per-day data and decide for itself. It also names the alternative tool (get_muhurta) and the condition to choose it ('if you want the system to rank dates by rules'). This is the model example of usage guidance.

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