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

Annotations already declare readOnlyHint, idempotentHint, openWorldHint and destructiveHint=false, so safety is covered. The description adds genuinely useful behavioral context beyond that: the data is live from the database, null parts mean 'could not be loaded', and every UTC time has a pre-converted Eastern twin to quote. It stops short of describing the response shape or any freshness/staleness caveat.

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 the tool returns, followed by use cases and then quoting rules; every sentence carries an instruction the agent needs. It runs long in a single block and the enumeration of use cases could be tightened, but nothing is padding.

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?

With no output schema and zero parameters, the description carries the burden of explaining returns, and it does so at a high level (prices, plans, dates, topics, next show time, Eastern conversions). It does not enumerate the full result shape, so an agent learns the fields only after the first call, but the null and timezone conventions prevent the most likely mistakes.

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?

The tool takes no parameters, so the baseline is 4. The description adds no parameter semantics because there are none to add, but it does name two output fields (scheduledAtEastern, endDateEastern), which is a small bonus rather than a parameter concern.

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 verb and resource: 'Live facts about the AI Trading Bootcamp and the free live challenge show, read from the database.' It enumerates exactly which fields the result covers (price, payment plans, curriculum, dates, next show date/time), so an agent can distinguish it from the trading/backtest/portfolio siblings without opening any schema.

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?

Gives explicit triggers: user asks about the Bootcamp, price, plans, curriculum or dates, about the free live challenge or show's next date/time, or a new/stuck user asking how to learn AI trading. It also supplies operating constraints — quote only from this result, never guess nulls, quote the Eastern-converted times — leaving little to inference.

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