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

Annotations already mark this read-only/idempotent, but the description adds substantial behavior the annotations cannot: enumerated four-state semantics, the meaning of each state, and the meta.coverage / meta.freshness.lag_days reporting with an instruction to trust answers only up to coverage.answerable_through.

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-loads the core question, then states the return states, then usage, then the honesty constraint. Although long, every sentence earns its place given the non-obvious four-state contract and the bias-avoidance warning.

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, the description fully compensates by enumerating and explaining all four response states plus the coverage/freshness metadata an agent needs to interpret a result. Nothing needed to call or read it correctly is missing.

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 all five params (date, index, symbol, and two symbol aliases) are self-documented, so the schema carries the load. The description adds no date format or alias guidance beyond what the schema already states, so baseline 3 applies.

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?

Opens with a precise verb+resource framing ('Was a stock a constituent of an index on a specific historical date?') and immediately defines the four-state answer, making it unmistakably the point-in-time membership tool rather than price/index history or identifier resolution.

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 ('any was X in the Nifty 50/500 on <date> question', point-in-time universe construction, survivorship-bias-aware backtests) and an explicit anti-pattern ('Do NOT infer historical membership from today's constituent list'), which is exactly the sibling-confusion this tool guards against.

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