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

Annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false and openWorldHint=false, so safety and closed-world scope are covered structurally. The description adds data provenance ('Official NSE index data') and reinforces single-index scope, but says nothing about rate limits, pagination, or how missing/suspended index data is handled. With annotations carrying the behavioral profile, the added value is moderate.

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 what is returned (level series with OHLC and valuation ratios) and the entity scope before moving to examples and routing. Sentences are dense but each carries distinct information: data shape, provenance, examples, and sibling disambiguation.

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?

There is no output schema, but the description states the returned fields (OHLC, PE/PB, dividend yield) and the entity scope, and the input schema fully covers parameters. Given a read-only, single-entity history tool, nothing an agent needs to invoke 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 every parameter is documented in the schema, including the alias relationships (days/range -> interval, index/symbol -> index_name) and the lookback semantics. The description adds no parameter-level detail beyond this, so the baseline of 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?

States a specific verb and resource: retrieve the historical LEVEL series (OHLC + PE/PB/dividend yield) for a single NSE index, with an explicit scope note and concrete examples. It distinguishes itself from get_price_history (stocks only) and get_index_performance (multi-index ranking), so the agent can pick the right tool without opening a 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 use cases ('what did Nifty IT close at on <date>', valuation trend, VIX history) and names two alternatives with the condition that selects them: get_price_history for individual stocks, get_index_performance for comparing multiple indices. This is the when/when-not/alternative pattern at full strength.

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