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

Annotations already declare readOnlyHint, idempotentHint, and non-destructive behavior. The description adds meaningful behavioral context beyond that: it states the data is factual only and explicitly excludes buy/sell recommendations, price targets, and IPO grey-market premium, setting expectations about what the tool will not return.

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 well-structured and front-loaded: the core data scope comes first, followed by concrete use cases, then a factual boundary. Every sentence adds distinct value with no redundancy or filler.

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 simple one-parameter, read-only tool with appropriate annotations, the description is complete: it names the returned data categories, gives usage contexts, and clarifies limitations. No output schema exists, but the description sufficiently enumerates what the agent can expect.

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?

With 100% schema description coverage for the single 'company' parameter, the schema already explains that a slug, NSE symbol, or UUID is accepted. The description adds only the 'one company' scope, which is already implied by the tool name and input schema, so no significant extra parameter semantics are provided.

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 clearly identifies the tool as returning latest fundamentals and valuation for a single company, enumerating the specific data points (price, market cap, P/E, P/B, revenue, profit, growth, ROCE/ROE, debt ratios). It distinguishes itself from broader siblings like run_screener or results_calendar by emphasizing 'one company' and the snapshot nature.

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?

Explicit usage guidance is provided: use for 'how is X doing', 'what does X trade at', or as the numeric backdrop before reading filings. It does not explicitly name alternatives to avoid, but the use cases are concrete enough for an agent to route correctly.

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