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

With no annotations, the description carries the behavioral burden and does substantial work: it discloses the unfiltered market-wide fallback, the enrichment fields per announcement, whether provenance came from a language model or fixed rules, and the pre-payment refusal for empty symbols. It does not describe refresh or pagination behavior, but those are secondary.

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?

Four dense sentences, each earning its place: scope first, modifier behavior second, record enrichment third, edge case and payment guard last. The category list is long but useful for setting caller expectations, and there is no 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?

Without an output schema, the description compensates by explaining what each item contains: filing category, sentiment, one-line summary, and provenance. It also covers the main behavioral branches and a payment-related edge case. It omits details like default limit and exact response shape, but the essential calling context is present.

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 coverage is 100%, so the baseline is 3, and the description adds real value: concrete symbol examples (RELIANCE, TCS), the behavior when symbol is omitted, and the refusal case for symbols with no announcements. The limit parameter is left mostly to the schema's own description.

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 resource: corporate announcements filed with the NSE by Indian listed companies, ordered newest first. The symbol/no-symbol distinction makes the tool's scope precise and distinguishes it from siblings like hsh-india-fundamentals and hsh-company-intelligence.

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?

It gives explicit usage context: providing a symbol returns that company's own record, while omitting one returns the exchange's latest market-wide page. It does not explicitly name alternative tools or state when not to use this one, so it stops short of full when/when-not guidance.

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