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

Annotations already indicate a read-only, idempotent, non-destructive operation, so the bar for additional disclosure is lower. The description adds valuable policy-level behavior: it deliberately excludes grey-market premium, recommendations, price targets, and verdicts. This tells the agent what kind of data it will never receive, which is useful beyond the structured annotations.

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 opening sentence is information-dense and immediately communicates the tool's contents. The following sentences add important exclusions, but the final sentence repeats 'no IPO grey-market premium' and overlaps with the 'apply/avoid verdict' caveat. The message is clear but could be tightened without losing meaning.

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?

Given the read-only annotations and absence of an output schema, the description does a solid job of conveying what data the tool returns and what it intentionally omits. It covers statuses, boards, and content fields, which is enough for an agent to decide whether this tool fits a query. It does not detail return structure or sort semantics, but the enums and the field list mitigate that gap.

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?

Only 33% of parameters have schema descriptions, so the description must compensate. It partially does by mapping 'mainboard and SME' to board, and 'open now, upcoming, closed or already listed' to status. It also mentions subscription figures and post-listing performance, which relate to some sort options like 'subscription' and 'gain'. However, it does not explicitly explain individual parameters such as sort, year, or how they interact.

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 (Indian IPOs) and the scope of data: price band, issue size, lot size, dates, subscription figures, and post-listing performance, across mainboard and SME. It implicitly describes a listing/tracking tool, though it never uses a direct verb like 'fetch' or 'list'. It also distinguishes itself from sources that provide grey-market premiums or apply/avoid verdicts, which helps separate it from related financial tools.

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?

The description explicitly states when this tool is not appropriate: if the user needs grey-market premium or apply/avoid verdicts, this is not the source. It also frames the tool as a factual, recommendation-free IPO tracker, giving clear context for expected use. It does not name sibling alternatives, but no obvious sibling tool covers the same IPO-tracking niche.

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