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

Annotations already declare readOnlyHint=true and openWorldHint=false, so safety is covered. The description adds meaningful behavioral context beyond that: the statistical scope (hit rate, median and mean miss), segmentation (mainboard vs SME, by period), an additional analytical dimension (whether gains held after listing), and recency coverage (latest IPOs). It does not discuss data refresh cadence, which is the main remaining gap.

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?

Content is front-loaded with the core claim (GMP vs actual listing gain, since 2023) before the enumerated breakdowns. It is a single dense sentence whose list is slightly run-on, but every clause carries informational weight rather than 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?

With no parameters and no output schema, the description must convey what comes back — and it does, enumerating the precise metrics and segmentations in the report. An agent knows the scope (Indian IPOs since 2023), the sample size, and the analytical axes before calling.

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?

The tool takes zero parameters, so there is no parameter semantics to document; baseline is 4. The description correctly implies a single fixed analytical report with no filtering options, so an agent will not hunt for missing arguments.

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 states a concrete analytical purpose: measuring how well the last pre-listing GMP predicted actual listing gains across 1,200+ Indian IPOs since 2023, including named breakdowns (hit rate, median/mean miss, mainboard vs SME). It is clearly not a quote or listing tool like its siblings, though it never names those siblings to sharpen the distinction explicitly.

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?

Usage is only implied — an agent can infer this is the tool for evaluating GMP reliability rather than fetching a current GMP value. There is no explicit 'use this when…' statement, no exclusion, and no pointer to get_ipo_gmp_today for live quotes or get_upcoming_ipos for forward-looking data.

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