correlate_gst_to_stocks

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

With no annotations, the description carries full burden. It discloses the data source (Finance Ministry, public) and leading indicator behavior, but does not explicitly confirm it is read-only or describe any limitations like data freshness or accuracy.

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 succinct, with no wasted words. It front-loads the core concept, provides an example, and clearly separates sections for sectors and args.

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 presence of an output schema (so return values need not be described) and only one parameter, the description covers the tool's purpose, usage, and sector scope adequately. Minor gaps include lack of detail on the prediction methodology or confidence intervals.

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 parameter 'sector' lacks schema descriptions (0% coverage), but the description compensates by listing valid sector values (Auto, FMCG, etc.) and explaining the 'all' option for a full report. This adds significant meaning beyond the schema's default.

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 states the tool correlates GST data to sector performance as a leading indicator, with a concrete example ('GST from auto sector up 24% YoY → MSIL/Bajaj Auto historically follow in 2-3 months'). It distinguishes itself from sibling tools like sector_performance by specifying its predictive 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?

The description explains when to use the tool (for leading indicators based on GST data) and lists covered sectors. However, it does not explicitly state when not to use it or mention alternative tools, leaving some ambiguity.

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