correlate_gst_to_stocks

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

With no annotations, the description must carry behavioral disclosure but only offers a conceptual example ('GST from auto sector up 24% YoY → MSIL/Bajaj Auto historically follow in 2-3 months'). It does not describe the calculation method, output format, data freshness, or limitations, leaving significant operational ambiguity.

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 front-loaded with the core purpose and organized with clear sections for sectors and arguments. The example quote adds illustrative value but is slightly redundant; overall, it is concise enough and well-structured without wasted words.

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 single-parameter tool with an output schema, the description covers the purpose, sector list, and parameter usage. It lacks explicit guidance on interpreting the output or handling edge cases, but the output schema can supply return-value details, making the description sufficiently complete for invocation.

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 schema offers no description for 'sector', but the description compensates with an 'Args' section providing examples ('Auto', 'FMCG'), the special value 'all', and a list of supported sectors. This adds meaningful semantics beyond the schema, though it does not specify exact string case or an exhaustive enumeration.

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 'GST collection data → sector performance predictor' and elaborates on the leading indicator concept, listing specific sectors covered. This establishes a distinct purpose compared to generic sector tools, with a clear verb-resource relationship.

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 implies usage by explaining the leading indicator timeframe and sector coverage, but it never explicitly says when to use this tool over alternatives or provides exclusions. No sibling tools are referenced, leaving the agent to infer applicability.

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