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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It clearly says the tool runs a query and returns matches, which implies a read operation, but it does not mention side effects, resource consumption, rate limits, or authentication requirements.

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?

Three sentences with an effective front-loaded purpose, a useful example, and a fallback instruction. Every sentence earns its place, and the description is compact without being under-specified.

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 high schema coverage, the presence of an output schema, and the example query, the description is largely complete. It could be improved by noting that this runs an ad-hoc scan versus saving one, but that is a nice-to-have rather than a correctness 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?

Schema description coverage is 100%, so the schema already documents all four parameters. The description adds value beyond the schema by showing an example Sift expression for the required source parameter, which clarifies the expected query syntax beyond a generic parameter 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 opens with a specific verb and resource: "Run a Sift screener query against NSE equities and return the matches." This makes the tool's role immediately clear and implicitly distinguishes it from siblings like save_scan, list_saved_scans, and get_bars.

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 provides a concrete Sift query example and explicitly tells the agent to call sift_reference first if unsure of the syntax. It does not, however, state when not to use this tool or contrast it directly with save_scan/list_saved_scans.

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