Sector Performance

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It transparently reveals that this is an aggregation over live quotes, what metrics are computed, and that results are sorted best-to-worst. It does not discuss failure modes or data-source caveats, but for a zero-parameter read-only aggregation this is sufficient behavioral transparency.

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?

One sentence with no filler; the action, target, computed fields, and ordering are all front-loaded. Every segment of the sentence adds useful information, and there is no redundancy with schema or annotations.

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 no-argument tool with an output schema present, the description is nearly complete: it states what data is aggregated, what fields are returned, and how the result is sorted. The only minor gap is the absence of explicit guidance about when to select this tool instead of a sibling like market_summary, but this does not prevent correct 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 has zero parameters, so the baseline for this dimension is 4. The description has no parameter explanations, but none are needed because the input schema is empty and additionalProperties is false. The tool is fully invocable with no ambiguity.

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 names a specific operation ('Aggregate live-quote performance per sector') and specifies the exact outputs: advancing/declining counts, average change percent, and ordering from best to worst. This clearly distinguishes it from market-summary or top-movers siblings, which operate at market or symbol level rather than sector level.

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 when to use the tool through 'per sector,' but it never explicitly states when to prefer this over alternatives like market_summary or top_movers, nor does it name any exclusions. The usage context is inferable, not stated.

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