get_market_sentiment

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

Annotations already indicate readOnlyHint, destructiveHint, and idempotentHint. The description adds behavioral context: it combines specific data sources (FinBERT and institutional movements) and returns a structured index and breakdown, providing transparency beyond annotations.

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 very concise with two sentences, front-loading the action and result. Every part is informative and not redundant.

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 tool's simplicity (one optional parameter, no output schema), the description provides complete context: what it does, what it returns, and how it compares to a sibling. No gaps for this complexity level.

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?

With 100% schema description coverage for the single parameter 'market', the baseline is 3. The description does not add extra semantic meaning beyond what the schema already provides (market: TW or US).

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's purpose: to get market sentiment analysis using FinBERT news sentiment and institutional movements, returning a sentiment index (0-100) and breakdown by source. It also distinguishes itself from the sibling 'analyze_sentiment' by claiming higher accuracy.

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 explicitly compares this tool to 'analyze_sentiment', suggesting it is more accurate, which guides when to use it over that alternative. However, it does not mention other potential alternatives or exclusions, but the context is clear.

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