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

Annotations cover safety (readOnly, idempotent, non-destructive), and the description adds behavior they cannot: it reuses captured source numbers and selection rather than recalculating, expired evidence requires an explicit new read, and displayed probabilities are not calibrated confidence. Those are the details an agent needs to avoid misusing the output.

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?

Front-loaded with what the tool displays and its dependency, and every sentence carries a constraint or caveat. Slightly dense with a listy negative clause ('not a data fetch, calculation, navigation hub'), but nothing is padding.

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?

Output schema and annotations already carry return shape and safety profile; the description supplies the remaining agent-critical context: prerequisite evidence, expiry/re-read behavior, and interpretation caveats. Nothing needed to call it correctly is missing.

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 coverage is 100% and the single evidence_id parameter is already documented as the exact evidence.id from the matching data tool with a 64-hex pattern. The description reinforces reuse and expiry but adds no syntax or sourcing detail beyond the schema, so baseline 3 applies.

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?

States a specific verb (Display) and resource (market regime and volatility widget) and names the sibling data tool whose evidence it depends on, research_market_context. An agent can distinguish it from the raw data tool without opening the schema.

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?

Gives an explicit trigger ('after evidence from research_market_context is available'), an explicit conditional ('Use only when a visual helps answer the question'), and explicit exclusions ('Not a data fetch, calculation, navigation hub or replacement for the assistant's interpretation'). This is about as complete as a when/when-not statement gets.

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