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

The description adds useful behavior beyond the annotations: it fetches history for every instrument in the universe Choose a JSON code block with all scores and justifications. and is therefore slow;; this is meaningful operational context. The annotations already cover read-only, idempotent, and non-destructive behavior, so the description's performance disclosure is a valuable supplement. No contradiction with 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 three sentences long and every sentence earns its place: purpose, use case, and performance guidance. It is front-loaded with the primary action and includes the most important operational caveat without wasting 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?

The description covers the purpose, use case, and major performance characteristic, andthe schema fills in most parameter details. However, there is no output schema, and the description does not state what the tool returns (e.g., matching symbols, values, or matched rule details). This leaves some context missing for an agent that needs to handle the result.

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 already covers 78% of parameters, including enums and defaultsconstant. The description adds conceptual context for how rules work (price fields, indicators, formulas, ALL/ANY matching), which helps an agent understand the rule structure. However, it does not go much beyond the schema's own parameter descriptions.

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 states a specific operation: scan the venue's listed instruments for ones matching conditions, explicitly contrasting with looking at the open chart. It also gives a memorable use case ('which coins are doing X right now'). It does not name sibling tools like screener_backtest, but the resource and action are clear enough to distinguish from chart-oriented tools.

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 clearly identifies when to use this tool: when scanning for instruments matching conditions across the universe. It also warns that the operation is slow and recommends asking once with the right conditions rather than repeatedly. It does not explicitly mention when not to use it or alternatives, but the guidance is practical and context-rich.

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