Get Premarket Scanner

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

Beyond the readOnlyHint annotation, the description discloses many important behaviors: off-hours fallback to the last session, the distinct liveRvol vs premarketPaceRatio semantics and their time-skew caveat, null values outside the premarket window until baseline is warm, and the low-float board returning empty rows with meta.reason as a normal state. It even warns the two live metrics are DIFFERENT quantities and must not be substituted for each other or for rvol.

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 long but densely packed and well structured: purpose first, then usage, then parameter-specific guidance, then the nuanced live-volume metrics, then the low-float board behavior. Every sentence carries operational information an agent needs to avoid misusing the tool, especially the distinction between liveRvol and premarketPaceRatio. No filler or tautology.

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 complexity, the description is complete: it explains the board's contents, fallback behavior, parameter effects, cache behavior, empty-result semantics, output fields like liveRvolAsOf and meta.asOf, and pricing implications. The existence of an output schema covers return structures, and the description still provides the key interpretive context needed to call the tool correctly.

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 all three parameters at 100%, so the baseline is 3. The description adds meaningful semantics beyond the schema: includePennyStocks uses a separate cache slot, universe='lowfloat' is served from the aggregator snapshot and may return empty rows with meta.reason, and sort is ignored for universe='default'. This gives the agent a richer understanding of parameter behavior than the schema alone.

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 verb and resource: 'Get the live premarket scanner board — the top premarket gainers and losers by absolute gap %'. It also details what each row contains (rvol, marketCap, short interest, etc.), making the tool's function unmistakable. The word 'live' and the board-oriented framing distinguish it from sibling tools like get_premarket_scan_history.

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?

It explicitly says 'Use for premarket small-cap runner discovery' and explains when special settings apply, such as includePennyStocks for sub-$1 names and universe='lowfloat' for the low-float board. It also notes the off-hours fallback behavior and that an empty low-float board is a normal state, giving clear operating context. It does not explicitly name alternatives or when-not-to-use cases, but the usage guidance is strong.

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