chainvectorOrderbookImbalance

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

With no annotations provided, the description carries the burden of behavioral disclosure. It specifies the output scale, sign convention, units (bps for microprice tilt), and adds an interpretive rule. It does not cover response structure or update cadence, but the core semantics are well explained.

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?

Two sentences effectively front-load the definition and provide interpretation without redundancy. No filler words, and the structure is easy to scan.

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 metric's meaning, range, and decision relevance, and the schema documents all parameters. Missing an explicit statement of return type, but given the simple metric and no output schema, the information is mostly sufficient.

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?

All three parameters have schema descriptions (100% coverage), so the baseline is 3. The description's mention of '5/10/20 levels' aligns with the depths parameter default but does not add semantic detail beyond what the schema already provides.

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 identifies the specific metric (order-book depth imbalance) and adds distinguishing details: level counts (5/10/20), value range [-1, +1], polarity (+ = bid-heavy), and a microprice tilt in bps. This clearly differentiates it from sibling chainvectorOrderbookWalls and chainvectorOrderflowCvd.

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 second sentence explicitly frames the tool's relevance to trading decisions: a book leaning against a candidate trade is a warning, leaning with it is confirmation. This gives clear context for when to apply the metric, though no explicit alternatives or exclusions are mentioned.

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