chainvectorFundingSqueeze

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

No annotations are provided, so the description carries the full transparency burden. It explains the meaning of the scores and direction, which is useful, but it does not disclose whether it is a read-only operation, data freshness, or any other behavioral traits.

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 two sentences that are direct and informative. It front-loads the tool's identity and includes the key output details and an interpretation hint, with no redundant text.

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 parameter, no output schema), the description covers the main return fields and offers a practical interpretation. It could be more complete by listing all expected output fields or linking to related tools, but it is sufficient for a basic gauge.

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 for the only parameter (symbol) is 100%, so the schema already fully documents the parameter. The description adds no additional parameter semantics, which aligns with the baseline for high schema coverage.

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 identifies the tool as a 'funding-squeeze gauge' and specifies the key outputs (aggregate_score, crowded side, squeeze_direction). This distinguishes it from sibling tools like chainvectorFundingCurrent or chainvectorCascadeRisk by focusing specifically on the squeeze metric.

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 implies usage for gauging funding-squeeze conditions and offers an interpretive rule ('High score + confirming cascade risk = the unwind has started'), but it does not explicitly state when to prefer this tool over related siblings such as chainvectorCascadeRisk or chainvectorStrategySqueeze.

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