compute_indicator

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

Discloses important constraints (1 MiB cap, flox-py dependency) and implies a read-only compute operation, but does not explicitly state whether it has side effects or error behavior. With no annotations provided, the description bears the full burden.

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?

Four sentences, each adding value: purpose, usage guideline, input cap, dependency. No fluff, well front-loaded.

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 no output schema and simple params, the description covers when to use, constraints, and dependency. However, it omits the return format, which could help an agent interpret results.

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 already describes both parameters (name, data) in detail. The description adds context about extra parameters (window/period/smoothing) but does not enhance semantics of the required params beyond the schema.

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 states the tool runs a single FLOX indicator over a list of floats and returns output, distinguishing it from sibling tools like list_indicators and suggest_indicator.

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?

Explicitly advises using it for sanity-checking indicator behavior on small arrays before strategy integration, especially for indicators with non-obvious parameters. Also notes input cap and optional dependency.

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