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

Annotations already declare read-only, idempotent, and non-destructive behavior. The description adds meaningful behavioral detail: it reports delta and z-score, uses trailing-window mean/stddev, and always states the exact window (start date, end date, n observations). 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?

Two sentences, front-loaded with the core comparison and output, then input modes and window-reporting behavior. Every sentence earns its place with no filler.

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?

With no output schema, the description explains the key outputs (delta, z-score, window) and input modes. It could be more explicit about the exact response shape or how to interpret the z-score, but it is sufficient for an agent to call and understand 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?

Schema coverage is 100%, so the schema already documents all six parameters. The description adds value by explaining the two input modes, the tri-party overnight default, and that a mnemonic overrides structured args, which helps an agent choose the right parameters.

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 names a specific operation (compares latest observation to a trailing window and reports delta and z-score), identifies the resource (repo or MMF series), and frames it as anomaly detection. It also references sibling tools like ofr_repo_rates and ofr_search_funding_series, making its distinct niche clear.

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 explains the two invocation modes: structured args like ofr_repo_rates or a raw mnemonic from the search/holdings tools. It does not explicitly state when not to use it versus those siblings, but the anomaly-detection framing and explicit sibling references make the intended context clear.

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