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

The description adds value beyond the annotations by explaining that on a quiet day it may return a clearly labelled historical replay, and it lists the exact return fields (headline, dek, Markdown, evidence clock, generation mode, receipt). This discloses fallback behavior and output contents, exceeding what the readOnly/idempotent hints convey.

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, front-loaded with the primary function and immediately followed by usage guidance and return details. Every clause adds value, with no redundancy or 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?

Given zero parameters and an existing output schema, the description covers purpose, usage, and behavioral nuances thoroughly. It explains the fallback replay mode and the return fields, leaving no significant gaps for an agent to misuse the tool.

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?

There are zero parameters, so the description is not expected to explain parameter details. The baseline of 4 applies because the schema is trivially satisfied (no parameters to document), and the description still clarifies the tool's fixed operation.

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 it returns the exact full-text Seiche editorial published today, with specific fields like headline, dek, Markdown, etc. It directly addresses 'what did Seiche write today?' and distinguishes itself by focusing on the canonical latest article without regeneration, differentiating it from sibling tools that handle other data or stress records.

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 provides explicit usage context ('Use this for what did Seiche write today? and quote it without regenerating facts'), giving a clear when-to-use. However, it does not explicitly mention alternatives or when not to use, though no sibling tool appears to serve the same purpose, so the guidance is adequate.

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