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

Annotations already declare readOnly, idempotent, and non-destructive, but the description adds genuinely non-redundant context: it clarifies that despite the 'is-' prefix this is a transformation, not a boolean validator, and that output is de-ANSI'd text rather than parsed log entries. That guards against a real mis-use the annotations alone would not prevent.

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 short sentences, front-loaded with the action, then usage, then the exclusion, then the output contract. Every sentence carries distinct information with no repetition of the title.

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?

For a single-parameter pure transformation with no output schema, the description covers action, usage, boundary against a sibling, nature of the operation, and shape of the result. An agent has everything needed to call it correctly.

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 description coverage is 100%, so the single 'text' parameter is already documented in the schema, and the baseline is 3. The description adds no syntax or format detail (e.g., the 4096 max length) beyond what the schema provides, only a boundary statement about not parsing entries.

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?

States a specific verb+resource ('Strip ANSI escape sequences') and explicitly disambiguates from a sibling ('For structured datasets, use is-dataset-minify instead'). The agent can distinguish this from the many is-* validator siblings without opening any schema.

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?

Gives an explicit use case ('turning colorized terminal logs into clean text for indexing or display') and names the alternative tool with the condition that selects it. Nothing about when to reach for this vs. alternatives is left to inference.

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