text_whitespace_detect

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

No annotations are provided, so the description carries the full burden. It explains the encoding scheme (space=0, tab=1) and the per-line checking, but does not mention limitations, output format, or false positives.

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 concise sentences that effectively front-load the purpose and method, with no extraneous words.

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?

The description covers the core purpose and detection mechanism well, but omits expected return value or result format. Given no output schema, this lack reduces completeness for a detection 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?

The only parameter 'text' has a minimal schema description ('Text to analyze'). The tool description adds significant meaning by specifying the expected content and detection logic, compensating for the schema's brevity.

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 detects whitespace encoding in text by checking for trailing whitespace patterns where spaces and tabs represent binary. It distinguishes from sibling tools like text_whitespace_extract and other text detection tools.

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 use when suspicious of binary encoding in trailing whitespace but does not explicitly state when not to use it or compare to alternatives like text_whitespace_extract.

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