text_cleanup

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

With no annotations, the description discloses key behavioral traits: operations are chained in sequence (order matters), and it specifies the return value (cleaned text plus per-operation stats). It also explains normalization behaviors (e.g., curly → straight quotes). This goes beyond a basic functional statement, though it does not cover edge cases or error handling.

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 main purpose. The operation list is compact and the return behavior is included. No filler or repetition.

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 no annotations, the description covers the essential usage (operations, sequence, return format). It does not mention error behavior, but the schema's enum prevents invalid inputs. The tool is a straightforward transformation, so this level of detail is sufficient for an agent to invoke 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 0%, so the description must compensate. It lists and explains the operations (e.g., normalize_quotes maps curly to straight) and clarifies the chaining semantics, adding value beyond the raw schema enums. The 'text' parameter is only referenced by name, but its purpose is evident from the tool's purpose.

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 uses a specific verb ('Apply') and resource ('text cleanup operations') and clearly defines the scope via the enumerated operation list. It distinguishes itself from sibling text tools like case_convert or sort_lines by emphasizing chained, sequential execution.

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 usage for multi-step text cleaning tasks ('Apply chained text cleanup operations in sequence') but does not explicitly state when to prefer this over alternatives like slugify or text_diff, nor does it mention exclusions or prerequisites. The context is clear but not fully explicit.

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