scan_language_input

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

With no annotations provided, the description carries full burden. It states the tool scans for specific attacks, but does not disclose return format (e.g., boolean, list of findings), side effects, authentication requirements, or rate limits. The 'scan' verb implies read-only behavior but is not explicit.

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?

Single sentence that is front-loaded with the tool's purpose. Efficient and contains no redundant information; every word is necessary.

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 is adequate for a simple scan tool but lacks details about output behavior (no output schema provided). For a tool with only two parameters and no nested objects, the description should ideally describe what the tool returns (findings summary, severity, etc.) to be fully complete.

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%; both parameters ('text' and 'source_name') are documented in the input schema. The description adds no additional meaning about parameter constraints, formats, or usage beyond what the schema provides. Baseline score of 3 is appropriate.

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 scans natural-language input for prompt-injection directives and hidden Unicode attacks, using a specific verb and resource. It distinguishes from siblings like 'scan_code_symbols' and 'scan_unicode_security' by targeting natural-language input with two specific threat types.

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 scanning natural-language input before model ingestion, but does not provide explicit guidance on when to use this tool versus alternatives (e.g., 'scan_unicode_security') or when not to use it. No exclusions or alternative tool references are given.

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