find_text

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

No annotations provided, so description carries behavioral burden. It discloses ranking behavior (article/main over nav/header/footer) and return format, but does not confirm read-only nature or mention any state changes. Adequate but not comprehensive.

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, clear sentence that efficiently conveys return structure and ranking behavior. No unnecessary words or redundancy.

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?

No output schema, but description defines return structure and ranking. Combined with 100% parameter coverage, the tool is well-documented for its purpose. Lacks usage examples but sufficient for basic understanding.

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?

Input schema has 100% coverage with parameter descriptions. The tool description adds no additional parameter semantics beyond what is in the schema, maintaining the baseline score.

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 finds localized text matches and specifies the return format with fields like ref, tag, attrs, etc. It distinguishes from sibling tools like 'text' or 'text_around' by focusing on substring search rather than full text extraction.

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?

No explicit guidance on when to use this tool versus alternatives like 'text_main' or 'text_clean'. The mention of ranking article content above boilerplate implies usage context but does not state exclusions or conditions.

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