check_redundancy

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

The description goes beyond annotations by detailing heuristic rules (phase-1, high-precision), specific patterns checked, and the conservative design. It also discloses input limitations (100k chars) and that absence of flags does not guarantee tight prose, adding valuable behavioral context not captured in readOnlyHint or idempotentHint.

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?

The description is well-structured with bullet points and clear categories, making it easy to scan. Every sentence provides essential information without unnecessary verbosity, including examples and limitations.

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 the presence of an output schema (not shown but noted), the description covers all necessary aspects: purpose, specific rules, conservative design, input constraints, and what results mean. It is comprehensive for the tool's complexity.

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 sole parameter 'text' has a clear description in the schema ('Estonian text to check for pleonasm / redundant word pairs'), which is consistent with the tool's purpose. The main description provides additional context about what the check looks for, but the schema already covers 100% of parameters, so the added value is moderate.

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 checks Estonian pleonasm/semantic-doubling, provides specific examples (doubled 'also' particles, double superlative, fixed pleonasm phrases), and distinguishes itself from sibling tools like spell_check by focusing on a specific class of AI-produced redundancy.

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 explains it is conservative and high-precision, noting that absence of flags is not proof of tight prose, which guides appropriate use. It mentions the input cap of 100,000 characters. However, it does not explicitly compare with sibling tools or provide when-not-to-use scenarios, missing some contextual guidance.

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