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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint, but the description adds substantial behavioral context beyond those: it specifies the algorithm (Damerau-Levenshtein distance ≤ 2), the curated corpus, the false-positive reduction, and the exact return fields (is_likely_typosquat, closest_match, distance, risk_level). This is rich behavioral disclosure that goes beyond the structured annotations.

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 a single, well-structured paragraph that front-loads purpose and usage, then covers parameters, algorithm, return fields, and fallback. It is somewhat long due to the detailed algorithm explanation and the report_feedback instruction, but every sentence contributes to the agent's understanding. It's not overly verbose; it earns its length.

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?

For a tool with two parameters and an output schema, the description covers all essential aspects: purpose, usage boundaries, algorithm details, return values, and the fallback feedback mechanism. An agent can correctly invoke it and interpret results without additional information. Nothing critical is missing.

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 schema provides 100% description coverage for both parameters (package_name and ecosystem) with clear descriptions and defaults. The description essentially restates the parameter information without adding new semantics. Baseline 3 is appropriate because the schema already does the heavy lifting; the description adds no extra meaning.

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 typosquatting, specifically optimized for the top 500 frontend packages, and explicitly contrasts with a full npm scan. It names the sibling security_detect_typosquatting for backend packages, making the distinction unambiguous. The purpose is concrete and actionable.

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 explicitly states when to use this tool (frontend packages) and when to use the alternative (backend packages, pointing to security_detect_typosquatting). It also provides the fallback instruction to report feedback if the tool doesn't serve the user's need. This is explicit guidance with clear alternatives and conditions.

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