generate_detection

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

No annotations provided, so description must disclose behavioral traits (e.g., read-only, side effects). It only states what is generated, not how it behaves (e.g., whether it creates files, requires permissions, or is idempotent). Insufficient for safe tool selection.

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?

Extremely concise: one sentence front-loading the main action ('Generate detection rules and tests') and quickly listing supported types. No redundant words, efficient for an agent to parse.

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?

Despite high schema coverage, the lack of annotations and output schema leaves gaps. The description does not explain return format, whether generation is synchronous, or if additional constraints (e.g., binary required for certain modes) exist. Incomplete for a tool with 5 parameters and no output schema.

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 descriptions cover 100% of parameters with clear definitions (e.g., mode enum). Description adds no new semantic value beyond summarizing modes already listed in schema. Baseline of 3 is appropriate as schema carries the full parameter explanation.

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?

Clearly states the tool generates detection rules and tests for LOL techniques, listing specific types (Sigma, YARA, Sysmon, etc.). Unambiguous and distinct from sibling tools, which focus on other aspects like discovery or analysis.

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 guidance on when to use this tool versus alternatives. It does not mention prerequisites, when not to use it, or context for optimal usage. The description simply lists capabilities without directing the agent.

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