tunnel_query_length

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

With no annotations provided, the description carries the full burden of explaining behavior. It discloses the measurement logic and thresholds but does not describe the output format, return type, or any side effects. Since this is a detection tool, the agent is left uncertain whether it returns a score, boolean, or structured metrics.

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?

Three sentences, no filler, and the core action is front-loaded. Each sentence earns its place: it states what it measures, provides normal baselines, and explains anomalous thresholds. This is highly efficient.

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 tool has a simple interface (one required array param, no output schema), and the description covers the detection logic well. However, it does not describe what the tool returns or how to interpret the results operationally, which leaves a gap for an agent needing to act on the outcome. It also doesn't mention any relationship to the many sibling tunnel detection tools.

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 already covers the single parameter 'queries' with a clear description, so the baseline is 3. The tool description adds interpretive value by explaining what length patterns will be considered abnormal, directly enriching the meaning of the parameter beyond the schema's generic 'analyze for abnormal length patterns.' This justifies a 4.

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 opens with a specific verb ('Measures') and identifies the exact resource ('subdomain label lengths and total query length') with a clear purpose ('to detect DNS tunneling'). This distinguishes it from sibling tools like tunnel_entropy_analysis or tunnel_txt_payload, which focus on other DNS tunneling indicators.

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 provides concrete detection criteria (normal browsing rarely exceeds 3 labels or 60 total characters; tunneling often uses labels >40 chars and totals >200 chars), giving the agent clear context on when results are suspicious. However, it does not explicitly mention alternative tools or when not to use this tool, so it stops short of full usage guidance.

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