check_control_gaps

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

With no annotations provided, the description carries full burden and does well: it states 'Read-only (does not mutate the model); runs as a polled background job and uses LLM reasoning.' This discloses key behavioral traits like mutation safety, async execution, and probabilistic reasoning.

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 concise and front-loaded: the first sentence states the core purpose, followed by a focused second paragraph clarifying relationship and usage. Every sentence adds value with no fluff 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?

Given the output schema exists, the description needn't detail return values. It covers the tools' read-only nature, background execution, LLM reasoning, and comparison to assess_model. The only minor gap is the lack of any parameter explanation, but overall it is quite complete for a complex tool.

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 input schema describes only 'model_id' (50% coverage), while 'server_version' lacks any description. The tool description does not mention parameters at all, so it fails to compensate for the schema gap. The description adds no meaning beyond what the schema already provides.

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's function: 'Analyze control coverage and surface control objectives that lack sufficient controls.' It also distinguishes itself from the sibling 'assess_model' by explaining it reasons about under-covered COs, making the purpose specific and unique.

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?

Explicit usage guidance is provided: 'Use this to decide what controls to add; use assess_model to score the current state.' It also frames the tool as complementary to assess_model, giving clear when-to-use and when-not-to-use context.

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