security.generate_test_plan

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

With no annotations, the description carries the full burden. It adds meaningful behavioral context by stating the output is 'deterministic' and intended for execution, which goes beyond the tool name. However, it does not disclose return format, whether the plan is returned as text or written to a file, side effects, or prerequisites, leaving notable gaps.

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, front-loaded sentence with no filler. It states the core function, input, and output audience efficiently, and every phrase adds information.

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 one parameter, no output schema, and no annotations, the description is adequate but incomplete. It does not explain what the generated test plan looks like, how it is delivered to the caller, or how it relates to sibling tools like security.scan_source. An agent would need additional inference to know the return contract or necessary prior steps.

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 description coverage is 0%, so the description must compensate. It links reportPath to 'a source-scan report', which gives the parameter some semantic grounding beyond a bare string. But it does not describe the expected path format, file type, or whether the report must be a specific scan output, so compensation is only partial.

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 uses a specific verb ('generate') and resource ('a deterministic mobile security test plan'), and clearly identifies the input ('from a source-scan report') and audience ('for an AI or engineer to execute'). It is unambiguous about what the tool does, but it does not explicitly contrast with sibling tools like flow.generate_test_scenarios, so it stops short of full sibling differentiation.

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 implies when to use the tool: when you have a source-scan report and want a test plan. However, it provides no explicit guidance on when not to use it, no alternatives, and no mention of prerequisites such as running security.scan_source first. The usage context is inferable but not spelled out.

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