analyze_for_testing

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

No annotations are provided, so the description bears full responsibility. It discloses that the tool performs analysis, can fetch live data from ServiceNow, and returns various metrics. Since it is a read-only analysis, side effects are not expected, and no contradictions are present. It could mention that connectivity is needed for mode B.

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 well-structured: a clear first sentence for purpose, followed by bullet points for input modes and returns. It is front-loaded and contains no unnecessary words.

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 no annotations and no output schema, the description covers inputs, outputs, and usage order adequately. It lacks details on error handling, prerequisites for mode B, or behavior if both modes are supplied, but it is sufficient for an AI to understand how to use the 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?

Schema description coverage is 100%, so the baseline is 3. The description adds significant value by explaining the two modes (code vs. artifact_type+name/sys_id) and how each parameter is used, which goes beyond the schema descriptions.

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 purpose: deep-analyze a ServiceNow artifact to understand testing needs. It distinguishes itself from sibling tools like analyze_dependencies and analyze_flow by focusing specifically on testing analysis. The input modes and return fields are explicitly listed.

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 says 'Always call this FIRST before create_test_plan', providing a strong usage guideline. It also describes two input modes. However, it does not explicitly mention when not to use the tool or suggest alternatives among the many sibling tools.

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