analyze_cross_component_impact

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. The description does mention that this runs Claude CLI against RMS and MIP codebases, which is a nontrivial behavioral detail (external process execution) that an agent would want to know. However, it doesn't disclose side effects (if any), cost/time implications of running CLI analysis, or permission requirements. For a non-mutating analysis tool, the disclosure is reasonable but could be richer.

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?

Two sentences, reasonably front-loaded with the purpose stated clearly. The first sentence is concise and informative. The second sentence adds context about methodology. Slight redundancy between 'detailed analysis' and 'runs Claude CLI' but no wasted 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 output schema and no annotations, the description should compensate more. It doesn't describe what the analysis output looks like (report format, findings structure), whether results are returned directly or saved somewhere, or how long execution may take given it runs CLI commands. For a tool that triggers external processes, these operational details are meaningful. The 3-parameter schema is fully covered in the schema itself, which helps, but the tool's execution model remains underspecified.

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 schema documents all 3 parameters well. The description adds context about what the tool does with these inputs (runs analysis against RMS/MIP codebases), but doesn't add semantic detail beyond the schema, such as how codeChanges should be formatted or how analysisType affects output. Baseline 3 is appropriate when the schema carries the documentation weight.

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 verb (analyze) + resource (cross-component impact on RMS and MIP) and describes what it produces (dependencies, breaking changes, integration issues). The purpose is clear and specific. However, it doesn't explicitly distinguish this from sibling tools like 'validate_abac_changes', though the distinct focus on component impact analysis provides implicit 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 it (when analyzing code changes across RMS/MIP components), but provides no explicit when-not-to-use guidance or alternatives. The sibling tools (validate_abac_changes, get_current_changes, generate_validation_questions) are not referenced to help disambiguate use cases. The description states methodology (runs Claude CLI), which provides context, but no exclusions or alternative guidance means the agent must infer fit.

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