get_cross_module_dependencies

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

The description adds the key behavioral insight 'No prior indexing required,' which goes beyond the annotations (readOnlyHint, idempotentHint) to inform the agent about prerequisites. It also outlines the return structure, though it omits potential performance considerations for large repositories.

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 extremely concise: two sentences that cover purpose, outputs, and a key benefit (no indexing). No redundant information is present.

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 complexity (6 parameters, no output schema), the description provides a good overview of what the tool returns (modules, edges, diagram, stats). It lacks an example output structure but is otherwise sufficient for an agent to understand the tool's capabilities.

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?

All parameters have schema descriptions (100% coverage), so the description adds no additional parameter-level meaning. It focuses on outputs rather than parameter details, so a baseline score of 3 is appropriate.

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 explicitly states the tool builds an inter-module import graph for a Python repository, listing specific outputs (nodes, edges, stats, Mermaid diagram). This clearly differentiates it from sibling tools like get_call_graph or get_inheritance.

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?

No guidance is provided on when to use this tool versus alternatives. The description does not mention scenarios where other tools (e.g., get_call_graph for call-level analysis) would be more appropriate.

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