dependency_analysis

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

With no annotations, the description carries the burden of behavioral disclosure. It discloses performance (3-10s), that it builds a dependency graph, and offers a tip about what to look for. It doesn't detail return format or side effects, but for a read-only analysis tool this is sufficient.

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 well-structured with labeled sections (PURPOSE, USAGE, PERFORMANCE, WORKFLOW, TIP). Each section adds unique value without redundancy, making it both compact and highly informative.

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 zero-parameter tool with no output schema and no annotations, the description is remarkably complete. It covers purpose, usage scenarios, performance expectations, workflow integration, and even analysis tips, fully enabling an agent to decide when and how to invoke it.

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 tool has zero parameters and an empty schema, so the description doesn't need to explain parameter details. It confirms that the tool analyzes the entire codebase implicitly, which is appropriate given the lack of inputs.

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: analyzing module dependencies, mapping interdependencies, identifying circular dependencies, and revealing architectural patterns. It distinguishes itself from sibling tools like find_references or find_callers by focusing on the overall dependency graph rather than specific references.

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?

It provides explicit use cases (architectural analysis, identifying tightly coupled modules, planning restructuring) and places the tool in a workflow (analyze_codebase → dependency_analysis → complexity_analysis). However, it does not explicitly mention alternatives or when-not-to-use conditions, so it's not a full 5.

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