get_di_registrations

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

Without annotations, the description thoroughly discloses scanning behavior, output categories, and error handling (no error for non-Spring). It could add details about being read-only or performance characteristics, but the provided information 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 concise with structured sections (USAGE, OUTPUT, lists). It avoids verbose explanations while covering essential points. Minor improvements could include removing redundant formatting.

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 simple input (one optional param) and no output schema, the description covers key aspects: purpose, scanned items, and precondition. It does not detail output structure, but the context signals indicate low complexity, making this adequate.

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 only parameter, maxResults, is fully described in the schema (100% coverage). The description adds no additional detail about the parameter beyond the schema, resulting in a baseline score of 3.

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 'Find all dependency injection registrations' and lists specific types scanned (Spring components, configurations, beans, injection points). This clearly identifies the tool's function and distinguishes it from sibling tools like find_large_classes or get_dependency_graph.

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 provides clear usage context: it requires load_project to be called first and returns empty categories for non-Spring projects without error. However, it does not explicitly compare to alternative tools or indicate when not to use it.

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