get_code_comprehension_strategy

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

No annotations are provided, so the description carries the burden. It discloses the generation mechanism and mentions a behavioral trait of avoiding hallucinations, which is useful. However, it does not state side effects, auth requirements, or what the output format exactly looks like (beyond 'strategies'). Since this is a read-only generation tool, the lack of side-effect disclosure is not critical, but the description could mention that it returns a textual strategy.

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 a single, information-dense sentence. It front-loads the purpose and packs in method and quality attributes. It is not overly long and no words are wasted. It could be split for readability, but it's effective.

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 tool's simplicity (2 params, no output schema), the description is mostly sufficient. It explains what the tool produces (step-by-step strategies) and implies the input variables. It lacks explicit statement of output format or limitations, but for a strategy generator, this is acceptable. The description is complete enough for an agent to call it correctly.

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 coverage is 100%, so the baseline is 3. The description adds value by explaining that the parameters (repo_size and primary_language) feed into the dependency-tree and entry-point-mapping approach, giving context for how they influence the output. This goes beyond the schema's simple field 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 function: generating step-by-step strategies for reading, mapping, and understanding complex codebases. It specifies the method (dependency trees, key entry-point mapping) and even includes a quality goal ('without hallucinations'). This distinguishes it from sibling tools, which are mostly blueprint generators for other domains (security, deployment, marketing, etc.).

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 the agent needs to understand a complex codebase. It gives clear context but does not explicitly name alternatives or state when not to use it. Siblings like generate_*_blueprint are clearly different, so ambiguity is low, but the description lacks direct exclusion criteria.

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