log_recommend

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

With no annotations, the description carries the behavioral burden, and 'analyze' plus 'recommend' clearly signal a non-mutating advisory operation, which is the core behavior. However, it does not explicitly disclose the output format, whether the optional api_key may trigger external calls, or whether the codebase is left untouched.

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 front-loaded sentence with no filler, repetition, or irrelevant detail. It states the purpose efficiently and earns its place.

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 three-parameter analysis tool with no output schema and no annotations, this one-sentence definition is incomplete. It does not describe the shape of the recommendations, how the framework parameter influences analysis, whether api_key is needed, or what the agent should expect as a return value.

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 schema already describes directory and framework well, providing 67% coverage. The description adds no parameter-level detail and does not clarify the meaning or necessity of api_key, leaving that parameter under-documented.

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 names a specific action (analyze codebase) and a concrete outcome (recommend where to add structured logging), so an agent can tell what the tool produces. It is clear but does not explicitly differentiate itself from related log_analyze, log_search, or log_correlate tools, relying on 'codebase' to imply the distinction.

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 gives no explicit guidance on when to prefer this tool over related logging/observability tools, and it names no alternatives, exclusions, or prerequisites. The only usage signal is the general purpose sentence, which is implied rather than clearly stated.

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