detect_bugs

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

Given no annotations, the description carries the transparency burden. It adds valuable context by specifying the 8 bug categories, giving an example (datetime.now()) for call-expression defaults, and asserting that findings are 'likely real bugs, not style violations'. This goes beyond a generic 'detect bugs' statement. However, it does not mention return format or side effects, which is a minor gap.

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 two sentences, front-loaded with the core purpose, and includes the essential list of categories without verbosity. Every word adds value, achieving excellent conciseness and structure.

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 tool with 3 parameters and 8 bug categories, the description covers purpose, methodology, and the 'real bug' guarantee. It implies that findings are returned but does not specify the output format, which is a slight gap. Overall, it's largely complete given the schema richness.

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 description coverage is 100%, so parameters are well documented in the input schema. The tool description adds some value by enumerating the rule options and providing an example for one rule, but it doesn't clarify parameter usage beyond what the schema already states. Baseline of 3 is appropriate for high schema coverage.

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 detects common Python semantic bugs using AST analysis, and lists the 8 specific bug categories. This distinct purpose separates it from sibling tools like find_dead_code or security_scan.

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 (for semantic bug detection) but provides no explicit guidance on when not to use it or how it differs from alternatives like find_dead_code. It lacks any mention of alternative tools or exclusions, so usage context is only implied.

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