lldb_help

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

Annotations indicate read-only, non-destructive, and idempotent behavior, which the description doesn't contradict. The description adds context about what help is provided (general usage, command syntax) and the return format, enhancing transparency beyond annotations.

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 clear sections ('Provides', 'Args', 'Returns'), uses bullet points for readability, and every sentence adds value without redundancy. It's front-loaded with the core purpose.

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 low complexity (one optional parameter), rich annotations (read-only, idempotent), and an output schema (returns string), the description is complete. It covers purpose, usage, parameters, and return values adequately.

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 has 0% description coverage for the single parameter 'topic'. The description compensates by explaining that an empty topic provides general help, while a specific topic (e.g., 'breakpoint') gives command-specific help, adding meaningful semantics not in the schema.

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 purpose as 'Get help on LLDB commands and usage' with specific examples like 'breakpoint' and 'memory', distinguishing it from sibling tools that perform debugging operations rather than providing documentation.

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 explicitly states when to use this tool: for general LLDB usage (empty topic) or help on specific commands, with clear examples. This distinguishes it from all sibling tools, which are for execution or analysis rather than help retrieval.

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