variables_set

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

No annotations are provided, so the description bears the full burden. It discloses that the tool mutates state (destructive behavior) and mentions frame scoping via the frameId parameter. However, it lacks details on potential side effects (e.g., hitting breakpoints, thread safety, error handling for invalid expressions) and does not explain what happens when frameId is null or different frames.

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?

Two sentences, front-loaded with purpose and a clear example of usage. Every word earns its place; no filler or redundancy.

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 has three parameters and no output schema or annotations, the description covers the key aspects: purpose, scope (lvalue expression, frame context), and a use case. It could mention return value or error behavior, but for a debugger mutation tool it is reasonably complete.

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?

Input schema covers all three parameters with descriptions (100% coverage), so baseline is 3. The description adds value by providing concrete examples for 'expression' and 'value' (e.g., 'userId', '42'), and clarifies the default for frameId. However, it does not significantly extend beyond the schema's 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?

Description clearly states the tool sets a variable or lvalue expression, with examples. It distinguishes from sibling tools like 'evaluate' (which does not mutate state) and 'variables_get' (for reading). The verb 'Set' and resource 'variable or lvalue expression' are specific and unambiguous.

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?

Description explicitly says the agent can use this 'to test fixes by mutating state mid-run', providing a clear use case and context. While it does not list when not to use or directly compare to alternatives, the purpose is clear enough for an AI agent to infer appropriate usage.

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