brain_lenses

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

No annotations are provided, so the description carries the full burden. It discloses the output includes an 'applyGuidance' string and that the model is expected to execute it, not just read the list. This goes beyond a simple list tool, but it doesn't disclose other potential behavioral traits like return details beyond the mentioned string.

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 three sentences: purpose, parameter, and output expectations. Each sentence adds distinct value, front-loading the core function. 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?

For a simple tool with one optional parameter and no output schema, the description covers the tool's purpose, the parameter, and the nature of the output (including the applyGuidance string and expected action). This is complete enough for an agent to select and invoke the tool 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?

The schema for 'kind' has no description and only an enum, so the clarification that 'kind optionally filters to one lens kind' adds meaning. It confirms the parameter is an optional filter, which is not otherwise self-evident from the bare schema. However, the enum values themselves are reasonably self-explanatory.

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 explicitly states 'List available reasoning lenses (mental models / thinker-inspired frames) for framing a decision.' This is a specific verb ('list') and resource ('reasoning lenses') with a clear purpose (framing a decision). The lens-specific focus distinguishes it from sibling tools like brain_backlog or brain_architecture.

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 provides clear usage context: it's for framing a decision, and it instructs the calling model to 'pick the 1-2 lenses that bite hardest on the live problem and apply them, rather than treating the list as reference material.' However, it does not explicitly compare against alternatives or state when not to use this tool.

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