dashclaw_learning_query

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

With no annotations provided, the description carries full burden for behavioral disclosure. It only states the tool 'queries' without revealing potential side effects, rate limits, authentication needs, or behavior on empty results. The description is too sparse for a non-annotated tool.

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?

Extremely concise: two sentences with zero wasted words. The purpose is front-loaded, making it easy for the agent to quickly understand the tool's role.

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 query tool with 3 optional parameters and no output schema, the description covers the essential purpose and usage timing. However, it lacks details on return format, pagination, or error conditions, which would aid an agent's decision-making.

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 coverage is 67% (two of three parameters described). The description adds no parameter-specific meaning beyond the schema; it merely restates the function. Baseline of 3 is appropriate given moderate 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 action ('Query the learning database') and the resource ('prior decisions and lessons'). It also provides usage context ('Use BEFORE making a decision similar to one you might have made before'), which distinguishes it from other similar sibling tools like dashclaw_learning_log or dashclaw_decisions_recent.

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?

Provides explicit guidance on when to use the tool ('Use BEFORE making a decision similar to one you might have made before'), but does not mention exclusions or alternatives among sibling tools. The context is clear but could be more comprehensive.

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