recall_reflections

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

With no annotations, the description carries full burden. It discloses that reflections are fallible-by-design, written by a local LLM (default ministral-3:14b), and that the reader is the calibration mechanism. This provides adequate behavioral context.

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?

Three sentences, front-loaded with purpose, no unnecessary words. Every sentence adds important information.

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?

The description explains the nature of reflections but does not describe the output structure (e.g., fields returned). Since there is no output schema, the agent lacks information about what each reflection contains beyond the parameters.

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 100%, so parameters are well-documented. The description adds value by specifying the default model ('ministral-3:14b') and giving usage context for ack_status, which is not in the schema 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?

The description clearly states the action ('List') and the resource ('machine-generated reflections from the synthesis daemon'). It distinguishes from sibling tools like 'recall_insights' by specifying the source and nature of reflections.

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 instructs to 'Use ack_status=''unread'' to find new ones, then ack each with reflection_ack', providing clear when-to-use and post-action guidance. It does not explicitly mention when not to use or alternatives, but the guidance is effective.

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