List Reflections

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

Despite the openWorldHint annotation, the description does not disclose any potential side effects or additional behaviors. It also lacks details about pagination, return format, or cost implications, which are important for a list operation with an open-world hint.

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 a single sentence that front-loads the core purpose ('List self-learning reflections generated by a bot') and includes the filtering option concisely. No extraneous words.

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 lacks information about the return format or output structure, which is important since no output schema is provided. Additionally, with openWorldHint, more context about potential side effects would be expected. However, the tool is relatively simple, so a 3 is reasonable.

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 input schema already provides complete descriptions for both parameters (botId and status). The tool description only mentions 'optionally filtered by status,' adding no significant meaning beyond the schema. Baseline 3 is appropriate given 100% schema 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 uses the specific verb 'list' and clearly identifies the resource as 'self-learning reflections generated by a bot.' It also mentions optional filtering by status, which effectively distinguishes it from sibling tools like neuron_approve_reflection or neuron_reject_reflection.

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 states the tool lists reflections and optionally filters by status, which implicitly suggests its use for reading reflections. However, it does not explicitly contrast with related tools (e.g., neuron_sync_reflections, neuron_approve_reflection) or provide when-not guidance.

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