agent_reflection

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

No annotations are provided, so the description carries the full burden for behavioral transparency. It only states that the tool creates and retrieves reflections, without disclosing side effects, persistence guarantees, idempotency, authentication needs, or rate limits. The description does not go beyond the basic operation, leaving significant gaps for an agent to understand the tool's behavior.

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 front-loaded with the purpose statement, followed by examples and reflection types. The examples are helpful but make the description longer than necessary. Structure is clear and logical, but could be more concise by trimming redundant example patterns. Still, it earns points for good organization.

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's complexity (6 parameters, no output schema, no annotations), the description covers the actions and reflection types adequately. However, it fails to describe the return format (e.g., does 'list' return an array of reflections? Does 'create' return the created object?). With no output schema, these details are missing, making the description incomplete for an agent to fully understand the tool's behavior.

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 description coverage is 100%, so the input schema already documents all parameters. The description adds value through examples showing valid parameter combinations (e.g., content with learning type, relatedAgents with collaboration). However, it does not elaborate on parameter semantics beyond what the schema provides, such as constraints on content length or format. Baseline is 3, and the examples only slightly enhance understanding.

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 tool's purpose: 'Create and retrieve agent reflections for continuous improvement.' It specifies a verb (create/retrieve) and a resource (agent reflections). The examples and reflection types further clarify the scope, distinguishing it from sibling tools like 'remember' or 'agent_memory' which handle more generic memory.

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 usage examples for both create and list actions, showing typical scenarios. However, it does not explicitly contrast with alternative tools (e.g., when to use 'agent_reflection' vs 'remember' or 'agent_error_learning'), nor does it specify when not to use this tool. The guidance is clear in context but lacks explicit exclusions.

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