memory_reflect_now

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

The description discloses that the tool updates the self-model and consolidates knowledge, which implies state changes, but it does not explicitly state side effects, reversibility, or what happens to data. Annotations indicate readOnlyHint=false and destructiveHint=false, which are consistent with the description but add no extra detail. The description goes slightly beyond the annotations by mentioning 'updates self-model' but does not fully elaborate on behavioral implications.

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 exceptionally concise—two sentences that pack all essential information. It front-loads the primary purpose and then lists the key actions without any fluff. There is no redundant or irrelevant text, making it easy to parse and understand quickly.

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 has only one parameter, no output schema, and a clear description of its actions, the context is largely complete. However, the description does not mention what the tool returns (e.g., success confirmation or a summary of reflection), and given the large sibling set, a note on when to prefer this over memory_consolidate would improve completeness. Still, the core functionality is adequately covered.

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 description covers the 'scope' parameter with a full enum and descriptions for each option (quick, full, weekly), so parameter semantics are already well-documented. The tool description does not add extra context beyond what the schema provides. With 100% schema coverage, the baseline score of 3 is appropriate.

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 function with a specific verb ('Run reflection') and resource ('the sleep process'), and lists concrete actions (consolidates, finds patterns, generates proposals, updates self-model). While it doesn't explicitly contrast with sibling tools like memory_consolidate or self_reflect, the specificity of the actions makes the purpose clear enough for an agent to understand what it does.

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 no guidance on when to use this tool versus its siblings (e.g., memory_consolidate, self_reflect). It does not mention conditions, prerequisites, or alternatives. An agent would have to infer usage from the name and description alone, which is insufficient given the many overlapping memory and reflection tools.

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