extract_memories

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

No annotations are provided, so the description must fully disclose behavior. It mentions AI extraction but does not clarify whether the tool returns the extracted facts or stores them, nor does it discuss side effects, permissions, or error handling.

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?

Two sentences that are direct and front-loaded: first states the purpose, second explains input and outcome. No filler 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?

With no output schema and no annotations, the description should explain what the tool returns or whether it modifies state. It fails to clarify if extracted memories are returned, saved, or both, leaving the agent uncertain about usage.

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?

All three parameters have schema descriptions (100% coverage). The description adds minimal value by mentioning 'developer message' and 'assistant response', but does not explain the optional 'previous_context' parameter beyond what is in the schema.

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 extracts memories from a conversation using AI, with specific examples of facts (architecture decisions, preferences, bug fixes). This distinguishes it from siblings like recall_memories or save_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?

It describes when to use the tool (after a conversation exchange) and what input to provide, but does not explicitly mention when not to use it or compare to alternatives like consolidate_memories.

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