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

Annotations are minimal, so the description carries the burden. It discloses key behaviors: returns immediately while extraction happens in the background, stores facts automatically, and requires conversation_id. This adds significant behavioral detail not present in annotations or schema.

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, front-loaded with the core purpose. Every sentence earns its place: one explains the what/when, the other provides the key usage instruction (conversation_id) and behavior (immediate return, background processing). No filler or redundancy.

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?

For a 3-parameter tool with no output schema and weak annotations, the description covers purpose, usage context, async behavior, and a critical parameter requirement. It doesn't address error cases or what happens on extraction failure, but that is not essential for this tool.

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 baseline is 3. The description adds value by emphasizing the need to always include conversation_id in client, which is useful because client is optional in the schema. It also reinforces what to pass for task_content, though the schema already documents that.

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 captures durable facts from a just-completed task as an automatic byproduct, with the user doing nothing. It specifies the input (task output/content) and the process (extracted and stored automatically), distinguishing it from sibling tools like save_memory by emphasizing the hands-off, automatic nature.

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?

Provides clear context: use after completing a task (drafting email, summarizing doc, making decision) and pass the task output. It implies when to use this instead of manual memory tools, but does not explicitly name alternatives or exclusions like save_memory or search_memory.

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