remember_extracted

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

With no annotations, the description carries full burden. It discloses the extraction process, graph building, and return of fact IDs. It mentions prerequisites but does not detail potential side effects like overwriting or merging.

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, no redundant words, front-loaded with purpose and benefit. The prerequisite and return values are efficiently stated.

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 and presence of an output schema, the description covers inputs, process, prerequisites, and output. It could mention idempotency or duplicate handling, but is fairly complete.

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 minimal value beyond schema descriptions; for 'text' it is nearly identical, and for 'metadata' it adds no extra context. No meaningful enhancement.

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 explicitly states the tool stores raw text by extracting atomic facts and building a fact-to-topic graph, differentiating it from sibling tools like `remember` and linking to `why`. The verb 'store' and resource 'passage of raw text' are clear.

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 explicit prerequisites (server started with extraction backend) and implies the tool is for automatic fact extraction and linking. It does not explicitly state when not to use or list alternatives, but context is clear enough.

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