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

Annotations already certify idempotent and non-destructive, and the description adds meaningful context beyond that: key-value scoping by identifier, persistence differences for authenticated vs anonymous sessions (24h retention). It does not contradict annotations and enriches the behavioral model.

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?

Three sentences, no wasted words. The main action is front-loaded, and each sentence adds distinct value: what it does, when to use, and how it behaves (session persistence, pairing with recall/forget).

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 simple two-parameter tool with 100% schema coverage and clear annotations, the description covers all essential aspects: purpose, usage context, persistence behavior, and relationship to sibling tools. No output schema exists, but the tool's return value is not critical for the agent to invoke it correctly.

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 input schema fully documents both parameters (key and value) with descriptions and examples, so baseline is 3. The description only restates that it's a key-value pair, adding little beyond the schema's existing coverage.

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 opens with a specific verb and resource: 'Save data the agent will need to reuse later' and clarifies scope across conversation or sessions. It clearly distinguishes from siblings by naming recall and forget as complementary operations.

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 explicit when-to-use guidance: 'Use when you discover something worth carrying forward...' and gives concrete examples like resolved ticker or user preference. It also tells when not to use it by directing to recall for retrieval and forget for deletion, making the choice clear.

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