Save lesson

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

With no annotations provided, the description carries the full burden, and it does supply useful behavioral context: the operation is a write ('Record') and carries a timing constraint (only after a correction). It does not disclose persistence semantics — whether the lesson is stored permanently, surfaced by recall or search_history, or deduplicated on repeated saves — which an agent would need to anticipate downstream effects.

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, both purposeful: the first defines what the record captures, the second states when to invoke the tool. No wasted words, and the most operationally important guidance ('immediately after the user corrects your work') is prominent.

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 tool with three simple string params, full schema documentation, and no output schema, the description covers the essentials: what to record and when to call it. The only gap is explicit boundary-setting against the closely related write-siblings (remember, extract_memories, update_memory), which is implied by the correction-specific language but never stated.

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 description coverage is 100%, so the schema already documents all three parameters, setting the baseline at 3. The prose ('what situation, what mistake, what is the correct way') merely restates the parameter meanings rather than adding format, examples, or edge-case nuance, so the description adds marginal value beyond 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 states a specific verb and resource ('Record a lesson learned from a correction') and enumerates the three captured elements ('what situation, what mistake, what is the correct way'), which map directly to the required schema parameters. This correction-specific framing clearly distinguishes it from generic memory siblings like remember and recall.

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?

'Call immediately after the user corrects your work' provides an explicit, unambiguous trigger for invocation. However, it does not name alternatives (e.g., extract_memories or remember) or state when not to use this tool, so it stops short of full routing guidance.

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