Remove a learning record by its unique ID. First list learnings to find the ID, then delete the specific entry.
Delete a learning by its ID. Use list_learnings first to find the ID of the learning you want to remove.
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes | The unique ID of the learning to delete |
Changes observed during successful MCP inspections.
v2.9.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description bears full responsibility. It states the destructive action ('delete') but lacks disclosure of side effects, permissions, reversibility, or error behavior. The minimal information is insufficient for a mutation tool.
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 redundancy, front-loaded with action. Every word serves a purpose. Highly efficient.
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 simple single-parameter nature, the description covers the essential action and provides a useful prerequisite. However, it omits details about return values, error handling, and behavioral nuances that would aid an agent in robust 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?
The single 'id' parameter is fully described in the schema (100% coverage). The description repeats the ID usage but adds no additional semantic meaning beyond the schema. The prerequisite hint (list_learnings) is useful but not directly parameter-related.
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 action ('Delete a learning by its ID') and distinguishes it from siblings like list_learnings and import_learnings. The verb 'delete' and resource 'learning' are specific and unambiguous.
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?
Explicitly advises using list_learnings first to obtain the ID, providing a clear prerequisite and workflow direction. Does not mention when not to use or name specific alternatives, but the guidance is helpful.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.