cos_learn_narrative

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

The description states it 'Creates a high-impact learned pattern' and discloses the return format (status, history_id, pattern_id), adding value beyond the annotations. The annotations already indicate a write operation (readOnlyHint false), and the description aligns with that without contradicting it.

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?

The description is well-organized: purpose, trigger, bullet points of what to capture, args, and returns. Each section is concise and serves a clear function, though slightly longer than strictly necessary.

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?

The description covers purpose, usage context, parameters, and return value. It does not address the relationship with other learn tools or clarify the optionality of key_insight, but the presence of an output schema and annotations partially compensates. Overall it is sufficiently complete for an agent to select and invoke the 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?

All four parameters are described with brief explanations, which is critical given 0% schema coverage. However, the description marks key_insight as 'required' while the schema lists it as optional with a default, and fails to note that task_id is the actual required parameter. This inconsistency could mislead the agent during invocation.

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 'Record what was learned from a difficult task (breakthrough narrative),' providing a specific verb and resource. It clearly distinguishes itself from sibling learn tools by focusing on post-rework success narratives and capturing failure/success/insight.

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?

It gives an explicit trigger: 'Call this after a rework→success breakthrough.' This tells the agent exactly when to use it. However, it does not mention alternatives or exclusions, so it lacks the explicit 'when not to use' that would merit a 5.

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