Improve an existing skill by hand: teach it from examples and corrections you provide.
The agent follows the pack locally with the user and persists changes via save_skill(source='teach'). Requires edit access on the skill.
| Name | Required | Description | Default |
|---|---|---|---|
| skill_id | Yes | The skill to act on, identified by its UUID, slug, or name. |
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Changes observed during successful MCP inspections.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description indicates mutation ('improve', 'persists changes') while the annotations declare readOnlyHint: true, which is a contradiction. This severely undermines transparency.
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 three sentences, front-loaded with the key action, and every sentence adds essential information without fluff.
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 tool, the description covers purpose, permissions, and persistence. However, the annotation contradiction detracts from overall completeness.
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?
With 100% schema coverage and only one parameter, the description adds no extra semantic meaning beyond the schema's existing description.
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 verb 'improve' and the resource 'existing skill', and distinguishes it from siblings like 'save_skill' by specifying the teaching process.
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 mentions the prerequisite of edit access and the persistence mechanism via save_skill, but does not explicitly contrast with alternative modification tools like optimize_skill.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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