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JeremyLakeyJr

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explain_skill_error

Use to normalize skill validation error text into a client-friendly format. Provide the raw error string to get a structured, understandable explanation of the failure.

Instructions

Normalize skill validation failures for the client.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
error_textYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Implementation Reference

  • The actual tool handler: raises a SkillError with the provided error_text and catches it, returning the string representation to normalize skill validation failures for the client.
    @mcp.tool()
    def explain_skill_error(error_text: str) -> str:
        """Normalize skill validation failures for the client."""
        try:
            raise SkillError(error_text)
        except SkillError as exc:
            return str(exc)
  • The tool is registered via the @mcp.tool() decorator, defined within the register() function which receives the mcp instance.
    @mcp.tool()
    def explain_skill_error(error_text: str) -> str:
        """Normalize skill validation failures for the client."""
        try:
            raise SkillError(error_text)
        except SkillError as exc:
            return str(exc)
  • SkillError is a custom exception (subclass of ValueError) used by the tool to normalize validation errors.
    class SkillError(ValueError):
        """Base exception for skill validation and installation failures."""
Behavior2/5

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

No annotations are provided, so the description must disclose behavior. It only says 'normalize', but does not state if this is a read-only transformation, whether it makes external calls, or what the output format is. The agent cannot infer side effects or return value characteristics.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness2/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is extremely short (one sentence) but lacks informativeness. It is not concise in a helpful way; it omits critical details. Every word should earn its place, but here the vague verb 'normalize' wastes space.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given that an output schema exists (though unseen), the description does not explain what the tool returns. For a tool processing error text, the agent needs to know whether it returns a structured explanation or a modified string. The description is incomplete for the agent to use correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters1/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema has 1 parameter (error_text) with 0% description coverage. The tool description adds no meaning beyond the schema itself. It does not explain the expected format or content of error_text, nor how it should be structured. This fails to compensate for the low schema coverage.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose2/5

Does the description clearly state what the tool does and how it differs from similar tools?

Description says 'Normalize skill validation failures for the client.' This is vague; 'normalize' could mean reformat or standardize, but it doesn't specify what the tool actually does with the error_text. Compared to siblings like 'validate_skill_markdown', the purpose is unclear and not differentiated.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance on when to use this tool versus alternatives. No context about prerequisites or typical use cases. The description provides no directional hints for an agent.

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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