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Generate Voice Skill

generate_voice_skill

Creates a Claude Skill bundle from analyzed writing corpus, enabling voice-consistent prose generation through example-based learning.

Instructions

Generate a Claude Skill bundle (SKILL.md plus real article samples) so Claude writes prose in the corpus author's voice by mimicking actual writing rather than following rule lists.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
corpus_nameYesName of analyzed corpus
corpus_dirYesDirectory where corpus is stored
sample_countNoNumber of article samples to bundle into the skill (default: 8)
Behavior2/5

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

No annotations are present, so the description carries full burden for behavioral disclosure. It mentions the output components and the technique of mimicking writing, but fails to disclose side effects (e.g., file creation), required dependencies, error conditions, or any limitations. The behavioral picture is incomplete.

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

Conciseness4/5

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

The description is a single, front-loaded sentence that conveys the core purpose efficiently. No redundant phrases. While it could be slightly more structured for scanning, it earns its place effectively.

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

Completeness3/5

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

Given the absence of output schema and annotations, the description is minimally adequate. It explains what the tool produces and the core idea, but lacks details on prerequisites, error handling, output format, or post-conditions. The schema covers parameter semantics, but overall context is thin.

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

Parameters3/5

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

Schema description coverage is 100%, so each parameter has a description. The tool description does not add additional meaning beyond the schema. According to guidelines, baseline is 3 when schema coverage is high, and no extra value is provided from the description.

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

Purpose5/5

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

Description clearly states the tool generates a Claude Skill bundle, specifies the output (SKILL.md plus article samples), and distinguishes its method from rule-based approaches. It contrasts with sibling tools (analyze_corpus, collect_corpus) by focusing on generation.

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

Usage Guidelines3/5

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

No explicit when-to-use or when-not-to-use guidance. The description implies this is the final step after corpus collection/analysis, but does not state exclusions or alternatives. Sibling names provide some context, but the description lacks direct usage advice.

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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