Skill Creator
Design modular, reusable skills for AI assistants to extend their specialized capabilities.
The skill guides creating skills, involving generating scripts and files, but lacks least-privilege or user-confirmation mechanisms. It suggests executing scripts via shell_interpreter without explicit sandboxing or data-flow disclosure. The skill itself doesn't handle sensitive data directly, but generated scripts could be used for arbitrary actions. Based on trust anchors, main risks are visible but permission confirmation incomplete, hence 14.
The skill includes clear steps and scripts (init_skill.py, package_skill.py, quick_validate.py), but static review cannot execute validation. Scripts are well-structured with basic error handling, but lack tests or mock data. Per static calibration, reliability capped at 10; given good code quality, assign 8.
The skill clearly targets Claude users for skill creation, with clear scenarios and triggers, detailed description. Non-fit boundaries not explicit but inferable from examples and steps. Environment fit: docs include Chinese examples, but core tools mostly English; no mention of mainland-China network reachability. Boundaries fairly clear, hence 14.
SKILL.md structure is clear, with frontmatter, body, progressive disclosure principles, but lacks installation notes, version history, and changelog. License mentioned but full terms not included. Maintenance responsibility carried by repo, but update path not explicit. Overall readable but governance incomplete, hence 13.
The skill's core goal is to guide skill creation, steps are detailed and should accomplish basic tasks. But static review cannot verify direct usability of outputs, and no comparison to manual methods. Per static calibration, effectiveness capped at 7, so assign 7.
Repository has test files (e.g., test_dispatch_prompt.py etc.), but not for this skill path. The skill's own scripts lack accompanying tests, insufficient verification. Static review cannot independently reproduce, so cap at 5.
- The skill suggests executing scripts via shell_interpreter without explicit least-privilege or user confirmation; use with caution.
- Lack of explicit non-fit scenarios may lead to inappropriate triggering.
- Core scripts lack accompanying tests; static review cannot verify reliability.
What does this skill do, and when should you use it?
Skill Creator is a structured workflow that guides users through creating, packaging, and iterating on Claude skills. It emphasizes concise, effective prompt design and managing context windows through a three-level progressive disclosure mechanism (metadata, SKILL.md, bundled resources). The skill provides step-by-step instructions: starting with understanding concrete examples, planning reusable resources (scripts, references, assets), initializing the skill with init_skill.py, editing SKILL.md and resources, packaging with package_skill.py, and iterating. It also includes guidance on skill anatomy, what to avoid including, and design patterns like organizing references by domain.
The skill walks users through the end-to-end skill creation process: it instructs on using the Python script init_skill.py to generate a template skill directory structure (with SKILL.md and scripts/, references/, assets/ subdirectories), provides guidance on editing SKILL.md and bundled resources, and then runs package_skill.py to validate and package the skill into a .skill file (a zip). It emphasizes using the shell_interpreter tool for command execution and encourages iteration based on real usage.
- A developer wanting to build a specialized AI assistant capability, such as a PDF processing skill.
- A team needing to encapsulate company-specific knowledge (like database schemas or policies) for AI assistants to reference during analysis tasks.
- A user who wants to package repeated code into reusable scripts to reduce context usage.
- A user aiming to ensure skills follow best practices like progressive disclosure and concise principles.
- A user needing to produce a distributable .skill file for a specific workflow to share with their team.
What are this skill's strengths and limitations?
- Detailed step-by-step process covering the entire skill lifecycle from planning to packaging.
- Emphasis on conciseness and progressive disclosure helps maintain efficient context usage.
- Provides validation and packaging scripts to produce standard-format distributable .skill files.
- Includes guidance on avoiding redundant documentation and best-practice structure organization.
- Primarily designed for Claude and may not be fully applicable to all AI assistant platforms.
- Workflow assumes user familiarity with shell commands and resource planning.
- This skill does not implement concrete business logic itself; it requires user-provided domain knowledge.
- Lacks fully worked examples illustrating how to design a skill from scratch.
How do you install this skill?
The skill lives in the skills/skill-creator/ directory in the repository. No separate installation is required; it's used as part of the DB-GPT project. Its internal scripts (e.g., init_skill.py, package_skill.py) are located under skills/skill-creator/scripts/ and are designed to be executed via shell_interpreter.
How do you use this skill?
After identifying a skill need, follow the steps: optionally clarify requirements, plan resources, initialize the skill with python skills/skill-creator/scripts/init_skill.py <skill-name> --path skills/, edit the generated SKILL.md and resources, package with python skills/skill-creator/scripts/package_skill.py <path/to/skill-folder>, and finally test and iterate on real tasks.