metakirby5/.dots/skillify
Claude Code and agent skill by metakirby5/.dots
- community
Checking that the SKILL.md file is still in the repository.
Convert a freshly completed task or described workflow into a reusable skill. Use when the user invokes $skillify, asks to create a skill from the current process, wants generic repeatable steps captured, or requests a skill with optional name/destination clauses such as "$skillify as Spec to English in ~/.agent_skills" or "$skillify in projectname".
Install
npx vskill@latest install metakirby5/.dots/skillifySKILL.md
Skillify
Use this skill to turn a completed or described workflow into a reusable skill folder. The default output location is adjacent to this skillify skill. If the user provides as <NAME> or in <DIRECTORY>, infer the intended name or destination from natural language and honor it.
Workflow
- Infer the skill name and destination from the user's request.
- If there is no explicit name, infer a concise hyphen-case name from the workflow. Prefer action-oriented names under 64 characters.
- If there is no explicit destination, create the new skill adjacent to this
skillifyskill; use the parent directory of the loadedskillify/SKILL.md. - Identify concrete examples from the just-completed task or the user's description. If the source workflow is ambiguous, ask one concise clarifying question.
- Decompose the workflow into generic, repeatable steps.
- Classify each step:
- LLM-suited: translation, judgment, synthesis, naming, prioritization, visual QA, or context-specific choices.
- Script-suited: deterministic parsing, extraction, rendering, file transforms, validation, API calls with stable parameters, and repetitive boilerplate.
- Create the destination skill folder. Prefer the system
skill-creatorinitializer when available. If it is not available or is blocked, use:
- Author scripts for the script-suited steps first. Keep scripts parameterized, deterministic, and runnable without loading large context.
- Write
SKILL.mdwith concise frontmatter and body instructions. Include when to invoke each script, where LLM judgment is required, and validation steps. - Add
agents/openai.yamlwithdisplay_name,short_description, and adefault_promptthat explicitly mentions$<skill-name>. - Run script smoke tests and validate the skill:
If quick_validate.py is unavailable, at minimum verify SKILL.md has valid YAML frontmatter with name and description, and the folder name matches the skill name.
Destination Rules
- No
inclause: create the skill adjacent to thisskillifyskill, meaning in the same parent directory as the loadedskillifyfolder. - Absolute or
~path: use that directory. - Relative path containing
/: resolve from the current working directory. - Bare names such as
projectname: infer the intended skill directory from the user's active workspace and known local conventions. Do not assume a fixed folder name such asagent_skills; inspect or ask if the destination is ambiguous.
Quality Bar
- Do not encode one-off facts as universal instructions.
- Do not put generated reports, README files, changelogs, or process notes in the skill.
- Keep the skill lean; move only reusable deterministic code into
scripts/. - Test every new script with representative inputs before finishing.
Security
- Security scanPassed, 100 of 100Pattern checks on the skill's files.
- Model reviewNot runA model review is scheduled for the next rescan.
Quality evaluation
- Task evaluationNot runNo evaluation yet. Run one in Skill Studio.
Source
- SKILL.md in the repositoryCheckingbase-fold/.config/agent/skills/skillify/SKILL.md
Popularity
- Repository stars
- 76
- Repository forks
- 3
- 7-day trend score
- 22
Stars and forks are for the whole GitHub repository, not this skill alone. Not refreshed yet.
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