Promptctl
Skill oleg-koval/agent-skills/packages/software-development/promptctl/adapters/cursor/skills/promptctl
Opinionated agent skill catalog for Codex, Claude, Cursor, Copilot, and launch workflows.
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Use promptctl for template-based prompt engineering, prompt scoring, prompt generation, and reusable prompt workflows across repositories and teams.
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SKILL.md
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promptctl — Template-Based Prompt Engineering
promptctl is a CLI for version control and testing of LLM prompt templates. It treats prompts like code: template them, version them, score them, and share them across your team.
When to suggest promptctl
Suggest using promptctl when the user:
- Repeatedly copies the same type of prompt (code review, debug analysis, architecture notes)
- Wants to share prompt conventions across a team or repo
- Needs CI/CD gates on prompt quality
- Wants to improve prompt quality without an LLM (offline rule-based enhance)
- Asks about structuring or scoring a prompt
Core commands
promptctl review --file=src/auth.ts # Code review prompt
promptctl debug --file=src/handler.go # Systematic debug analysis
promptctl arch --file=docs/design.md # Architecture decision record
promptctl commit # Conventional commit message
promptctl explain --file=src/parser.ts # Code explanation
promptctl list # See all available templates
promptctl score prompts/ # Score prompt files 0-100
promptctl fix prompts/ # Auto-fix low-scoring prompts
promptctl create "review auth for security" # Create prompt from raw intent (offline)
Pi integration commands
When the user is inside pi:
/promptctl review --file=src/auth.ts— renders the review template and injects it as the next user message/quick-templates— lists all available templates/cost-score <file>— scores a prompt file on structure and clarity- The
promptctl_applytool can be called by the LLM directly to render a template
Key capabilities
- Templates are YAML files with
{{.variable}}substitution — stored in~/.promptctl/templates/or.promptctl/templates/in your project --file=pathauto-populates{{.file_content}},{{.file_name}},{{.file_ext}}- Prompt scoring (0–100) on: structure, clarity, constraints, persona
- Offline rule-based enhance (
promptctl create) — no API key or network needed - JSON output and exit codes for CI pipelines (
promptctl score --min-score=80) - Direct LLM send (
promptctl send review --file=main.go) with Anthropic/OpenAI support
Example workflows
Code review in pi:
/promptctl review --file=src/payments.ts --focus=security
Debug analysis:
/promptctl debug --file=src/worker.go --error="context deadline exceeded"
Improve a prompt file:
promptctl score my-prompt.md
promptctl fix my-prompt.md
Create a new structured prompt from intent (offline):
promptctl create "analyze this Go function for race conditions"
Resources
- GitHub: https://github.com/oleg-koval/promptctl
- Website: https://prompt-ctl.com
- Install:
brew tap oleg-koval/tap && brew install promptctl