Prompt Architect
An Agent Skill that turns any rough idea into a domain-classified, pattern-aware, quality-reviewed expert prompt. Supports input in Turkish and English.
πΉπ· TΓΌrkΓ§e iΓ§in README.tr.md
Quick Start
git clone https://github.com/sametbrr/prompt-architect.git ~/.claude/skills/prompt-architect
Restart your Claude Code session, then trigger naturally:
> "Turn this into an expert prompt: build an onboarding strategy for a B2B SaaS"
Features
Given a vague input like "build an onboarding strategy" or "design an API for X", the skill:
- Analyzes the input β objective, constraints, complexity score (simple / moderate / complex).
- Classifies the domain against a 25-domain taxonomy with TR + EN signal keywords.
- Selects 3β6 prompting patterns (out of 9 UI-compatible ones) appropriate for the task.
- Drafts a refined English prompt using either a compact bullet scaffold or a full XML scaffold.
- Self-reviews the prompt against 8 quality gates.
- Executes the prompt and writes structured output to a file β only if the user asked for it.
The refined prompt body is always written in English for cross-model portability. Section labels follow the user's input language.
Requirements
- Python 3.10+ (for the optional validator script β no pip install needed)
- Claude Code or any agentskills.io-compatible agent
Installation
git clone https://github.com/sametbrr/prompt-architect.git ~/.claude/skills/prompt-architect
Claude Code auto-discovers skills under ~/.claude/skills/. Restart your session after cloning.
Usage
Modes
| You want⦠| Say something like⦠| Mode |
|---|
| Just the refined prompt | just the prompt, prompt only, don't run it | prompt_only (default) |
| Prompt + the actual deliverable | run it, execute it, generate the output too | prompt_and_execute |
Example
Input:
build an onboarding strategy for a B2B SaaS, and run it
Output (abbreviated):
Detected Domain: Product Growth Strategy
Complexity: moderate
Selected Patterns: Role, XML Structuring, Positive Guidance, CoT, Output Framing
Refined English Prompt:
<role>You are a senior product growth strategist...</role>
<task>Design a B2B SaaS onboarding strategy...</task>
...
Self-Review: 8/8 gates passed
Final Output: Saved to ./onboarding-strategy-output.md
Repository layout
prompt-architect/
βββ SKILL.md # Skill entrypoint + 6-stage workflow
βββ references/
β βββ claude-prompting-patterns.md # 9 UI-compatible patterns
β βββ quality-gates.md # 8 self-review gates + case study
β βββ domain-taxonomy.md # 25 domains, TR + EN signals
β βββ mode-inference.md # prompt_only vs prompt_and_execute
β βββ claude-md-rules.md # Authoring rules applied dual-layer
βββ assets/templates/
β βββ refined-prompt-xml.tmpl # Full XML scaffold (default for complex tasks)
β βββ refined-prompt-compact.tmpl # Bullet scaffold (simple tasks)
β βββ domain-*.tmpl # 6 domain packs
βββ scripts/
βββ validate_prompt.py # Optional 8-gate validator (stdlib only)
Key design choices
- Purpose-built for Claude. Designed specifically for Claude Code, claude.ai, and Agent Skills-compatible clients, following Anthropic's official prompting practices end-to-end. Refined prompt outputs remain portable to other LLMs.
- UI-compatible only. Patterns requiring API-level access (assistant prefill,
thinking, stop_sequences, tool_choice) are out of scope. Everything works in a regular chat window.
- Bilingual input, English body. The skill accepts Turkish or English input; the refined prompt body is always English for cross-model portability.
- Minimum-viable patterns. 3β6 patterns per task, not all 9. Simplicity wins.
- Don't over-ask. A clarifying question is allowed only if the input is genuinely unusable. Otherwise, infer and state assumptions.
- File output discipline. In execute mode, structured deliverables (>~50 lines) are saved to disk; only summaries print inline.
Validator
python3 scripts/validate_prompt.py --stdin < draft-prompt.txt
python3 scripts/validate_prompt.py --self-test
Pure stdlib, Python 3.10+.
Compatibility
