PromptShift is a model-aware prompt adapter for Claude.
It improves prompts by making them clearer and more reliable — without changing what the user actually meant.
Most prompt optimizers change your intent without realizing it.
PromptShift does the opposite:
It rewrites prompts while preserving intent as the highest constraint.
It improves:
- Clarity
- Structure
- Consistency across models
Without adding:
- New goals
- New requirements
- Artificial complexity
Prompt optimization tools often "help" by rewriting your prompt into something more verbose, like:
Input
Summarize this article.
Typical optimizer output (problematic):
Act as an expert analyst and provide strategic insights, risks, and implications...
That's not the same task anymore. PromptShift treats that as intent drift.
- Clarity first — Remove ambiguity before adding structure.
- Preserve intent — Never invent goals, audiences, or constraints.
- Minimal change — If the prompt is already good → leave it.
- Model-aware (not model-dependent) — Adapt only when it measurably improves output.
- No prompt inflation — Avoid unnecessary roles, fluff, or "AI personas".
Prompt Input ↓ Triage (Simple / Complex) ↓ Clarify Ambiguity ↓ Repair Weak Constraints ↓ Minimal Model Adaptation ↓ Optimized Prompt
PromptShift can:
- Clean ambiguous prompts
- Normalize structure
- Fix missing constraints
- Detect missing output formats
- Adapt prompts across model families
- Improve consistency across LLMs
PromptShift does NOT:
- Invent requirements
- Add fake expertise or roles
- Inflate prompts for appearance
- Guarantee better outputs
- Replace prompt iteration
- Override user intent
Input
Summarize the attached article about recent climate policy developments and their implications for global emissions.
Output
The prompt is underspecified: no output format or constraints defined.
Summarize the attached article about recent climate policy developments and their implications for global emissions.
Requirements:
- 6 bullet points
- 1 sentence per bullet
- Maximum 200 words
Added explicit structure and length constraint.
High
The task is unchanged — only clarity is improved.
PromptShift includes lightweight adaptation rules for:
- Claude (Opus / Sonnet / Haiku)
- GPT (reasoning models)
- Gemini
- Grok
- DeepSeek
- Llama
- Mistral
- Qwen / Kimi
- Command R+
These are heuristics, not guarantees.
PromptShift is not:
- a prompt generator
- a persona builder
- a prompt marketing tool
It is:
A minimal transformation layer between intent and execution.
The repo includes benchmark cases for:
- Coding
- UI generation
- Writing tasks
- Reasoning tasks
- RAG-style prompts
See ./benchmarks for details.
git clone https://github.com/Alvaro-Manzo/promptshift.gitCopy SKILL.md into your Claude Skills directory and enable it.
Contributions are welcome, especially for:
- Edge cases where intent drift happens
- Model-specific failure patterns
- Better evaluation benchmarks
Please read CONTRIBUTE.md before making any PR or Issue, include reasoning, not just edits.
MIT © 2026 Alvaro-Manzo