DSPy vs i-have-adhd
A side-by-side comparison of features, pricing, and characteristics.
DSPy
DSPy is a framework for algorithmically optimizing LM prompts and weights, especially when LMs are used within pipelines.
Read the full reviewi-have-adhd
An open-source skill that makes coding-agent responses concise, actionable, and ADHD-friendly.
Read the full review| Attribute | DSPy | i-have-adhd |
|---|---|---|
| Pricing type | Free | Free |
| Korean support | No | No |
| Platforms | API, CLI | Claude Code, OpenAI Codex, Gemini CLI, GitHub Copilot, Cursor, Zed |
| Open source | Yes | Yes |
| API available | Available | - |
| SDK | Available | - |
| LLM-based | Yes | - |
| Multimodal | Yes | - |
| AI model | Anthropic Claude, Google Gemini, Databricks | - |
| GitHub Stars | - | 27.4K |
| Vendor | Stanford NLP Group | - |
| Category | Developer Tools | Developer Tools |
| Details | View | View |
DSPy key features
- Declarative Signatures
- Modular Pipelines
- Automatic Prompt Optimization
- Data-driven Tuning
- Model-agnostic Programming
- Validation & Metrics
i-have-adhd key features
- Presenting answers and next actions first
- Structuring multi-step tasks into numbered lists
- Redisplaying progress at every turn
- Providing specific time estimates
- Explaining errors focusing on location, cause, and solution
- Suppressing unnecessary introductions and conclusions