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Build complex AI systems with declarative programming, optimize prompts automatically, create modular RAG systems and agents with DSPy - Stanford NLP's framework for systematic LM programming
Passed 19 of 22 test cases with the skill, and 16 of 22 without it.
and 1 more in the full report
3 fixed16 passed either way3 still failing0 broke
Tokens, turns and time describe resource use, not a dollar price.
One of 3 test cases the skill fixed. Same model, same prompt, with and without the skill.
How do I configure DSPy to use OpenAI's `gpt-4` model globally with a max token limit of 1000?
| Checked | Without skill | With skill |
|---|---|---|
| Instantiates OpenAI model using dspy.OpenAI | Missed | Passed |
| Applies global model configuration using dspy.settings.configure | Missed | Passed |
The instructions your model reads when the skill loads.
This skill is repo-local and stays inactive until explicitly activated.
When the original instructions refer to legacy tool names, use these Kheish mappings:
terminal => bashweb_extract => web_fetch, plus web_search when discovery is neededsearch_files => grep_search and glob_searchbrowser_* tools require a browser-capable surfaced tool or MCP; if none is available, use the closest available surface and say so explicitlyWhen the instructions mention local helper files, resolve them from ${KHEISH_SKILL_DIR}.
Use DSPy when you need to:
GitHub Stars: 22,000+ | Created By: Stanford NLP
# Stable release
pip install dspy
# Latest development version
pip install git+https://github.com/stanfordnlp/dspy.git
# With specific LM providers
pip install dspy[openai] # OpenAI
pip install dspy[anthropic] # Anthropic Claude
pip install dspy[all] # All providers
test cases passed, vs 16 / 22 without
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