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DSPy optimization workflows — teleprompters, metrics, evaluation, and compilation strategies. Use when optimizing DSPy programs with BootstrapFewShot, MIPROv2, or custom metrics.
Codex または Claude でインストール この Prompt をコピーして Codex、Claude、または他のアシスタントに貼り付けると、Skill ページを確認してインストールできます。
SOC 職業分類に基づく
Execute batched or parallel RLM work using Daytona sandboxes. Use when running multiple sub-tasks, parameter sweeps, or batch recursive RLM calls in the daytona_pilot runtime.
Debug fleet-rlm runtime issues from Claude Code. Use when diagnosing daytona_pilot failures, API and websocket contract problems, sandbox persistence bugs, or runtime readiness drift.
Execute Python code in Daytona sandboxes with durable volume persistence. Use when running code in a Daytona sandbox, processing data with stateful execution, or persisting results across sessions.
(EXPERIMENTAL) Research implementation for RLM long-context processing using standalone Python scripts. For production use, prefer the rlm skill which uses the fleet-rlm package with Daytona sandboxes. This skill is for experimentation, evaluation, and alternative implementation patterns.
Long-term memory persistence for RLM using Daytona durable volume storage. Use when storing, recalling, listing, or searching data that persists across sandbox sessions in the daytona_pilot runtime.
Run fleet-rlm through its current public entrypoints. Use when you need the right command for the Web UI, API server, MCP server, terminal chat, or Daytona smoke validation from a Claude Code workflow.
| name | dspy-optimization |
| description | DSPy optimization workflows — teleprompters, metrics, evaluation, and compilation strategies. Use when optimizing DSPy programs with BootstrapFewShot, MIPROv2, or custom metrics. |
Guidance for optimizing DSPy programs: teleprompter selection, metric definition, evaluation workflows, and save/load patterns.
This skill requires uv as the Python package manager.
uv venv
source .venv/bin/activate
uv pip install dspy
Rule: Never use raw
pip. Always useuv pipfor installs anduv runfor script execution.
# Use the optimize-dspy script
uv run scripts/optimize-dspy.py --module my_module --metric my_metric --examples examples.jsonl
from dspy.teleprompt import BootstrapFewShot
optimizer = BootstrapFewShot(metric=my_metric, max_bootstrapped_demos=4)
compiled = optimizer.compile(program, trainset=trainset)
compiled.save("./compiled/program.json")
Use this skill when:
See optimization.md for:
.save() / .load(), never raw pickle)uv: uv pip for installs, uv run for scripts.save() / .load(): Never use raw pickle for DSPy programsdspy.LM: Never use deprecated dspy.OpenAI or dspy.settings.configure.with_inputs() on dspy.Example