dspy-optimizer-selection — independently scanned and version-tracked by SaferSkills.
SaferSkills independently audited dspy-optimizer-selection (Agent Skill) and scored it 100/100 (green). The audit ran 55 deterministic rules across Security, Supply Chain, Maintenance, Transparency, and Community; it found 0 high-severity and 0 lower-severity findings. The full rule-by-rule trace and per-finding evidence are below. Free, methodology-open.
Findings & checks · 0 flagged
Every scanned point with the score it earned and what moved between them.
First recorded scan — no prior version to compare against.
The primary manifest — the file an agent reads to learn what this artifact does.
Choose the smallest DSPy optimizer that matches the data, budget, and artifact being tuned. Establish a baseline before compiling anything.
| Need | Start with | Notes |
|---|---|---|
| Include a few labeled examples | dspy.LabeledFewShot | Random labeled demos; useful as a baseline |
| About 10 examples | dspy.BootstrapFewShot | Teacher-generated demos with metric filtering |
| 50+ examples and stronger demo search | dspy.BootstrapFewShotWithRandomSearch | Searches multiple demo sets; alias: dspy.BootstrapRS |
| Per-input nearest demos | dspy.KNNFewShot | Retrieves nearby examples before bootstrapping |
| Instruction-only hill climbing | dspy.COPRO | Coordinate ascent over instructions |
| Instruction and demo search | dspy.MIPROv2 | Bayesian search; install dspy[optuna] |
| Mini-batch introspective rules or demos | dspy.SIMBA | Uses output variability and self-reflection |
| Rich textual feedback and trace reflection | dspy.GEPA | Metric must accept five arguments |
| Distill prompts into model weights | dspy.BootstrapFinetune | Requires a fine-tunable LM and set_lm() |
| Combine candidate programs | dspy.Ensemble | Trades inference cost for robustness |
| Sequence prompt and weight optimization | dspy.BetterTogether | Meta-optimizer for configurable optimizer chains |
Use dspy-bootstrap-fewshot for the first optimization pass. Move to BootstrapFewShotWithRandomSearch when enough examples are available to search multiple demo sets.
Use dspy-miprov2-optimizer for instruction and demonstration search. Install its optional dependency first:
pip install -U "dspy[optuna]>=3.2.1,<3.3"Use dspy-gepa-reflective when failures can be described with actionable text. Use dspy-simba-optimizer for a smaller mini-batch introspective loop with numeric metrics.
Use dspy-better-together when a fine-tunable LM is available and prompt optimization alone has plateaued.
~30 seconds. Free. No account. Every finding cites a rule and a line of evidence.