Agent skill
dspy-1-signatures
Sub-skill of dspy: 1. Signatures.
Install this agent skill to your Project
npx add-skill https://github.com/vamseeachanta/workspace-hub/tree/main/.claude/skills/_archive/ai/prompting/dspy/1-signatures
SKILL.md
1. Signatures
1. Signatures
Basic Signatures:
import dspy
# Configure LLM
lm = dspy.OpenAI(model="gpt-4", max_tokens=1000)
dspy.settings.configure(lm=lm)
# Inline signature (simple)
classify = dspy.Predict("document -> category")
result = classify(document="The mooring line tension exceeded limits.")
print(result.category)
# Class-based signature (recommended)
class SentimentAnalysis(dspy.Signature):
"""Analyze the sentiment of engineering feedback."""
feedback = dspy.InputField(desc="Engineering feedback or review text")
sentiment = dspy.OutputField(desc="Sentiment: positive, negative, or neutral")
confidence = dspy.OutputField(desc="Confidence score 0-1")
# Use signature
analyzer = dspy.Predict(SentimentAnalysis)
result = analyzer(feedback="The mooring design passed all safety checks.")
print(f"Sentiment: {result.sentiment}, Confidence: {result.confidence}")
Complex Signatures with Multiple Fields:
class EngineeringAnalysis(dspy.Signature):
"""Analyze an engineering report and extract key insights."""
report_text = dspy.InputField(
desc="Full text of the engineering report"
)
domain = dspy.InputField(
desc="Engineering domain (offshore, structural, mechanical)"
)
summary = dspy.OutputField(
desc="Concise 2-3 sentence summary of findings"
)
key_metrics = dspy.OutputField(
desc="List of key metrics mentioned with values"
)
risk_factors = dspy.OutputField(
desc="Identified risk factors and concerns"
)
recommendations = dspy.OutputField(
desc="Actionable recommendations from the report"
)
confidence_level = dspy.OutputField(
desc="Overall confidence in analysis: high, medium, or low"
)
# Create predictor
report_analyzer = dspy.Predict(EngineeringAnalysis)
# Analyze report
result = report_analyzer(
report_text="""
The mooring analysis for Platform Alpha shows maximum tensions
of 2,450 kN under 100-year storm conditions. Safety factors
range from 1.72 to 2.15 across all lines. Line 3 shows the
lowest margin at the fairlead connection. Fatigue life estimates
indicate 35-year service life, exceeding the 25-year requirement.
Chain wear measurements show 8% diameter loss after 5 years.
""",
domain="offshore"
)
print(f"Summary: {result.summary}")
print(f"Key Metrics: {result.key_metrics}")
print(f"Risk Factors: {result.risk_factors}")
print(f"Recommendations: {result.recommendations}")
Recommended Agent Skills
Expand your agent's capabilities with these related and highly-rated skills.
gsd-complete-milestone
Archive completed milestone and prepare for next version
gsd-reapply-patches
Reapply local modifications after a GSD update
gsd-verify-work
Validate built features through conversational UAT
gsd-thread
Manage persistent context threads for cross-session work
clinical-trial-protocol
Generate clinical trial protocols for medical devices or drugs through a modular, waypoint-based architecture with research-only and full protocol modes.
single-cell-rna-qc
Performs quality control on single-cell RNA-seq data (.h5ad or .h5 files) using scverse best practices with MAD-based filtering and comprehensive visualizations.
Didn't find tool you were looking for?