Recipe Cycle Testing

Create, Run, Judge, Evaluate, and Fix recipes iteratively

The Recipe Cycle Testing workflow helps you iteratively improve your AI agent recipes.

Diagram

Quick Start

Create a Recipe

bash

praisonai recipe create "Research AI agent frameworks"

Run with Trace

bash

praisonai recipe run my-recipe --save --name run1

Judge the Output

bash

praisonai recipe judge run1 --yaml my-recipe/agents.yaml

Apply Fixes

bash

praisonai recipe apply judge_plan.yaml --confirm

Repeat
Run cycles 2-5 until score reaches target threshold.

Common Errors & Fixes

Tool Result Truncation

Error: Tool 'tavily_search' result was truncated

Cause: Large search results exceed context window

Fix: – Use --chunked flag when judging – Reduce max_results in tool calls – Add instructions to summarize results

Low Task Achievement Score

Error: Task Achievement: 5.0/10

Cause: Agent output doesn’t match expected format

Fix: – Add clearer expected_output in steps – Include specific format requirements in action – Add verification instructions to backstory

Hallucination Detected

Error: Hallucination: 3.0/10

Cause: Agent generates unverified information

Fix: – Add instruction to cite sources – Use include_answer: true in tavily_search – Add verification step in backstory

Missing Goal

Error: Recipe Goal: Not specified

Cause: No goal field in agents.yaml

Fix: Add a clear, measurable goal:

yaml

goal: Research and compare top 5 AI frameworks

Tool-Specific Fixes

tavily_search

Issue: Results truncated or incomplete

yaml

# Fix: Add specific instructions
agents:
  researcher:
    backstory: |
      Expert researcher. Always verify completeness
      of search results before finalizing output.
      Cite sources for all claims.

search_web

Issue: Fallback to DuckDuckGo with limited results

yaml

# Fix: Set TAVILY_API_KEY for better results
metadata:
  requires:
    env:
      - TAVILY_API_KEY

write_file

Issue: Approval required but not configured

yaml

# Fix: Add approve field
approve:
  - write_file

Cycle Results Example

Cycle	Score	Fixes Applied	Key Issue
1	7.5/10	2	Tool truncation warnings
2	6.67/10	6	Hallucination detection
3	4.5/10	5	Output format issues
4	4.5/10	5	Verification needed
5	4.5/10	–	Stable, needs manual tuning

Best Practices

Start Simple

Use 1 agent for simple tasks. Add agents only when needed.

Be Specific

Use concrete values in actions, not variables.

Set Goals

Always include a measurable goal field.

Verify Output

Add verification instructions to agent backstory.

CLI Reference

bash

# Create recipe
praisonai recipe create "goal" [--no-optimize]

# Run with trace
praisonai recipe run <name> --save --name <trace-id>

# Judge trace
praisonai recipe judge <trace-id> --yaml <file> [--chunked]

# Apply fixes
praisonai recipe apply <plan.yaml> --confirm

# Optimize (automated cycles)
praisonai recipe optimize <path> --iterations 5 --threshold 8.0