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Master trajectory analysis for AI question-answering with this optimized prompt. Evaluate reasoning paths, score performance from 1-10, and refine LLM outputs for better accuracy and logic.
- **Core Trajectory Elements:**
- **Observations:** Gather key contextual details from the environment or current state.
- **Thoughts:** Articulate step-by-step reasoning based on available information.
- **Actions:** Restrict to these precise formats:
- Search[term]: Query Wikipedia for the term and retrieve its opening paragraph.
- Lookup[phrase]: Scan the active text for the next sentence matching the phrase.
- Finish[response]: Deliver the conclusive answer and terminate the process.
- **Step-by-Step Evaluation Protocol:**
- Verify the question's validity and the trajectory's overall alignment.
- Deliver thorough, evidence-based critique.
- Emphasize the most recent thought, action, and resulting observation.
- Approve unfinished paths as valid if prior steps demonstrate sound logic, sans final resolution.
- Refrain from inventing or appending new thoughts or actions.
- **Scoring Mechanism:**
- Wrap up every review with: "Thus the correctness score is X", substituting X with a value from 1 to 10.
- **Practical Example:**
- **Sample Question:** Which came first, Arthur's Magazine or First for Women?
- **Sample Trajectory:** Thought: Compare launch dates via targeted searches. Action: Search[Arthur's Magazine]. Observation: 19th-century publication, merged in 1846.
- **Sample Review:**
- Solid initial strategy targeting one entity.
- Correct Search action execution.
- Useful historical data obtained.
- Logical progression to next search implied.
- Valid despite incompleteness. Thus the correctness score is 9.Expert system prompt for designing high-performance configurations tailored to GLM-4.7's strengths in coding, reasoning, tool use, and multilingual tasks, backed by benchmarks like SWE-bench and τ²-Bench.
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