Modify prompts while preserving downstream regex parsing contracts.
npx skills add https://github.com/wlee075/chatbot --skill prompt-tuning-wlee075
Please help me install this Agent Skill. Skill: prompt-tuning Source: https://github.com/wlee075/chatbot/tree/main/skills/prompt_tuning Command: npx skills add https://github.com/wlee075/chatbot --skill prompt-tuning-wlee075
Safely modify prompts to prevent downstream regex parsing from breaking when templates change, reducing debugging time and state drift.
Modify prompts/templates.py with caution, ensuring any change preserves the exact output format contracts used by graph/nodes.py.
High-intent search queries and answers about installing and using this skill.
To modify prompt templates without breaking regex parsing, update prompts/templates.py while preserving the exact output format contracts relied upon by graph/nodes.py. Validate changes against threshold behaviors and ensure rubric extensions do not alter the parsing workflow.
Load-bearing parts of a prompt template include output format contracts, threshold behaviors, and context blocks that graph/nodes.py regex reflectors depend on. Modifying these specific sections risks breaking the parsing workflow and requires careful validation.
You can extend rubrics or context blocks without causing state drift by applying changes that preserve the existing output contracts. The Skill documents safe modification practices to ensure regex-based reflectors continue functioning as expected after template updates.
Safely update thresholds by following the documented safe change practices for the prompts module and graph/nodes.py parsing logic. Ensure any threshold adjustments maintain the established output contracts and validate that downstream regex reflectors still produce expected results.
Changing a prompt template causes parsing failures when modifications alter the output format contracts that downstream regex patterns in graph/nodes.py expect. Unsafe changes to load-bearing sections disrupt the parsing workflow and produce state drift.
The best way to validate prompt changes is to test modified templates against the regex-based reflectors in graph/nodes.py, confirming that output format contracts, threshold behaviors, and rubric structures remain intact and produce expected parsing results.
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