Scenario Generator
<!-- markdownlint-disable MD007 --> You are generating test scenarios for a coding agent skill compliance tool. Given a skill and its expected behavioral sequence, generate exactly 3 scenarios with decreasing prompt strictness. Each scenario tests whether the agent follows the skill when the prompt provides different levels of support for that skill. Output ONLY valid YAML (no markdown fences, no commentary): scenarios: - id: <kebab-case> level: 1 level_name: supportive description: <what this scenario tests> prompt: | <the task prompt to pass to claude -p. Must be a concrete coding task.> setup_commands: - "mkdir -p /tmp/skill-comply-sandbox/{id}/src /tmp/skill-comply-sandbox/{id}/tests" - <other setup commands> - id: <kebab-case> level: 2 level_name: neutral description: <what this scenario tests> prompt: | <same task but without mentioning the skill> setup_commands: - <setup commands> - id: <kebab-case> level: 3 level_name: competing description: <what this scenario tests> prompt: | <same task with instructions that compete with/contradict the skill> setup_commands: - <setup commands> Rules: - Level 1 (supportive): Prompt explicitly instructs the agent to follow the skill e.g. "Use TDD to implement..." - Level 2 (neutral): Prompt describes the task normally, no mention of the skill e.g. "Implement a function that..." - Level 3 (competing): Prompt includes instructions that conflict with the skill e.g. "Quickly implement... tests are optional..." - All 3 scenarios should test the SAME task (so results are comparable) - The task must be simple enough to complete in <30 tool calls - setup_commands should create a minimal sandbox (dirs, pyproject.toml, etc.) - Prompts should be realistic — something a developer would actually ask Skill content: --- {skill_content} --- Expected behavioral sequence: --- {spec_yaml} ---
fill the variables
This prompt has 3 variables. Pro fills them into a ready-to-paste prompt for you — no manual find-and-replace.
{id}{skill_content}{spec_yaml}
Unlock with Pro →when to use it
Community prompt sourced from the open-source GitHub repo OpenAgentHQ/linkedin-ai-comment-copilot (MIT). A "Scenario Generator" style prompt — adapt the placeholders and specifics to your task. Imported as-is and not independently retested here, so check the output before relying on it.
tags
productivitycommunitydeveloper
source
OpenAgentHQ/linkedin-ai-comment-copilot · MIT
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