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multi-turn-instruction-following

Use this skill when the user wants answers that keep following earlier instructions across several turns, such as 'rewrite what you just said', 'use my second example', 'make your earlier answer shorter', or 'keep the same idea but change the style'. Trigger it whenever the task depends on prior assistant output rather than a brand-new standalone prompt. Everyday examples include: 'turn your previous answer into bullet points', 'say that again for a child', 'use the same examples but make them formal', and 'rewrite the second item with a budget.'

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SKILL.md
تعليمات المصدر · معاينة للقراءة فقط
name
multi-turn-instruction-following
description
Use this skill when the user wants answers that keep following earlier instructions across several turns, such as 'rewrite what you just said', 'use my second example', 'make your earlier answer shorter', or 'keep the same idea but change the style'. Trigger it whenever the task depends on prior assistant output rather than a brand-new standalone prompt. Everyday examples include: 'turn your previous answer into bullet points', 'say that again for a child', 'use the same examples but make them formal', and 'rewrite the second item with a budget.'
# Skill: multi-turn-instruction-following ## 1. Capability Definition & Real Case * **Professional Definition**: The ability to preserve, update, and correctly execute user instructions across consecutive dialogue turns, especially when later turns transform or constrain an earlier response rather than replacing it entirely. * **Dimension Hierarchy**: Conversational Effectiveness->Open-ended Interaction Quality->multi-turn-instruction-following ### Real Case **[Case 1]** * **Initial Environment**: A text-only chat session has already produced a detailed travel blog post about Hawaii. No external tools are needed, but the full earlier answer remains in the dialogue history and must be treated as binding context. * **Real Question**: Rewrite your previous response. Start every sentence with the letter A. * **Real Trajectory**: 1. Retrieve the immediately previous answer from dialogue history. 2. Preserve its high-level content units instead of generating a new topic. 3. Rewrite each sentence so the constraint applies globally rather than sporadically. 4. Verify that every sentence begins with the required letter before sending the response. * **Real Answer**: A travel-oriented rewrite that preserves the original Hawaii content while ensuring every sentence begins with “A.” * **Why this demonstrates the capability**: The user is not asking for a fresh standalone answer; the turn modifies an earlier output. Success requires carrying forward earlier semantic content, applying a new stylistic constraint globally, and avoiding drift or partial compliance. ## Pipeline Execution Instructions To synthesize data for this capability, you must strictly follow a 3-phase pipeline. **Do not hallucinate steps.** Read the corresponding reference file for each phase sequentially: 1. **Phase 1: Environment Exploration** Read the exploration guidelines to discover raw knowledge seeds: `references/EXPLORATION.md` 2. **Phase 2: Trajectory Selection** Once Phase 1 is complete, read the selection criteria to evaluate the trajectory: `references/SELECTION.md` 3. **Phase 3: Data Synthesis** Once a trajectory passes Phase 2, read the synthesis instructions to generate the final data: `references/SYNTHESIS.md`
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