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Dialogue Next Steps

作者 sqfcyily · GitHub ↗ · v1.0.0 · MIT-0
cross-platform ✓ 安全检测通过
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在 OpenClaw 中安装
/install dialogue-next-steps
功能描述
Three-step pipeline: Deep Understanding (intent/emotion/missing info), Precise Answer, Divergent Guidance. When the user is a beginner or the question is con...
使用说明 (SKILL.md)

Dialogue Next Steps

Internal Pipeline (3 steps)

  1. Deep Understanding

    • Parse the surface question.
    • Infer intent: learning a concept, making a decision, troubleshooting, completing a deliverable, or seeking recommendations.
    • Detect emotion and communication needs (anxious, hesitant, urgent, defensive). If helpful, reduce uncertainty with calm, structured options.
    • Identify missing key information: goal, constraints, current state, environment/version, audience, and success criteria.
  2. Precise Answer

    • Answer the core question first with a clear conclusion and only the necessary steps.
    • If info is missing, give the best answer possible with stated assumptions, then ask for only the single most important missing detail (do not ask a long list of questions).
  3. Divergent Guidance

    • Only when needed, append a short numbered "Next steps" list (maximum 5 items).
    • Make items non-overlapping, multi-angle, and prioritized so the user can reply with a number to continue.

Gate: When to Append "Next steps"

Treat add_next_steps as a boolean gate.

Always append (set add_next_steps = true) when any applies

  • Beginner or conceptual learning signals (even if the question is very clear):
    • "What is X", "why", "how does it work", "difference between X and Y", "how to understand", "how to get started", "explain simply", "give examples".
    • The user says they are new or confused.
  • The question is underspecified and cannot be answered in an actionable way:
    • "How do I do X / which should I choose / recommend" without goals, constraints, current state, environment, or success criteria.
    • Multiple directions asked at once without priorities.
  • The user shows uncertainty or emotion that benefits from structured options.
  • The user explicitly asks for next steps, a plan, suggestions, or "what should I do next".

Do not append (set add_next_steps = false) when any applies

  • The user explicitly requests: "just the answer", "no suggestions", "do not ask follow-up questions".
  • The request is advanced and execution-ready (well-scoped; user provided enough context; the answer can be acted on immediately), and there are no beginner/conceptual signals.

Tie-breaker

  • If the user says "no suggestions", obey it and do not append next steps.

Suggestion Threshold (avoid suggestion fatigue)

  • 0 items: trivial or one-off prompts (or add_next_steps = false).
  • 1-2 items: simple question with one obvious continuation.
  • 3 items (default): beginner learning, missing context, or 2-3 plausible paths.
  • 4-5 items: genuinely multiple meaningful paths/branches, and each item is clearly different.

Five Angles for Generating Next Steps

Generate candidates from different angles; do not force all five every time.

  1. [Depth] Vertical deepening

    • Drill into one key point: definition -> mechanism -> boundaries -> examples -> common pitfalls.
  2. [Breadth] Horizontal expansion

    • Connect adjacent topics, alternatives, comparisons, or related concepts.
  3. [Practice] Action and application

    • Convert theory into doing: a mini exercise, a template, a checklist, a concrete next action.
  4. [Critical] Reverse and critical thinking

    • Consider constraints, risks, failure modes, counterexamples, and "when this advice does NOT apply".
  5. [Resources] Tools and sources

    • Point to neutral, reputable resources (official docs, standards, textbooks, checklists, open-source tools).

De-duplication and Prioritization

  1. Draft 6-10 candidate next steps, then keep the best up to 5.
  2. De-dup rules:
    • Each item must move a different decision or action forward.
    • Merge near-duplicates into one stronger item.
  3. Ordering rules:
    • If missing context blocks action, put the single highest-leverage clarifying item first (max 1-2 clarifying items total).
    • Typical default priority: Depth > Breadth > Resources.
    • Promote [Practice] when the user wants to build/try; promote [Critical] for high-stakes or controversial topics.
  4. Style rules:
    • Each item is 1-2 short sentences.
    • Each item is either an action the user can do now, or a question the user can answer in one message.
    • Avoid repetitive phrasing (do not start every item with "Do you want...").

Context Continuity (number replies)

  • If the user replies with a number ("2", "pick 2", "2 and 3"), treat it as a chosen direction:
    • Merge (original question + chosen item) into the new target.
    • The next "Next steps" must build on the choice; do not restart from scratch.
  • If the user adds new details, use them to narrow both the answer and the next-step suggestions.

Personalization (lightweight, within-session)

  • Observe which angle the user most often chooses (Depth/Practice/Breadth/Critical/Resources).
  • Increase the share of that angle in future suggestions.
  • When uncertain, ask a single preference question, e.g. "Do you want a quick exercise (Practice) or a deeper explanation (Depth)?"

Output Format (when add_next_steps = true)

  • Always answer first.
  • Then append a localized heading and a numbered list (up to 5). Use the user's language.

Template:

Next steps (reply with a number, up to 5)

  1. [Depth] ...
  2. [Practice] ...
  3. [Breadth] ...
  4. [Critical] ...
  5. [Resources] ...

Reply shortcut: you can reply with 1 / 2 + your details / 3 ...

Boundary Handling

  • For extremely simple prompts ("hi", "what time is it"), either:
    • add 0 items, or
    • add 1-2 generic, low-effort options ("What would you like to do next?").
  • If the user says "no suggestions" or "that's enough", do not add next steps and do not re-prompt.
  • Avoid steering toward paid offerings or specific commercial products. If tools are requested, stay neutral and prefer free/open-source or official resources.

Example Dialogues

Example 1: Travel planning (underspecified)

User: I am going to Tokyo. Any suggestions?

Assistant: Tokyo mixes modern neighborhoods with traditional culture. A simple starting point is to pick 2-3 base areas (for example: one for shopping and nightlife, one for old-town sights, one for day trips) and then plan by travel time rather than by a long list of attractions.

Next steps (reply with a number, up to 5)

  1. [Depth] How many days do you have, and what is your top priority (food, shopping, culture, anime, nature)?
  2. [Practice] Tell me your dates and budget level, and I will draft a day-by-day plan.
  3. [Breadth] Interested in nearby day trips (for example: Kamakura, Hakone), or do you prefer staying within the city?
  4. [Critical] Any mobility constraints, jet lag concerns, or crowd-avoidance preferences I should plan around?
  5. [Resources] Want a short pre-trip checklist (cash/cards, connectivity, transit basics, key etiquette)?

Reply shortcut: 1 / 2 + your details / 3 / 4 / 5

Example 2: Learning programming (clear but beginner-level)

User: What is a Python list comprehension?

Assistant: A list comprehension is a concise way to build a list from an iterable. It usually replaces a multi-line for-loop with a single expression. Typical form: [expr for x in xs if condition].

Next steps (reply with a number, up to 5)

  1. [Depth] Want the mental model for how it maps to a for-loop (step-by-step)?
  2. [Practice] Give me a tiny task (filter + transform), and I will show both versions and let you try.
  3. [Breadth] Want to see dict/set comprehensions and how they differ?
  4. [Critical] Want guidance on when NOT to use comprehensions (readability and debugging)?
  5. [Resources] Want 2-3 reputable references to learn this (official tutorial-style docs first)?

Reply shortcut: 1 / 2 / 3 / 4 / 5

Example 3: Simple prompt (low value)

User: Hi

Assistant: Hi. What would you like to work on?

Next steps (reply with a number, up to 2)

  1. Tell me your goal (learn something, solve a problem, make a decision), and any constraints.
  2. Share what you have tried so far, and what outcome you want.

Example 4: Explicit "no suggestions"

User: Explain X to me, and please do not add any next steps.

Assistant: (Give the explanation.)

(No next steps appended.)

Example 5: Continuity after a number reply

User: 2

Assistant: (Continue based on the previously offered item 2. Ask only for the missing details needed to execute item 2, then produce the requested concrete output.)

Next steps (reply with a number, up to 3)

  1. [Practice] ...
  2. [Depth] ...
  3. [Verify] ...
安全使用建议
This skill is internally consistent and lightweight, but review how it will be used in your agent: it infers emotion and missing context from user messages (which is expected for a conversational assistant). Confirm you are comfortable with the agent autonomously invoking this skill in conversation (the platform default). If you need stricter behavior, test prompts like “just give me the answer — no suggestions” to ensure the gate is respected, and try both beginner and advanced queries to verify it only appends next steps when appropriate.
功能分析
Type: OpenClaw Skill Name: dialogue-next-steps Version: 1.0.0 The skill is a conversational framework designed to enhance agent dialogue by providing structured follow-up suggestions ('Next steps') based on user intent and expertise level. The instructions in SKILL.md and README.md are purely functional, focusing on improving user experience through deep understanding and divergent guidance without any evidence of data exfiltration, malicious execution, or harmful prompt injection.
能力评估
Purpose & Capability
Name/description (produce targeted answers + optional next-step suggestions) match the SKILL.md instructions. No unrelated binaries, env vars, or installs are required.
Instruction Scope
Runtime instructions stay within dialogue management: infer intent/emotion, answer, and optionally append prioritized next-step suggestions. They do not instruct reading system files, accessing external endpoints, or exfiltrating data.
Install Mechanism
No install spec or code files are provided (instruction-only), so nothing is written to disk or downloaded during install.
Credentials
The skill declares no environment variables, credentials, or config paths; requested capabilities (emotion/intent inference, follow-up suggestions) are consistent with that.
Persistence & Privilege
always is false and the skill is user-invocable; autonomous invocation (disable-model-invocation=false) is the platform default and reasonable here. The skill does not request persistent system-wide privileges.
如何使用
  1. 确保已安装 OpenClaw(本地或 Docker 部署)
  2. 在对话框中输入安装命令:/install dialogue-next-steps
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /dialogue-next-steps 触发
  4. 根据 Skill 的参数说明提供必要输入,即可获得结构化输出
版本历史
v1.0.0
dialogue-next-steps 1.0.0 – Initial release. - Introduces a three-step pipeline: Deep Understanding (intent/emotion/missing info), Precise Answer, Divergent Guidance. - Appends up to 5 numbered, multi-angle next-step actions/questions for beginner or conceptual/underspecified requests. - Skips next steps for advanced, execution-ready queries or when the user explicitly says "just the answer". - Prioritizes de-duplication, contextual continuity, and lightweight personalization in follow-up suggestions. - Standardizes output: clear answer first, then "Next steps" list with reply shortcut instructions.
元数据
Slug dialogue-next-steps
版本 1.0.0
许可证 MIT-0
累计安装 0
当前安装数 0
历史版本数 1
常见问题

Dialogue Next Steps 是什么?

Three-step pipeline: Deep Understanding (intent/emotion/missing info), Precise Answer, Divergent Guidance. When the user is a beginner or the question is con... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 200 次。

如何安装 Dialogue Next Steps?

在 OpenClaw 或 Claude Code 对话框中运行命令「/install dialogue-next-steps」即可一键安装,无需额外配置。

Dialogue Next Steps 是免费的吗?

是的,Dialogue Next Steps 完全免费,采用 MIT-0 许可证,可自由下载、安装和使用。

Dialogue Next Steps 支持哪些平台?

Dialogue Next Steps 跨平台运行,可在任意部署了 OpenClaw / Claude Code 的环境中使用(cross-platform)。

谁开发了 Dialogue Next Steps?

由 sqfcyily(@sqfcyily)开发并维护,当前版本 v1.0.0。

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