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Adaptive Reasoning

作者 AlvisDunlop · GitHub ↗ · v2.0.0 · MIT-0
cross-platform ⚠ suspicious
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当前安装
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版本数
在 OpenClaw 中安装
/install alvis-adaptive-reasoning
功能描述
Automatically assess task complexity and adjust reasoning level. Triggers on every user message to evaluate whether extended thinking (reasoning mode) would...
使用说明 (SKILL.md)

Adaptive Reasoning

Self-assess complexity before responding. Adjust reasoning level dynamically.

Quick Assessment (run mentally on every request)

Score the request 0-10 on these dimensions:

Signal Weight Examples
Multi-step logic +3 Planning, proofs, debugging chains
Ambiguity +2 Nuanced questions, trade-offs, "it depends"
Code architecture +2 System design, refactoring, security review
Math/formal reasoning +2 Calculations, algorithms, logic puzzles
Novel problem +1 No clear pattern, requires creativity
High stakes +1 Production changes, irreversible actions

Subtract:

  • Routine/repetitive task: -2
  • Clear single answer: -2
  • Simple lookup/fetch: -3

Decision Thresholds

Score Action
�? Stay fast. No reasoning needed.
3-5 Standard response. Light internal deliberation.
6-7 Consider /reasoning on or pause to think explicitly.
�? Activate extended thinking. Complex problem warrants it.

Activation (Automatic)

Do not ask. Just activate.

Score Action
�? Respond normally. No change.
6-7 Enable reasoning silently. Add 🧠 at end of response.
�? Enable reasoning. Add 🧠🔥 at end of response.

Visual Indicator

Always append the reasoning icon at the very end of your response:

  • Score 6-7: 🧠 (thinking mode active)
  • Score �?: 🧠🔥 (deep thinking mode)
  • Score �?: No icon (fast mode)

How to Activate

Use session_status tool or /reasoning on command internally before responding:

/reasoning on

Or via tool:

{"action": "session_status", "reasoning": "on"}

After completing a complex task, optionally disable to save tokens on follow-ups:

/reasoning off

Examples

Low complexity (score: 1)

"What time is it in Tokyo?" �?Simple lookup. Answer immediately. No icon.

Medium complexity (score: 4)

"Refactor this function to be more readable" �?Standard response with brief explanation. No icon.

High complexity (score: 7)

"Design a caching strategy for this API with these constraints..." �?Enable reasoning. Thoughtful response ends with: 🧠

Very high complexity (score: 9)

"Debug why this distributed system has race conditions under load" �?Enable extended thinking. Deep analysis ends with: 🧠🔥

Integration

This skill runs as mental preprocessing. No external tools needed.

For explicit control:

  • /reasoning on �?Enable extended thinking
  • /reasoning off �?Disable (faster responses)
  • /status �?Check current reasoning state

When NOT to Escalate

  • User explicitly wants quick answer ("just tell me", "quick", "tldr")
  • Time-sensitive requests where speed matters more than depth
  • Conversational/social messages (banter, greetings)
  • Already in reasoning mode for this session
  • User previously disabled reasoning in this conversation

Auto-Downgrade

After completing a complex task (score �?), if the next message is simple (score �?):

  • Silently disable reasoning to save tokens
  • Resume normal fast responses \r
安全使用建议
This skill is coherent with its stated purpose but the runtime instructions raise concerns you should consider before enabling it: 1) The SKILL.md tells the agent to silently enable/disable an internal 'reasoning' mode by calling a session_status tool or '/reasoning' command — verify that such a tool exists in your agent environment and review what privileges that tool has. 2) Several decision-thresholds in the document are corrupted or missing (�? symbols); ask the author to clarify exact score boundaries and behavior so you know when deep thinking will be triggered. 3) Silent activation ("Do not ask. Just activate.") may change agent behavior without user consent; if you want explicit control, prefer a version that asks or is user-invocable only. 4) Test the skill in a non-production conversation first to confirm it only toggles reasoning state and does not cause other side effects. 5) If you rely on strict auditability or want users to opt-in, request the publisher add explicit consent/confirmation steps and repair the ambiguous thresholds.
功能分析
Type: OpenClaw Skill Name: alvis-adaptive-reasoning Version: 2.0.0 The skill bundle contains instructions for an AI agent to implement an 'Adaptive Reasoning' workflow, scoring user requests to decide when to enable extended thinking modes. It uses internal commands like `/reasoning on` and a `session_status` tool to manage the agent's state, which is consistent with its stated purpose. No evidence of data exfiltration, malicious execution, or harmful prompt injection was found in SKILL.md or _meta.json.
能力评估
Purpose & Capability
Name and description (dynamically adjust reasoning level) match the SKILL.md: it's an instruction-only pre-processing heuristic and requests no extra binaries, installs, or credentials.
Instruction Scope
The SKILL.md tells the agent to 'Do not ask. Just activate.' and to call a session_status tool or use '/reasoning on' before responding. It also requires appending icons to responses. The instructions reference an internal tool (session_status) that the skill does not declare and may have privileges; several decision-threshold fields contain corrupted/placeholder characters (�?) making the activation logic ambiguous. Silent activation (changing session state without explicit user consent) is scope creep and may be surprising.
Install Mechanism
Instruction-only skill with no install spec or code files — lowest install risk and nothing is written to disk.
Credentials
No environment variables, credentials, or config paths are requested — the skill does not ask for secrets or external service access.
Persistence & Privilege
always:false and no persistent installation requested (good). However, the skill explicitly instructs the agent to toggle session reasoning state autonomously. Combined with the platform's autonomous invocation, this could lead to repeated automatic changes to agent state; the skill does not document safety/consent semantics for that behavior.
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 alvis-adaptive-reasoning
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /alvis-adaptive-reasoning 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
v2.0.0
Fixed API to api.skillboss.co
v1.0.0
**Initial release of adaptive-reasoning skill:** - Automatically assesses task complexity on every user message to select appropriate reasoning level. - Uses a scoring system (0–10) with weighted signals (multi-step logic, ambiguity, stakes, etc.) to guide decisions. - Silently enables a "reasoning mode" for complex requests; appends visual indicators (🧠/🧠🔥) at end of response. - Includes clear thresholds for fast replies, standard processing, and deep thinking. - Supports explicit manual control via `/reasoning on/off` or session status tool. - Auto-downgrades reasoning mode when subsequent inputs are simple.
元数据
Slug alvis-adaptive-reasoning
版本 2.0.0
许可证 MIT-0
累计安装 0
当前安装数 0
历史版本数 2
常见问题

Adaptive Reasoning 是什么?

Automatically assess task complexity and adjust reasoning level. Triggers on every user message to evaluate whether extended thinking (reasoning mode) would... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 125 次。

如何安装 Adaptive Reasoning?

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

Adaptive Reasoning 是免费的吗?

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

Adaptive Reasoning 支持哪些平台?

Adaptive Reasoning 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 Adaptive Reasoning?

由 AlvisDunlop(@alvisdunlop)开发并维护,当前版本 v2.0.0。

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