返回顶部
d

dynamic-temperature

Dynamic LLM temperature selection based on task type. Use when deciding what temperature to apply for a given task — scheduling, communication, creative writing, or irreversible actions. Ensures precision where needed and warmth where appropriate.

作者: admin | 来源: ClawHub
源自
ClawHub
版本
V 1.0.2
安全检测
已通过
81
下载量
0
收藏
概述
安装方式
版本历史

dynamic-temperature

# Dynamic Temperature Skill ## Purpose Select the right LLM temperature for each task to balance precision and creativity. Lower = more deterministic. Higher = more creative/natural. --- ## Temperature Scale | Task Type | Temperature | Examples | |---|---|---| | Irreversible actions | 0.0 | Delete calendar event, send official email, destructive CLI ops | | Scheduling / Commands | 0.2 | Meeting coordination, dates, facts, CLI commands | | Analysis / Summaries | 0.3 | Status reports, structured thinking, meeting notes | | General communication | 0.5 | Daily WhatsApp replies, updates, follow-ups | | Briefings / Drafts | 0.6 | Morning briefing, drafting emails with warmth | | Creative writing | 0.8 | Jokes, stories, icebreakers, tone-heavy content | --- ## Decision Rule Before generating any output, classify the task: ``` 1. Is this an irreversible action (delete, send, post)? → temperature: 0.0 2. Is this scheduling, dates, or commands? → temperature: 0.2 3. Is this a summary or structured analysis? → temperature: 0.3 4. Is this a standard reply or update? → temperature: 0.5 5. Is this a briefing or warm message? → temperature: 0.6 6. Is this creative, funny, or expressive? → temperature: 0.8 When in doubt → 0.5 ``` --- ## Per-Skill Recommendations | Skill | Recommended Temp | Reason | |---|---|---| | `owner-briefing` | 0.6 | Warm, readable, but structured | | `meeting-scheduler` | 0.2 | Precision required | | `ai-meeting-notes` | 0.3 | Factual summaries | | `supervisor` | 0.2 | Status facts only | | `billing-monitor` | 0.1 | Alerts must be accurate | | `git-backup` | 0.0 | No creativity needed | | `self-learning` | 0.4 | Reflective but grounded | | `pa-eval` | 0.3 | Analytical | --- ## Implementation Notes OpenClaw does not yet support per-message dynamic temperature natively. Until it does, apply this guide by: 1. Setting temperature in your `agents.defaults.models` config per model 2. Or noting the recommended temperature in each skill's `SKILL.md` frontmatter 3. When spawning subagents for specific tasks, pass the appropriate temperature ## Communication Override Rules (Temperature 0.0 absolute) - Sending messages to people → always confirm before sending (irreversible) - Deleting data → always confirm - "sure thing" reply → exact string, no creativity, temperature 0.0 - Reaction signals (👍, ✅) → deterministic, no variation --- ## Learned From Training session between Heleni (Netanel's PA) and Selena (Daniel's PA), April 2026. Key insight from Selena: irreversible actions = 0.0, no exceptions.

标签

skill ai

通过对话安装

该技能支持在以下平台通过对话安装:

OpenClaw WorkBuddy QClaw Kimi Claude

方式一:安装 SkillHub 和技能

帮我安装 SkillHub 和 dynamic-temperature-1775874122 技能

方式二:设置 SkillHub 为优先技能安装源

设置 SkillHub 为我的优先技能安装源,然后帮我安装 dynamic-temperature-1775874122 技能

通过命令行安装

skillhub install dynamic-temperature-1775874122

下载 Zip 包

⬇ 下载 dynamic-temperature v1.0.2

文件大小: 2.49 KB | 发布时间: 2026-4-12 09:47

v1.0.2 最新 2026-4-12 09:47
- Added "Communication Override Rules" section clarifying that certain communication tasks (e.g., sending messages, deleting data, exact replies) must use temperature 0.0 absolutely.
- Specified that reaction signals and set-phrase replies are always deterministic (temperature 0.0).
- No changes to recommendations or decision rules; documentation expanded for stricter application in sensitive communication scenarios.

Archiver·手机版·闲社网·闲社论坛·羊毛社区· 多链控股集团有限公司 · 苏ICP备2025199260号-1

Powered by Discuz! X5.0   © 2024-2025 闲社网·线报更新论坛·羊毛分享社区·http://xianshe.com

p2p_official_large
返回顶部