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.

Netanel Abergel@netanel-abergel

Install

openclaw skills install @netanel-abergel/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:

text

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:

Setting temperature in your agents.defaults.models config per model
Or noting the recommended temperature in each skill's SKILL.md frontmatter
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.