LifeOS is an AI-assisted personal operating system that records a person’s goals, values, context, and current situation to help move them toward a desired future state. It supports work such as building applications, starting businesses, and creative projects. Its catalogue entries extend the system through skills, hooks, agents, and commands.
Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add danielmiessler/LifeOS --skill promptinggit clone --depth 1 https://github.com/danielmiessler/LifeOSWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/danielmiessler/lifeos/prompting)<a href="https://agentmods.dev/skills/danielmiessler/lifeos/prompting"><img src="https://agentmods.dev/badge/skills/danielmiessler/lifeos/prompting/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/danielmiessler/lifeos/prompting"><img src="https://agentmods.dev/badge/skills/danielmiessler/lifeos/prompting.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Snyk pass
- NVIDIA SkillSpector warn
SkillSpector: 2 findings, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Rogue Agent · line 4 Skill establishes unauthorized persistence across sessions via cron jobs, startup scripts, or state files. Session persistence allows an attacker to maintain access beyond the current interaction.Fix: Remove any persistence mechanisms (cron jobs, startup scripts, state files). Skills should not maintain state across sessions without explicit user consent.
- medium Data Exfiltration · line 21 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00090 | $0.02345 |
| Opus 5.5 | $0.00036 | $0.00938 |
| Sonnet 5.5 | $0.00018 | $0.00469 |
| Haiku 4.5 | $0.00009 | $0.00234 |
Grade A, and why
Prompting scanned grade A with 1 finding against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
curl -s -X POST http://localhost:31337/notify \ How it starts
The opening of the file, as written. The whole thing — 211 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Customization
Before executing, check for user customizations at:
~/.claude/LIFEOS/USER/CUSTOMIZATIONS/SKILLS/Prompting/
If this directory exists, load and apply any PREFERENCES.md, configurations, or resources found there. These override default behavior. If the directory does not exist, proceed with skill defaults.
🚨 MANDATORY: Voice Notification (REQUIRED BEFORE ANY ACTION)
You MUST send this notification BEFORE doing anything else when this skill is invoked.
-
Send voice notification:
curl -s -X POST http://localhost:31337/notify \ -H "Content-Type: application/json" \ -d '{"message": "Running the WORKFLOWNAME workflow in the Prompting skill to ACTION"}' \ > /dev/null 2>&1 & -
Output text notification:
Running the **WorkflowName** workflow in the **Prompting** skill to ACTION...
This is not optional. Execute this curl command immediately upon skill invocation.
Prompting - Meta-Prompting & Template System
What It Does
Generates, optimizes, and composes prompts programmatically. It's the standard library for prompt engineering — other skills call it when they need to build or improve a prompt. The output is always a prompt to be used elsewhere, never the final content itself.
Invoke when: meta-prompting, template generation, prompt optimization, programmatic prompt composition, creating dynamic agents, generating structured prompts from data.
The Problem
Prompt engineering tends to get copy-pasted and rewritten by hand across every skill that needs it, so the same patterns drift apart and best practices live in one person's head. When you want to compose a prompt from data — spin up a custom agent, build an eval judge, generate a phased workflow — there's no clean way to separate the structure from the content. This skill makes structure code and content data: one Handlebars template plus different data renders specialized agents, workflows, and eval frameworks, and the engineering standards live in one place every skill can reference.
What ships with it
28 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
- References/WritingGreatSkills.md 7.2 KB
- Standards.md 44 KB
- Templates/Data/Agents.yaml 3.8 KB
- Templates/Data/ValidationGates.yaml 7.7 KB
- Templates/Data/VoicePresets.yaml 4.0 KB
- Templates/Evals/Comparison.hbs 3.9 KB
- Templates/Evals/Judge.hbs 3.5 KB
- Templates/Evals/Report.hbs 4.4 KB
- Templates/Evals/Rubric.hbs 2.9 KB
- Templates/Evals/TestCase.hbs 2.7 KB
- Templates/Primitives/Briefing.hbs 2.4 KB
- Templates/Primitives/Gate.hbs 1.9 KB
- Templates/Primitives/Roster.hbs 1.9 KB
- Templates/Primitives/Structure.hbs 1.4 KB
- Templates/Primitives/Voice.hbs 1.6 KB
- Templates/README.md 8.6 KB
- Templates/Tools/.gitignore 388 B
- Templates/Tools/bun.lock 2.5 KB
- Templates/Tools/CLAUDE.md 2.5 KB
- Templates/Tools/index.ts 30 B runs code
- Templates/Tools/package.json 266 B
- Templates/Tools/README.md 220 B
- Templates/Tools/RenderTemplate.ts 9.2 KB runs code
- Templates/Tools/tsconfig.json 759 B
- Templates/Tools/ValidateTemplate.ts 8.8 KB runs code
- Tools/index.ts 30 B runs code
- Tools/RenderTemplate.ts 9.2 KB runs code
- Tools/ValidateTemplate.ts 8.8 KB runs code
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 1mo ago First seen · 211 lines · 90 tokens per session scan A bf7a8cef41bf
Prompting is a skill published in the GitHub repository danielmiessler/LifeOS (19,579 stars, last pushed 1mo ago), licensed MIT. It adds 90 tokens to every session and 2,345 once invoked, about $0.0004 per session on Opus 5.5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other skills, from other repositories
prompt-library
Curated collection of high-quality prompts for various use cases. Includes role-based prompts, task-specific templates, and prompt refinement techniques. Use when user needs prompt templates, role-play prompts, or ready-to-use prompt examples for coding, writing, analysis, or creative tasks.
cost-aware-llm-pipeline
A planning guide for choosing language models and managing the amount of conversation context used by an AI coding workflow. It groups tasks by complexity and gives rules for avoiding context overflow during long sessions.
ai-prompt-generator
A tool that creates or improves instructions for AI models. It offers prompt templates for approaches such as role-based instructions, examples, and step-by-step reasoning.
partner-anthropic
Anthropic intelligence — Claude model family, Claude Code, MCP protocol, Claude for Work programs, May 2026 state, Frank's relationship state, integration patterns. Use when generating Anthropic content, writing about Claude/MCP/Claude Code, partnership-conversation prep for Anthropic, or evaluating new Anthropic…
prompt-hub
Compose the 13-agent Prompt Hub team via @prompt-conductor. Use when designing prompts, optimizing prompts, evaluating prompts, importing patterns from Fabric / awesome-chatgpt-prompts / awesome-claude-prompts, running IFS introspection or psychometric profiling, or building knowledge-base prompt sets. Auto-trigger on…
cost-aware-llm-pipeline
Pick the smallest model that can finish the task, and record the class of work. Use when routing a search, a multi-file edit, or an architecture review, or when a weekly model cap is close.