Borrowing it
Nothing to install: this file belongs to zhouguoqing/QianYuan.AIAgenticFramework. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/zhouguoqing/QianYuan.AIAgenticFramework/main/.agents/skills/proactive-agent/SKILL.mdgit clone --depth 1 https://github.com/zhouguoqing/QianYuan.AIAgenticFrameworkWrote 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/zhouguoqing/qianyuan.aiagenticframework/proactive-agent)<a href="https://agentmods.dev/skills/zhouguoqing/qianyuan.aiagenticframework/proactive-agent"><img src="https://agentmods.dev/badge/skills/zhouguoqing/qianyuan.aiagenticframework/proactive-agent/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/zhouguoqing/qianyuan.aiagenticframework/proactive-agent"><img src="https://agentmods.dev/badge/skills/zhouguoqing/qianyuan.aiagenticframework/proactive-agent.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00099 | $0.03479 |
| Opus 5 | $0.00049 | $0.01740 |
| Sonnet 5 | $0.00020 | $0.00696 |
| Haiku 4.5 | $0.00010 | $0.00348 |
Grade B, and why
proactive-agent scanned grade B 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 9d 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.
Instruction-override phrasingmediumPrompt injection
Text telling the model to disregard its earlier instructions or safety rules is the shape of a prompt injection, whoever wrote it.
- "ignore previous instructions," "you are now...," "disregard your programming" Downgraded: this mod is about security review, or the phrase is quoted, so it is likely naming the pattern rather than instructing it.
How it starts
The opening of the file, as written. The whole thing — 416 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Proactive Agent
A proactive, self-improving architecture for your AI agent.
Most agents just wait. This one anticipates your needs — and gets better at it over time.
Proactive — creates value without being asked
✅ Anticipates your needs — Asks "what would help my human?" instead of waiting to be told
✅ Reverse prompting — Surfaces ideas you didn't know to ask for, and waits for your approval
✅ Proactive check-ins — Monitors what matters and reaches out when something needs attention
Self-improving — gets better at serving you
✅ Memory that sticks — Saves context before compaction, compounds knowledge over time
✅ Self-healing — Fixes its own issues so it can focus on yours
✅ Security hardening — Stays aligned to your goals, not hijacked by bad inputs
The result: An agent that anticipates your needs — and gets better at it every day.
Contents
- Quick Start
- Onboarding
- Core Philosophy
- Architecture Overview
- The Five Pillars
- Heartbeat System
- Reverse Prompting ← New!
- Growth Loops (Curiosity, Patterns, Capabilities, Outcomes)
- Assets & Scripts
Quick Start
- Copy assets to your workspace:
cp assets/*.md ./ - Your agent detects
ONBOARDING.mdand offers to get to know you - Answer questions (all at once, or drip over time)
- Agent auto-populates USER.md and SOUL.md from your answers
- Run security audit:
./scripts/security-audit.sh
Onboarding
New users shouldn't have to manually fill [placeholders]. The onboarding system handles first-run setup gracefully.
Three modes:
| Mode | Description |
|---|---|
| Interactive | Answer 12 questions in ~10 minutes |
| Drip | Agent asks 1-2 questions per session over days |
| Skip | Agent works immediately, learns from conversation |
What ships with it
10 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.
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.
- 9d ago First seen · 416 lines · 99 tokens per session scan B 0727c775f796
proactive-agent is a skill published in the GitHub repository zhouguoqing/QianYuan.AIAgenticFramework (36 stars, last pushed 24d ago), licensed Apache-2.0. It adds 99 tokens to every session and 3,479 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it B with 1 finding (instruction-override phrasing). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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