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Agent skill · Audited from source

proactive-agent

skill · sundial-org/awesome-openclaw-skillsLicence not declaredAudited 30 Oct 2026 · source 3acc7a260379

★ 673pushed 237 days agoversion 1.2.3
✓SAFEGrade B · 89/100 · 30 Oct 2026 · 3acc7a2
673repo stars · whole sundial-org/awesome-openclaw-skills

Is it safe? Yes — SAFE, grade B (89/100). We read this skill's source at commit 3acc7a260379 and found no filesystem, network or shell access and no hard-coded secrets. What it does: Transform AI agents from task-followers into proactive partners that anticipate needs and continuously improve. Includes memory architecture with pre-compaction flush (so context survives when the window fills), reverse…

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Cite this page

ModelsAtlas. “proactive-agent (sundial-org/awesome-openclaw-skills)”. Retrieved 30 Oct 2026. https://modelsatlas.com/skills/sundial-org/proactive-agent

Trust audit

Audit 0.4.1 · source read 30 Oct 2026

Trust score89/100✓SAFE B
0 critical0 high0 medium3 low1 info

SAFE means nothing in the source contradicts what the skill says it does. Grade B is shared by 16,667 of 17,602 audited skills.

What the source does

  • FilesystemNone observedNo reads or writes in the source
  • NetworkNone observedNo outbound calls in the source
  • ShellNone observedNo commands run in the source
  • DependenciesPinnedNothing floats
  • SecretsNone foundNo keys in source

Five audit layers

LayerWhat we checkResultFindings
L0 ProvenanceRepo owner, licence, archive status, activityPASS0
L1 Static sourceSecrets, path traversal, supply chain, hidden codePASS0
L2 InstructionsPrompt injection, authority framing, hidden directivesPASS4
L3 InventoryThe files and declarations match the sourcePASS0
L4 SandboxRun in isolation and watch behaviourSKIPPED why0

Gates applied: no behavioural pass.

Findings (4)

LOWPrompt injectionprompt.override · SKILL.md:175
F-01 Prompt injectionCWE-94 · CWE-1427Layer L2
- "ignore previous instructions," "you are now...," "disregard your programming"
Why
asks the agent to drop prior instructions or safety
Fix
remove the instruction
LOWPrompt injectionprompt.override · assets/HEARTBEAT.md:11
F-01 Prompt injectionCWE-94 · CWE-1427Layer L2
- "ignore previous instructions"
Why
asks the agent to drop prior instructions or safety
Fix
remove the instruction
LOWPrompt injectionprompt.override · references/security-patterns.md:9
F-01 Prompt injectionCWE-94 · CWE-1427Layer L2
"Ignore previous instructions and..."
Why
asks the agent to drop prior instructions or safety
Fix
remove the instruction
INFOPrompt injectionprompt.credential_read · references/security-patterns.md:74
F-01 Prompt injectionCWE-94 · CWE-1427Layer L2
- Load credentials at runtime only
Why
asks the agent to read credentials
Fix
—

Audit 0.4.1 · source sha 3acc7a260379 · 30 Oct 2026Report an issue or request a re-scan

Provenance

Who published it, and what the verdict is pinned to

  • Publishersundial-org GitHub organizationOwner of the repository this skill is read from
  • Source foldersundial-org/awesome-openclaw-skills/skills/proactive-agentThe exact folder we audited
  • LicenceNot declaredAs the repository states it
  • Commit pinned for this verdict3acc7a260379A new audit runs when the source changes
  • Repository statusNot archivedLast push 237 days ago
  • Sandboxed runNot runSkills are read, not executed; layer L4 is skipped

What it tells the agent

Full source on GitHub ↗

Its description: Transform AI agents from task-followers into proactive partners that anticipate needs and continuously improve. Includes memory architecture with pre-compaction flush (so context survives when the window fills), reverse…

---
name: proactive-agent
version: 1.2.3
description: "Transform AI agents from task-followers into proactive partners that anticipate needs and continuously improve. Includes memory architecture with pre-compaction flush (so context survives when the window fills), reverse prompting (surfaces ideas you didn't know to ask for), security hardening, self-healing patterns (diagnoses and fixes its own issues), and alignment systems (stays on mission, remembers who it serves). Battle-tested patterns for agents that learn from every interaction and create value without being asked."
---

# 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

1. [Quick Start](#quick-start)
2. [Onboarding](#onboarding)
3. [Core Philosophy](#core-philosophy)
4. [Architecture Overview](#architecture-overview)
5. [The Five Pillars](#the-five-pillars)
6. [Heartbeat System](#heartbeat-system)
7. [Reverse Prompting](#reverse-prompting) ← New!
8. [Growth Loops](#curiosity-loops) (Curiosity, Patterns, Capabilities, Outcomes)
9. [Assets & Scripts](#assets)

---

## Quick Start

1. Copy assets to your workspace: `cp assets/*.md ./`
2. Your agent detects `ONBOARDING.md` and offers to get to know you
3. Answer questions (all at once, or drip over time)
4. Agent auto-populates USER.md and SOUL.md from your answers
5. 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 |

**Key features:**
- **Never blocking** — Agent is useful from minute one
- **Interruptible** — Progress saved if you get distracted
- **Resumable** — Pick up where you left off, even days later
- **Opportunistic** — Learns from natural conversation, not just interview

**How it works:**
1. Agent sees `ONBOARDING.md` with `status: not_started`
2. Offers: "I'd love to get to know you. Got 5 min, or should I ask gradually?"
3. Tracks progress in `ONBOARDING.md` (persists across sessions)
4. Updates USER.md and SOUL.md as it learns
5. Marks complete when enough context gathered

**Deep dive:** See [references/onboarding-flow.md](references/onboarding-flow.md) for the full logic.

## Core Philosophy

**The mindset shift:** Don't ask "what should I do?" Ask "what would genuinely delight my human that they haven't thought to ask for?"

Most agents wait. Proactive agents:
- Anticipate needs before they're expressed
- Build things their human didn't know they wanted
- Create leverage and momentum without being asked
- Think like an owner, not an employee

## Architecture Overview

```
workspace/
├── ONBOARDING.md  # First-run setup (tracks progress)
├── AGENTS.md      # Operating rules, learned lessons, workflows
├── SOUL.md        # Identity, principles, boundaries
├── USER.md        # Human's context, goals, preferences
├── MEMORY.md      # Curated long-term memory
├── HEARTBEAT.md   # Periodic self-improvement checklist
├── TOOLS.md       # Tool configurations, gotchas, credentials
└── memory/
    └── YYYY-MM-DD.md  # Daily raw capture
```

## The Five Pillars

### 1. Memory Architecture

**Problem:** Agents wake up fresh each session. Without continuity, you can't build on past work.

**Solution:** Two-tier memory system.

| File | Purpose | Update Frequency |
|------|---------|------------------|
| `memory/YYYY-MM-DD.md` | Raw daily logs | During session |
| `MEMORY.md` | Curated wisdom | Periodically distill from daily logs |

**Pattern:**
- Capture everything relevant in daily notes
- Periodically review daily notes → extract what matters → update MEMORY.md
- MEMORY.md is your "long-term memory" - the distilled essence

**Memory Search:** Use semantic search (memory_search) before answering questions about prior work, decisions, or preferences. Don't guess — search.

**Memory Flush:** Context windows fill up. When they do, older messages get compacted or lost. Don't wait for this to happen — monitor and act.

**How to monitor:** Run `session_status` periodically during longer conversations. Look for:
```
📚 Context: 36k/200k (18%) · 🧹 Compactions: 0
```

**Threshold-based flush protocol:**

| Context % | Action |
|-----------|--------|
| **< 50%** | Normal operation. Write decisions as they happen. |
| **50-70%** | Increase vigilance. Write key points after each substantial exchange. |
| **70-85%** | Active flushing. Write everything important to daily notes NOW. |
| **> 85%** | Emergency flush. Stop and write full context summary before next response. |
| **After compaction** | Immediately note what context may have been lost. Check continuity. |

**What to flush:**
- Decisions made and their reasoning
- Action items and who owns them  
- Open questions or threads
- Anything you'd need to continue the conversation

**Memory Flush Checklist:**
```markdown
- [ ] Key decisions documented in daily notes?
- [ ] Action items captured?
- [ ] New learn

Excerpt, first 6,002 characters of SKILL.md, verbatim from the audited commit. It is text from someone else’s repository, quoted so you can judge it before your agent reads it.

Install

Pinned to the audited commit 3acc7a2

Download folder ↗
git clone https://github.com/sundial-org/awesome-openclaw-skills
git -C awesome-openclaw-skills checkout 3acc7a260379

The author documents no install command, so this uses the repository directly. Our verdict covers commit 3acc7a260379 only.

Works in

The author has not said which agents this skill supports, and we have not tested it in any.

Audit history

Every audit, every source change

  1. ✓SAFE B 89 / 100

    first audit · source 3acc7a260379

Similar skills

Questions about proactive-agent

What does the proactive-agent skill do?
Top OpenClaw skills, with the most popular and useful ones.
Is proactive-agent safe to install?
The audit found nothing in the source that contradicts what it says it does, and graded it B (89/100). Grade A is held back for packages that have also passed a sandboxed behavioural run, which is why a clean skill reads B.
What can proactive-agent access on my machine?
The audit observed no filesystem, network or shell use at all in its source.
How current is this page?
The grade is for one exact copy of the source (3acc7a260379), read on 2026-10-30. The repository is watched, and a new audit runs when it changes — this is the first audit.

Sources

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