openclaw-superpowers

53 ready-to-use skills that make your AI agent autonomous, self-healing, and self-improving.

A plug-and-play skill library for OpenClaw — the open-source AI agent runtime. Gives your agent structured thinking, security guardrails, persistent memory, cron scheduling, runtime verification, self-recovery, and the ability to write its own new skills during conversation.

Built for developers who want their AI agent to run autonomously 24/7, not just respond to prompts in a chat window.

Inspired by obra/superpowers. Extended for agents that never sleep.

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Why this exists

Most AI agent frameworks give you a chatbot that forgets everything between sessions. OpenClaw is different — it runs persistently, handles multi-hour tasks, and has native cron scheduling. But out of the box, it doesn't know how to use those capabilities well.

openclaw-superpowers bridges that gap. Install 53 skills in one command, and your agent immediately knows how to:

• Think before it acts — brainstorming, planning, and systematic debugging skills prevent the "dive in and break things" failure mode
• Protect itself — 6 security skills detect prompt injection, block dangerous actions, audit installed code, and scan for leaked credentials
• Run unattended — 20 cron-scheduled skills handle memory cleanup, health checks, budget tracking, and community monitoring while you sleep
• Verify itself — runtime verification catches missing cron registrations, stale state, dependency drift, and install layout mistakes before they silently break automation
• Recover from failures — self-recovery, loop-breaking, and task handoff skills keep long-running work alive across crashes and restarts
• Never forget — DAG-based memory compaction, integrity checking, context scoring, and SQLite session persistence ensure the agent preserves critical information even in month-long conversations
• Improve itself — the agent can write new skills during normal conversation using create-skill, encoding your preferences as permanent behaviors

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The self-modifying agent

This is what makes openclaw-superpowers different from every other plugin library:

"Every time I do a code review, check for security issues first."

Your agent invokes create-skill, writes a new SKILL.md, and that behavior is live — immediately, permanently, no restart needed. The agent encodes your preferences as durable skills. You describe what you want. It teaches itself.

The community-skill-radar skill takes this further: it scans Reddit every 3 days for pain points and feature requests from the OpenClaw community, scores them by signal strength, and writes a prioritized PROPOSALS.md — so the agent (or you) always knows what to build next.

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Quickstart

git clone https://github.com/ArchieIndian/openclaw-superpowers ~/.openclaw/src/openclaw-superpowers
cd ~/.openclaw/src/openclaw-superpowers && ./install.sh
openclaw gateway restart

install.sh symlinks the repo's skills/ directory into ~/.openclaw/extensions/superpowers, creates state directories for stateful skills, and registers cron jobs. Clone the repo outside ~/.openclaw/extensions so the installer never has to replace your checkout.

Install PyYAML before using the stateful Python helpers: python3 -m pip install PyYAML.

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Skills included

Core (15 skills)

Methodology skills that work in any AI agent runtime. Adapted from obra/superpowers plus new additions for skill quality assurance.

Skill	What it does	Script
using-superpowers	Bootstrap — teaches the agent how to find and invoke skills	—
brainstorming	Structured ideation before any implementation	—
writing-plans	Clear, reviewable implementation plans	—
executing-plans	Executes plans step-by-step with verification	—
systematic-debugging	4-phase root cause process before any fix	—
verification-before-completion	Ensures tasks are done, not just attempted	—
test-driven-development	Red-green-refactor discipline	—
subagent-driven-development	Parallel subagent execution for complex tasks	—
create-skill	Writes new skills during conversation	—
skill-vetting	Security scanner for ClawHub skills before installing	vet.sh
project-onboarding	Crawls a new codebase to generate a PROJECT.md context file	onboard.py
fact-check-before-trust	Secondary verification pass for factual claims before acting on them	—
skill-trigger-tester	Scores a skill's description against sample prompts to predict trigger reliability	test.py
skill-conflict-detector	Detects name shadowing and description-overlap conflicts between installed skills	detect.py
skill-portability-checker	Validates OS/binary dependencies in companion scripts; catches non-portable calls	check.py

OpenClaw-Native (37 skills)

Skills that require OpenClaw's persistent runtime — cron scheduling, session state, or long-running execution. These are the skills that make a 24/7 autonomous agent actually work reliably.

Skill	What it does	Cron	Script
long-running-task-management	Breaks multi-hour tasks into checkpointed stages with resume	every 15 min	—
persistent-memory-hygiene	Keeps the agent's memory store clean and useful over time	daily 11pm	—
task-handoff	Gracefully hands off incomplete tasks across agent restarts	—	—
agent-self-recovery	Detects when the agent is stuck in a loop and escapes	—	—
context-window-management	Prevents context overflow on long-running sessions	—	—
daily-review	End-of-day structured summary and next-session prep	weekdays 6pm	—
morning-briefing	Daily briefing: priorities, active tasks, pending handoffs	weekdays 7am	run.py
secrets-hygiene	Audits installed skills for stale credentials and orphaned secrets	Mondays 9am	audit.py
workflow-orchestration	Chains skills into resumable named workflows with on-failure conditions	—	run.py
context-budget-guard	Estimates context usage and triggers compaction before overflow	—	check.py
prompt-injection-guard	Detects injection attempts in external content before the agent acts	—	guard.py
spend-circuit-breaker	Tracks API spend against a monthly budget; pauses crons at 100%	every 4h	check.py
dangerous-action-guard	Requires explicit user confirmation before irreversible actions	—	audit.py
loop-circuit-breaker	Detects infinite retry loops from deterministic errors and breaks them	—	check.py
workspace-integrity-guardian	Detects drift or tampering in SOUL.md, AGENTS.md, MEMORY.md	Sundays 3am	guard.py
multi-agent-coordinator	Manages parallel agent fleets: health checks, consistency, handoffs	—	run.py
cron-hygiene	Audits cron skills for session mode waste and token efficiency	Mondays 9am	audit.py
channel-context-bridge	Writes a context card at session end for seamless channel switching	—	bridge.py
skill-doctor	Diagnoses silent skill discovery failures — YAML errors, path violations, schema mismatches	—	doctor.py
installed-skill-auditor	Weekly post-install audit of all skills for injection, credentials, and drift	Mondays 9am	audit.py
skill-loadout-manager	Named skill profiles to manage active skill sets and prevent system prompt bloat	—	loadout.py
skill-compatibility-checker	Checks installed skills against the current OpenClaw version for feature compatibility	—	check.py
runtime-verification-dashboard	Verifies cron registration, state freshness, install layout, and dependency readiness across the live runtime; can dry-run or apply safe remediations	every 6h	check.py
heartbeat-governor	Enforces per-skill execution budgets for cron skills; auto-pauses runaway skills	every hour	governor.py
community-skill-radar	Scans Reddit for OpenClaw pain points and feature requests; writes prioritized PROPOSALS.md	every 3 days	radar.py
memory-graph-builder	Parses MEMORY.md into a knowledge graph; detects duplicates, contradictions, stale entries	daily 10pm	graph.py
config-encryption-auditor	Scans config directories for plaintext API keys, tokens, and world-readable permissions	Sundays 9am	audit.py
tool-description-optimizer	Scores skill descriptions for trigger quality — clarity, specificity, keyword density — and suggests rewrites	—	optimize.py
mcp-health-checker	Monitors MCP server connections for health, latency, and availability; detects stale connections	every 6h	check.py
memory-dag-compactor	Builds hierarchical summary DAGs from MEMORY.md with depth-aware prompts (d0 leaf → d3+ durable)	daily 11pm	compact.py
large-file-interceptor	Detects oversized files, generates structural exploration summaries, stores compact references	—	intercept.py
context-assembly-scorer	Scores how well current context represents full conversation; detects blind spots	every 4h	score.py
compaction-resilience-guard	Monitors compaction for failures; enforces normal → aggressive → deterministic fallback chain	—	guard.py
memory-integrity-checker	Validates summary DAGs for orphans, circular refs, token inflation, broken lineage	Sundays 3am	integrity.py
session-persistence	Imports session transcripts into SQLite with FTS5 full-text search; queryable message history	every 15 min	persist.py
dag-recall	Walks the memory DAG to recall detailed context on demand — query, expand, and assemble cited answers	—	recall.py
expansion-grant-guard	YAML-based delegation grant ledger — scoped permission grants with token budgets and auto-expiry	—	guard.py

Community (1 skill)

Skills written by agents and contributors. Any agent can add a community skill via create-skill.

Skill	What it does	Cron	Script
obsidian-sync	Syncs OpenClaw memory to an Obsidian vault nightly	daily 10pm	sync.py

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Security & guardrails

Six skills form a defense-in-depth security layer for autonomous agents:

Threat	Skill	How it works
Malicious skill installs	skill-vetting	Pre-install scanner with 6 security flags — rates SAFE / CAUTION / DO NOT INSTALL
Prompt injection from external content	prompt-injection-guard	Detects 6 injection signal types at runtime; blocks on 2+ signals
Agent takes destructive action without asking	dangerous-action-guard	Pre-execution confirmation gate with 5-min expiry and full audit trail
Post-install tampering or credential injection	installed-skill-auditor	Weekly SHA-256 drift detection; checks for INJECTION / CREDENTIAL / EXFILTRATION
Silent skill loading failures	skill-doctor	6 diagnostic checks per skill; surfaces every load-time failure
Plaintext secrets in config files	config-encryption-auditor	Scans for 8 API key patterns + 3 token patterns; auto-fixes permissions

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How it compares

Feature	openclaw-superpowers	obra/superpowers	Custom prompts
Skills included	53	8	0
Self-modifying (agent writes new skills)	Yes	No	No
Cron scheduling	20 scheduled skills	No	No
Persistent state across sessions	YAML state schemas	No	No
Security guardrails	6 defense-in-depth skills	No	No
Companion scripts with CLI	37 scripts	No	No
Memory graph / knowledge graph	Yes	No	No
SQLite session persistence + FTS5 search	Yes	No	No
Sub-agent recall with token-budgeted grants	Yes	No	No
MCP server health monitoring	Yes	No	No
Runtime verification / observability	Yes	No	No
API spend tracking & budget enforcement	Yes	No	No
Community feature radar (Reddit scanning)	Yes	No	No
Multi-agent coordination	Yes	No	No
Works with 24/7 persistent agents	Built for it	Session-only	Session-only

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Architecture

~/.openclaw/extensions/superpowers/
├── skills/
│   ├── core/                    # 15 methodology skills (any runtime)
│   │   ├── brainstorming/
│   │   │   └── SKILL.md
│   │   ├── create-skill/
│   │   │   ├── SKILL.md
│   │   │   └── TEMPLATE.md
│   │   └── ...
│   ├── openclaw-native/         # 37 persistent-runtime skills
│   │   ├── memory-graph-builder/
│   │   │   ├── SKILL.md             # Skill definition + YAML frontmatter
│   │   │   ├── STATE_SCHEMA.yaml    # State shape (committed, versioned)
│   │   │   ├── graph.py             # Companion script
│   │   │   └── example-state.yaml   # Annotated example
│   │   └── ...
│   └── community/               # Agent-written and contributed skills
├── scripts/
│   └── validate-skills.sh       # CI validation
├── tests/
│   └── test-runner.sh
└── install.sh                   # One-command setup

State model: Each stateful skill commits a STATE_SCHEMA.yaml defining the shape of its runtime data. At install time, install.sh creates ~/.openclaw/skill-state/<skill-name>/state.yaml on your machine. The schema is portable and versioned; the runtime state is local-only and never committed.

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Companion scripts

Skills marked with a script ship a small executable alongside their SKILL.md:

• 36 Python scripts (run.py, audit.py, check.py, guard.py, bridge.py, onboard.py, sync.py, doctor.py, loadout.py, governor.py, detect.py, test.py, radar.py, graph.py, optimize.py, compact.py, intercept.py, score.py, integrity.py, persist.py, recall.py) — run directly to manipulate state, generate reports, or trigger actions. Install PyYAML for any helper that reads or writes skill state.
• vet.sh — Pure bash scanner; runs on any system with grep.
• Every script supports --help and --format json. Dry-run mode available on scripts that make changes.
• See the example-state.yaml in each skill directory for sample state and a commented walkthrough of cron behaviour.

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Use cases

Solo developer with a persistent AI agent

Install superpowers, and your agent handles memory cleanup, security audits, and daily briefings on autopilot. You focus on building; the agent maintains itself.

Team running multiple OpenClaw agents

Use multi-agent-coordinator for fleet health checks, skill-loadout-manager to keep system prompts lean per agent role, and heartbeat-governor to prevent runaway cron costs.

Open-source maintainer

community-skill-radar scans Reddit for pain points automatically. skill-vetting catches malicious community contributions before they're installed. installed-skill-auditor detects post-install tampering.

Security-conscious deployment

Six defense-in-depth skills: pre-install vetting, runtime injection detection, destructive action gates, post-install drift detection, credential scanning, and silent failure diagnosis.

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Contributing

1. Open a Skill Proposal issue — or just ask your agent to write one using create-skill
2. Run ./scripts/validate-skills.sh
3. Submit a PR — CI validates automatically
4. Community skills may be promoted to core over time

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Credits

• openclaw/openclaw — the open-source AI agent runtime
• obra/superpowers — Jesse Vincent's skills framework; core skills adapted under MIT license
• OpenLobster — inspiration for memory graph, config encryption auditing, tool-description scoring, and MCP health monitoring
• lossless-claw — inspiration for DAG-based memory compaction, session persistence, sub-agent recall, and delegation grants