OpenClaw Master Skills is a curated, regularly updated collection of skills that extends an AI personal assistant platform with capabilities such as research, browser automation, presentation creation, and prompt work. It is intended for people using OpenClaw or MyClaw.ai to give their agents additional tasks and workflows. The catalogue contains many skills and agents from this collection.
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 LeoYeAI/openclaw-master-skills --skill acquire-first-1000-users-on-redditgit clone --depth 1 https://github.com/LeoYeAI/openclaw-master-skillsWrote 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/leoyeai/openclaw-master-skills/acquire-first-1000-users-on-reddit)<a href="https://agentmods.dev/skills/leoyeai/openclaw-master-skills/acquire-first-1000-users-on-reddit"><img src="https://agentmods.dev/badge/skills/leoyeai/openclaw-master-skills/acquire-first-1000-users-on-reddit/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/leoyeai/openclaw-master-skills/acquire-first-1000-users-on-reddit"><img src="https://agentmods.dev/badge/skills/leoyeai/openclaw-master-skills/acquire-first-1000-users-on-reddit.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 3 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 Excessive Agency · line 451 Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.
- medium Excessive Agency · line 465 Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.
- medium Excessive Agency · line 476 Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.
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 | $0.00084 | $0.04341 |
| Opus 5 | $0.00042 | $0.02171 |
| Sonnet 5 | $0.00017 | $0.00868 |
| Haiku 4.5 | $0.00008 | $0.00434 |
Grade A, and why
first-1000-users scanned grade A with 0 findings 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 12d 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.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 525 lines — stays where its author put it; the contents beside it link to each section on GitHub.
first-1000-users
You are first-1000-users, an AI agent that helps founders seed their product into real Reddit conversations. You research, discover real threads, draft personalized messages, and execute approved outreach.
Your Job
You run a 6-phase pipeline. Phases 1–3 are autonomous. Phase 4 is a human gate. Phases 5–6 are post-approval.
Phase 1: RESEARCH — Analyze product, map subreddits, generate signals
Phase 2: DISCOVERY — Search Reddit for real threads matching signals
Phase 3: DRAFT — Write personalized messages for specific threads
Phase 4: APPROVE — Present drafts, get human approval [HUMAN GATE]
Phase 5: EXECUTE — Post approved messages via Reddit API
Phase 6: MONITOR — Track engagement, alert on responses
CRITICAL: You NEVER send any message without explicit human approval.
How to Read the Product Spec
Extract these working variables from the product spec:
PRODUCT_NAME = exact name
ONE_LINER = one sentence description
CORE_PROBLEM = pain point in user language
TARGET_AUDIENCE = role + company stage + context (must be specific)
KEY_FEATURES = top 3-5, ranked by differentiator strength
PRICING_MODEL = free | freemium | paid | open-source
PRODUCT_STAGE = pre-launch | beta | live
PRODUCT_URL = link or "not yet"
COMPETITORS = list with brief notes on each
Then derive:
PAIN_PHRASES = 3-5 phrases a real person would type on Reddit when frustrated.
Not marketing copy. Real talk.
AUDIENCE_SIGNALS = Where does TARGET_AUDIENCE self-identify?
Subreddit flairs, post history patterns, bio keywords.
SWITCHING_COST = low | medium | high
→ low = stronger CTA, high = softer/educational
OFFER_TYPE = Derived from PRICING_MODEL + PRODUCT_STAGE:
free + pre-launch → "early access invite"
free + live → "it's free, here's the link"
freemium → "free tier, no credit card"
paid + pre-launch → "happy to give you early access"
paid + live → "free trial" or "demo"
open-source → "it's open source: [link]"
MAKER_FRAMING = "i built" (maker) or "i've been using" (user)
What ships with it
6 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.
- 12d ago First seen · 525 lines · 84 tokens per session scan A beec5dcdc641
first-1000-users is a skill published in the GitHub repository LeoYeAI/openclaw-master-skills (2,141 stars, last pushed 1mo ago), licensed MIT. It adds 84 tokens to every session and 4,341 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other skills, from other repositories
comfyui-skill-openclaw
Run registered ComfyUI workflows through the fast comfyui-skill CLI, and use the official local Comfy MCP for live template, node, model, validation, and orchestration capabilities. Use this Skill when: (1) The user requests to "generate an image", "draw a picture", or "execute a ComfyUI workflow". (2) The user has…
openclaw-auto-dream
Cognitive memory architecture for OpenClaw agents — periodic dream cycles that consolidate daily logs into structured long-term memory with importance scoring, insights, and push notifications. Use when: user asks for 'auto memory', 'dream', 'auto-dream', 'memory consolidation', 'memory dashboard'. Powered by…
openclaw-ultra-scraping
Powerful web scraping, crawling, and data extraction with stealth anti-bot bypass. Bypasses anti-bot systems (Cloudflare Turnstile, CAPTCHAs) out of the box. Use when: (1) scraping websites that block normal requests, (2) extracting structured data from web pages, (3) crawling multiple pages with concurrency, (4)…
myclaw-backup
Backup and restore all OpenClaw configuration, agent memory, skills, and workspace data. Part of the MyClaw.ai (https://myclaw.ai) open skills ecosystem — the AI personal assistant platform that gives every user a full server with complete code control. Use when the user wants to create a snapshot of their OpenClaw…
agentsec
Audit AI agent skills for security vulnerabilities. Use when scanning installed skills against the OWASP Agentic Skills Top 10, checking skills before running them, gating CI/CD on skill safety, or generating audit reports (text, JSON, SARIF, HTML) for stakeholders.
create-teammate
Distill a teammate into an AI Skill. Auto-collect Slack/Teams/GitHub data, generate Work Skill + 5-layer Persona, with continuous evolution. Use when: user wants to capture a colleague's knowledge before they leave, create an AI version of a teammate, distill tribal knowledge into a reusable skill, or says…