Virtuals Protocol Acp
Virtual-Protocol/openclaw-acp
Hire specialised agents to handle any task — data analysis, trading, content generation, research, on-chain operations, 3D printing, physical goods, gift delivery, and more.
Research a token and execute a trade if it passes due diligence.
$ npx skills add LeoYeAI/openclaw-master-skills --skill research-and-trade -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install LeoYeAI/openclaw-master-skills research-and-trade --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/LeoYeAI/openclaw-master-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/research-and-trade .claude/skills/research-and-trade && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "research-and-trade" agent skill from https://github.com/LeoYeAI/openclaw-master-skills/tree/main/skills/research-and-trade into .claude/skills/research-and-trade/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "research-and-trade", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/LeoYeAI/openclaw-master-skills/tree/main/skills/research-and-tradeType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add LeoYeAI/openclaw-master-skills --skill research-and-trade -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install LeoYeAI/openclaw-master-skills research-and-trade --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/LeoYeAI/openclaw-master-skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/research-and-trade .agents/skills/research-and-trade && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "research-and-trade" agent skill from https://github.com/LeoYeAI/openclaw-master-skills/tree/main/skills/research-and-trade into .agents/skills/research-and-trade/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "research-and-trade", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add LeoYeAI/openclaw-master-skills --skill research-and-trade -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install LeoYeAI/openclaw-master-skills research-and-trade --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/LeoYeAI/openclaw-master-skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/research-and-trade .cursor/skills/research-and-trade && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "research-and-trade" agent skill from https://github.com/LeoYeAI/openclaw-master-skills/tree/main/skills/research-and-trade into .cursor/skills/research-and-trade/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "research-and-trade", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/LeoYeAI/openclaw-master-skills.git --path skills/research-and-trade--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add LeoYeAI/openclaw-master-skills --skill research-and-trade -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install LeoYeAI/openclaw-master-skills research-and-trade --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/LeoYeAI/openclaw-master-skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/research-and-trade .gemini/skills/research-and-trade && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "research-and-trade" agent skill from https://github.com/LeoYeAI/openclaw-master-skills/tree/main/skills/research-and-trade into .gemini/skills/research-and-trade/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "research-and-trade", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install LeoYeAI/openclaw-master-skills research-and-tradeInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add LeoYeAI/openclaw-master-skills --skill research-and-trade -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/LeoYeAI/openclaw-master-skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/research-and-trade .github/skills/research-and-trade && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "research-and-trade" agent skill from https://github.com/LeoYeAI/openclaw-master-skills/tree/main/skills/research-and-trade into .github/skills/research-and-trade/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "research-and-trade", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add LeoYeAI/openclaw-master-skills --skill research-and-trade -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install LeoYeAI/openclaw-master-skills research-and-trade --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/LeoYeAI/openclaw-master-skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/research-and-trade .opencode/skills/research-and-trade && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "research-and-trade" agent skill from https://github.com/LeoYeAI/openclaw-master-skills/tree/main/skills/research-and-trade into .opencode/skills/research-and-trade/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "research-and-trade", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
research-and-tradeResearch a token and execute a trade if it passes due diligence.
Research And Trade is an agent skill from LeoYeAI/openclaw-master-skills. Research a token and execute a trade if it passes due diligence. Autonomous research-to-trade pipeline: researches the token, evaluates risk, and only trades if the risk assessment approves. Stops and reports if risk is too high. Use when user wants "research X and buy if it looks good" or "due diligence then trade."
Its SKILL.md is about 4.2k tokens, which your agent loads only when the skill is triggered. The skill folder holds 2 other files (for example `README.md` and `_meta.json`).
It sits in Business, Finance & HR, covering Fundraising and pitch decks. The repository describes itself as: 🧠 Curated collection of 1209+ best OpenClaw skills — weekly updated by MyClaw.ai. The licence is MIT.
5 steps, taken from the step headings in SKILL.md.
Read from SKILL.md and the folder at commit e5199b5. It shows what the files ask for, not the result of running them.
Pre-approves these tools, so the agent can use them without asking each time:
Task(subagent_type:token-analyst)Task(subagent_type:pool-researcher)Task(subagent_type:risk-assessor)Task(subagent_type:trade-executor)mcp__uniswap__check_safety_statusFrom allowed-tools in the SKILL.md frontmatter.
No scripts in the folder and no shell commands in SKILL.md.
From the folder's file list and the shell code blocks in SKILL.md.
Hosts in commands or code, which the agent is likely to contact:
etherscan.ioFrom URLs in SKILL.md, links to its own repository left out.
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Research And Trade loads about 4.2k tokens when it runs. Until then it costs about 84 tokens; SKILL.md has 950 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
The full file from LeoYeAI/openclaw-master-skills at commit e5199b5, republished under its MIT licence (© LeoYeAI). 950 words, ~4,206 tokens.
.claude/skills/research-and-trade/SKILL.md (or your agent's skills folder). This skill also uses 2 other files; get the full folder from GitHub.This is the autonomous research-to-execution pipeline. Instead of manually calling four different agents and wiring their outputs together, this skill runs the full expert workflow in one command: research a token, find the best pool, assess risk, and -- only if the risk assessment approves -- execute the trade.
Why this is 10x better than calling agents individually:
Activate when the user says anything like:
Do NOT use when the user just wants research without trading (use research-token instead) or just wants to execute a swap without research (use execute-swap instead).
| Parameter | Required | Default | How to Extract |
|---|---|---|---|
| token | Yes | -- | Token to research and potentially buy: "UNI", "AAVE", or 0x addr |
| amount | Yes | -- | Trade size: "$500", "1 ETH worth", "0.5 ETH" |
| chain | No | ethereum | Target chain: "ethereum", "base", "arbitrum" |
| riskTolerance | No | moderate | "conservative", "moderate", "aggressive" |
| action | No | buy | "buy" (swap into token) or "sell" (swap out of token) |
| payWith | No | WETH | Token to spend: "WETH", "USDC", etc. |
If the user doesn't provide an amount, ask for it -- never guess a trade size.
RESEARCH-AND-TRADE PIPELINE
┌─────────────────────────────────────────────────────────────────────┐
│ │
│ Step 1: RESEARCH (token-analyst) │
│ ├── Token metadata, liquidity, volume, risk factors │
│ ├── Cross-chain presence │
│ └── Output: Token Research Report │
│ │ │
│ ▼ (feeds into Step 2) │
│ │
│ Step 2: POOL ANALYSIS (pool-researcher) │
│ ├── Find all pools for {token}/{payWith} on {chain} │
│ ├── Rank by fee APY, depth, utilization │
│ ├── Analyze depth at trade size (can it handle $X?) │
│ └── Output: Pool Research Report + Best Pool Selection │
│ │ │
│ ▼ (feeds into Step 3 with COMPOUND CONTEXT) │
│ │
│ Step 3: RISK ASSESSMENT (risk-assessor) │
│ ├── Receives: token risks + pool risks + trade size + slippage │
│ ├── Evaluates: slippage, liquidity, smart contract, token risk │
│ ├── Decision: APPROVE / CONDITIONAL_APPROVE / VETO / HARD_VETO │
│ └── Output: Risk Assessment Report │
│ │ │
│ ▼ CONDITIONAL GATE │
│ ┌───────────────────────────────────────────────────┐ │
│ │ APPROVE → Proceed to Step 4 │ │
│ │ COND. APPROVE → Show conditions, ask user │ │
│ │ VETO → STOP. Show research + reason. │ │
│ │ HARD VETO → STOP. Non-negotiable. │ │
│ └───────────────────────────────────────────────────┘ │
│ │ (only if APPROVE or user confirms CONDITIONAL) │
│ ▼ │
│ │
│ Step 4: USER CONFIRMATION │
│ ├── Present: research summary + risk score + swap quote │
│ ├── Ask: "Proceed with this trade?" │
│ └── User must explicitly confirm │
│ │ │
│ ▼ │
│ │
│ Step 5: EXECUTE (trade-executor) │
│ ├── Execute swap through safety-guardian pipeline │
│ ├── Monitor transaction confirmation │
│ └── Output: Trade Execution Report │
│ │
└─────────────────────────────────────────────────────────────────────┘Delegate to Task(subagent_type:token-analyst) with:
What to pass to the agent:
Research this token for a potential trade:
- Token: {token}
- Chain: {chain}
- Trade size: {amount}
Provide a full due diligence report: liquidity across all pools, volume profile
(24h/7d/30d), risk factors, and a trading recommendation with maximum trade size
at < 1% price impact.Present to user after completion:
Step 1/5: Token Research Complete
Token: UNI (Uniswap) on Ethereum
Total Liquidity: $85M across 24 pools
24h Volume: $15M | 7d Volume: $95M
Volume Trend: Stable
Risk Factors: None significant
Max Trade (< 1% impact): $2.5M
Proceeding to pool analysis...Gate check: If the token-analyst reports critical risk factors (total liquidity < $100K, no pools found, token not verified), present findings and ask the user if they want to continue before proceeding.
Delegate to Task(subagent_type:pool-researcher) with the token research output:
Find the best pool for trading {token}/{payWith} on {chain}.
Context from token research:
- Total liquidity: {from Step 1}
- Dominant pool: {from Step 1}
- Risk factors: {from Step 1}
Trade details:
- Trade size: {amount}
- Direction: {action} (buying/selling {token})
Analyze all pools for this pair across fee tiers. For each pool, report:
fee APY, TVL, liquidity depth at the trade size, and price impact estimate.
Recommend the best pool for this specific trade.Present to user after completion:
Step 2/5: Pool Analysis Complete
Best Pool: WETH/UNI 0.3% (V3, Ethereum)
Pool TVL: $42M
Price Impact: ~0.3% for your trade size
Fee Tier: 0.3% (3000 bps)
Proceeding to risk assessment...Delegate to Task(subagent_type:risk-assessor) with compound context from Steps 1 and 2:
Evaluate risk for this proposed swap:
Operation: swap {amount} {payWith} for {token}
Pool: {best pool from Step 2}
Chain: {chain}
Risk tolerance: {riskTolerance}
Token research context (from token-analyst):
{Full token research summary from Step 1}
Pool analysis context (from pool-researcher):
{Full pool analysis from Step 2}
Evaluate all applicable risk dimensions: slippage, liquidity, smart contract risk.
Provide a clear APPROVE / CONDITIONAL_APPROVE / VETO / HARD_VETO decision.Conditional gate logic after risk-assessor returns:
| Decision | Action |
|---|---|
| APPROVE | Present risk summary, proceed to Step 4 (user confirmation) |
| CONDITIONAL_APPROVE | Show conditions (e.g., "split into 2 tranches"). Ask user: "Accept conditions?" |
| VETO | STOP. Show full research report + risk assessment + veto reason. Suggest alternatives. |
| HARD_VETO | STOP. Show reason. Non-negotiable -- do not offer to proceed. |
Present to user (APPROVE case):
Step 3/5: Risk Assessment Complete
Decision: APPROVE
Composite Risk: LOW
Slippage Risk: LOW (0.3% estimated)
Liquidity Risk: LOW (pool TVL 840x trade size)
Smart Contract Risk: LOW (V3, 18-month-old pool)
Ready for your confirmation...Present to user (VETO case):
Step 3/5: Risk Assessment -- VETOED
Decision: VETO
Reason: Price impact of 4.2% exceeds moderate risk tolerance (max 2%)
Research Summary:
Token: SMALLCAP ($180K total liquidity)
Best Pool: WETH/SMALLCAP 1% (V3, $95K TVL)
Your trade size ($5,000) represents 5.3% of pool TVL
Suggestions:
- Reduce trade size to < $1,000 for acceptable slippage
- Use a limit order instead: "Submit limit order for SMALLCAP"
- Try a different chain if more liquidity exists elsewhere
Pipeline stopped. No trade executed.Before executing any trade, present a clear summary and ask for explicit confirmation:
Trade Confirmation Required
Research: UNI — $85M liquidity, stable volume, no risk factors
Risk: APPROVED (LOW composite risk)
Swap Details:
Sell: 0.5 WETH (~$980)
Buy: ~28.5 UNI
Pool: WETH/UNI 0.3% (V3, Ethereum)
Impact: ~0.3%
Gas: ~$8 estimated
Proceed with this trade? (yes/no)Only proceed to Step 5 if the user explicitly confirms.
Delegate to Task(subagent_type:trade-executor) with the full pipeline context:
Execute this swap:
- Sell: {amount} {payWith}
- Buy: {token}
- Pool: {best pool address from Step 2}
- Chain: {chain}
- Slippage tolerance: {derived from risk assessment}
- Risk assessment: APPROVED, composite risk {level}
The token has been researched (liquidity: {X}, volume: {Y}) and risk-assessed
(slippage: {Z}, liquidity: {W}). Proceed with execution through the safety pipeline.Present final result:
Step 5/5: Trade Executed
Sold: 0.5 WETH ($980.00)
Received: 28.72 UNI ($985.50)
Pool: WETH/UNI 0.3% (V3, Ethereum)
Slippage: 0.28% (within tolerance)
Gas: $7.20
Tx: https://etherscan.io/tx/0x...
──────────────────────────────────────
Pipeline Summary
──────────────────────────────────────
Research: UNI — $85M liquidity, stable, no risk flags
Pool: WETH/UNI 0.3% — best depth for trade size
Risk: APPROVED (LOW)
Execution: Success — 28.72 UNI received
Total cost: $987.20 (trade + gas)Research and Trade Complete
Token: {symbol} ({name}) on {chain}
Research: {1-line summary from token-analyst}
Pool: {pool pair} {fee}% ({version}, {chain})
Risk: {decision} ({composite_risk})
Trade:
Sold: {amount} {payWith} (${usd_value})
Received: {amount} {token} (${usd_value})
Impact: {slippage}%
Gas: ${gas_cost}
Tx: {explorer_link}
Pipeline: Research -> Pool -> Risk -> Confirm -> Execute (all passed)Research and Trade -- Risk Vetoed
Token: {symbol} ({name}) on {chain}
Research: {1-line summary}
Pool: {best pool found}
Risk: VETOED — {reason}
Details:
{risk dimension scores}
Suggestions:
- {mitigation 1}
- {mitigation 2}
Pipeline: Research -> Pool -> Risk (VETOED) -- No trade executed.execute-swap.execute-swap directly if they want to proceed at their own risk -- but this skill will not do it.| Error | User-Facing Message | Suggested Action |
|---|---|---|
| Token not found | "Could not find token {X} on {chain}." | Check spelling or provide contract address |
| No pools found | "No Uniswap pools found for {token}/{payWith} on {chain}." | Try different pay token or chain |
| Token-analyst fails | "Token research failed: {reason}. Cannot proceed without due diligence." | Try again or use research-token directly |
| Pool-researcher fails | "Pool analysis failed. Research completed but cannot find optimal pool." | Try execute-swap with manual pool choice |
| Risk-assessor VETO | "Risk assessment vetoed this trade: {reason}." | Reduce amount, try different token/pool |
| Risk-assessor HARD_VETO | "Trade blocked: {reason}. This cannot be overridden." | The trade is unsafe at any size |
| Trade-executor fails | "Trade execution failed: {reason}. Research and risk data preserved." | Check wallet, balance, gas; retry |
| Safety check fails | "Safety limits exceeded. Check spending limits with check-safety." | Wait for limit reset or adjust limits |
| User declines confirmation | "Trade cancelled. Research and risk data are shown above for reference." | No action needed |
| Wallet not configured | "No wallet configured. Cannot execute trades." | Set up wallet with setup-agent-wallet |
| Insufficient balance | "Insufficient {payWith} balance: have {X}, need {Y}." | Reduce amount or acquire more tokens |
© LeoYeAI, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
SKILL.md and 2 other files in skills/research-and-trade of LeoYeAI/openclaw-master-skills.
Open the folder on GitHubat commit e5199b5
Research And Trade next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Research And Trade this skillLeoYeAI/openclaw-master-skills | 2.2k | — | ~4.2k | Automated safety check: Pass | MIT | |
| Virtuals Protocol AcpVirtual-Protocol/openclaw-acp | 168 | 1 repos | ~6.4k | Automated safety check: Pass | None | |
| Yc Applypedronauck/skills | 634 | — | ~1.3k | Automated safety check: Pass | None | |
| Storyline Buildersruthir28/enterprise-ai-skills | 148 | 1 repos | ~1.9k | Automated safety check: Pass | MIT | |
| Startup Pitchferdinandobons/startup-skill | 1.2k | — | ~6.4k | Automated safety check: Pass | MIT | |
| Dd SourcingAbilityai/trinity | 636 | — | ~664 | Automated safety check: Pass | Apache-2.0 |
Virtual-Protocol/openclaw-acp
Hire specialised agents to handle any task — data analysis, trading, content generation, research, on-chain operations, 3D printing, physical goods, gift delivery, and more.
pedronauck/skills
Prepare, review, and package Y Combinator application answers and founder-video notes using the live form and verified founder facts.
sruthir28/enterprise-ai-skills
McKinsey-style storyline framework for building presentation decks.
ferdinandobons/startup-skill
Build investor-ready pitch scripts in multiple formats (10-min, 5-min, 2-min, 1-min elevator, investor email).
Abilityai/trinity
Document sources properly for due diligence reports. An agent skill from Abilityai/trinity.
sanqiufong/slides-from-anything
Single-file horizontal-swipe HTML deck in the style of Replit Slides's landing-page template gallery.
LeoYeAI/openclaw-master-skills
Manages pipelines on a DevOps quality and efficiency platform through its OpenAPI: list workspaces and templates, create, update, run and cancel pipelines, and read run records.
LeoYeAI/openclaw-master-skills
Patches OpenClaw's Feishu extension so an edited document triggers an isolated agent session that reads the doc and replies inline, turning it into a live chat space.
LeoYeAI/openclaw-master-skills
Multi-context memory management system for OpenClaw agents with group-isolated storage, global shared memory, workspace organization, and group-specific skills isolation.
LeoYeAI/openclaw-master-skills
Runs a brand's AI-search visibility work end to end: diagnosing how AI platforms represent it, repositioning it, producing AI-optimized content and monitoring ongoing mentions.
LeoYeAI/openclaw-master-skills
Installs and authenticates the gws CLI, then automates Gmail, Drive, Sheets, Calendar, Docs, Chat and Tasks with ready-made recipes, persona bundles and security audits.
LeoYeAI/openclaw-master-skills
Runs four advisor roles, a fitness coach, nutritionist, data analyst and TCM practitioner, to build a health profile and track workouts, diet and wellness over time.
Categories
Research a token and execute a trade if it passes due diligence. Research And Trade is an agent skill from LeoYeAI/openclaw-master-skills. Research a token and execute a trade if it passes due diligence.
Research And Trade fits situations like: user wants research X and buy if it looks good; due diligence then trade.
Run `npx skills add LeoYeAI/openclaw-master-skills --skill research-and-trade -a claude-code`. Or copy the skill folder (skills/research-and-trade in LeoYeAI/openclaw-master-skills) into .claude/skills/research-and-trade in your project. Claude Code loads it when a task matches its description.
Run `npx skills add LeoYeAI/openclaw-master-skills --skill research-and-trade -a codex`. Or copy the skill folder (skills/research-and-trade in LeoYeAI/openclaw-master-skills) into .agents/skills/research-and-trade in your project. Codex loads it when a task matches its description.
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add LeoYeAI/openclaw-master-skills --skill research-and-trade -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/research-and-trade, .gemini/skills/research-and-trade, .github/skills/research-and-trade and .opencode/skills/research-and-trade in your project.
SKILL.md names no scripts, command-line tools or credentials: Research And Trade is instructions for the agent only. Its frontmatter pre-approves these tools: Task(subagent_type:token-analyst), Task(subagent_type:pool-researcher), Task(subagent_type:risk-assessor), Task(subagent_type:trade-executor), mcp__uniswap__check_safety_status.
SKILL.md names 1 domain. In commands or code: etherscan.io; the agent is likely to contact it when it follows the instructions. This is read from the text; nothing was executed.
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.
Research And Trade is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
About 4.2k tokens (SKILL.md is roughly 17k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
Skills that share tags, products or a category with Research And Trade: Virtuals Protocol Acp (Virtual-Protocol/openclaw-acp, 168 stars), Yc Apply (pedronauck/skills, 634 stars), Storyline Builder (sruthir28/enterprise-ai-skills, 148 stars) and Startup Pitch (ferdinandobons/startup-skill, 1.2k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
LeoYeAI (a GitHub user) maintains it in LeoYeAI/openclaw-master-skills, which has 2,161 GitHub stars. The repository holds 1,235 skills in this directory. The repository was last updated on July 20, 2026.
Source: LeoYeAI/openclaw-master-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.