Requirements
- Target platform
- OpenClaw
- Install method
- Manual import
- Extraction
- Extract archive
- Prerequisites
- OpenClaw
- Primary doc
- SKILL.md
Scan crypto and NFT sentiment on X/Twitter for daily alpha reports or token/NFT/project on-demand analyses with sentiment, trends, and red flags.
Scan crypto and NFT sentiment on X/Twitter for daily alpha reports or token/NFT/project on-demand analyses with sentiment, trends, and red flags.
Hand the extracted package to your coding agent with a concrete install brief instead of figuring it out manually.
I downloaded a skill package from Yavira. Read SKILL.md from the extracted folder and install it by following the included instructions. Then review README.md for any prerequisites, environment setup, or post-install checks. Tell me what you changed and call out any manual steps you could not complete.
I downloaded an updated skill package from Yavira. Read SKILL.md from the extracted folder, compare it with my current installation, and upgrade it while preserving any custom configuration unless the package docs explicitly say otherwise. Then review README.md for any prerequisites, environment setup, or post-install checks. Summarize what changed and any follow-up checks I should run.
Your agent's X/Twitter alpha scanner. Two things: daily reports and on-demand analysis.
Environment variables: export X_AUTH_TOKEN="your_twitter_auth_token" export X_CT0="your_twitter_ct0_cookie" Verify: bird whoami --auth-token "$X_AUTH_TOKEN" --ct0 "$X_CT0"
User says: "What do you think of $PEPEAI?" or "Analyze FomoBears NFT" What you do: # Deep scan this specific asset bird search "$PEPEAI" -n 30 bird search "$PEPEAI (gem OR scam OR rug OR buy)" -n 20 Analyze gathered tweets: Count sentiment: Bullish vs Bearish vs Neutral Identify high-conviction posts: Position sizes, wallet proofs, detailed threads Check high-rep accounts: Are known good callers in or out? Look for red flags: Contract issues, copycat names, anon team Deliver analysis in this exact format: 📊 CT Sentiments: [4-5 line summary based on top 20-30 recent tweets about the asset. What are people saying? Any patterns? Hype or concern? Specific details about the project/token/NFT] 📈 Overall: [Bullish/Bearish/Neutral] (assessment at end of CT Sentiments section) 🐋 Takes of High-Rep Accounts: [@Influencer1: "quote or summary of their take" — Bullish] [@Influencer2: "quote or summary of their take" — Bearish] [Or: No noticeable activity detected from high-rep accounts — Bearish] ⚠️ Red Flags: [Any contract issues, anon team, copycat name, LP not locked, etc. Or: None detected] 📊 Score: XX/100 ✅ Verdict: [High/Medium/Low confidence — Bullish/Neutral/Bearish] ⚡ NFA / DYOR How to gather data: # Get general sentiment tweets bird search "$TICKER" -n 30 # Get high-rep account takes specifically bird search "$TICKER (from:DegenKing OR from:AlphaKing OR from:CryptoGem)" -n 20 # Add more KOLs as needed Scoring guide: 90-100: Strong bullish consensus, high-reps bullish, no red flags 70-89: Moderate bullish, some high-reps in, minor concerns 50-69: Mixed/neutral, no clear direction or high-reps silent 30-49: Bearish signals, some red flags or high-reps warning 0-29: Strong bearish, multiple red flags, avoid
CT Sentiment Score (0-100): 80-100: Strong bullish consensus, high-rep accounts in, no red flags 50-79: Mixed or moderate sentiment, do more research <50: Bearish consensus or multiple red flags detected What to look for: Bullish: "gem", "undervalued", "loading up", "next 100x" Bearish: "rug", "scam", "avoid", "dumping" High-conviction: Specific numbers ("bought $5k"), wallet screenshots, detailed threads Red flags: Contract unverified, LP not locked, copycat name, team completely anon
TaskCommandDaily reportRun scans for last 24h, compile top callsAnalyze assetbird search "$TICKER" -n 30Check specific callerbird search "from:username" -n 20Find mintsbird search "free mint OR minting now NFT" -n 15
User: "Get my alpha report" You: Run the 4 daily scans → compile top calls → format report → deliver User: "What about $MOONSHOT?" You: Search "$MOONSHOT" (30 tweets) → analyze sentiment → check for red flags → deliver analysis with score + verdict + NFA User: "Is @DegenKing reliable?" You: Search "from:DegenKing" → review their recent calls → give qualitative assessment: "Known for high-conviction calls, recent streak looks solid" or "Mixed bag lately, verify before following" Built for the agent economy. NFA. DYOR. 🦅
Data access, storage, extraction, analysis, reporting, and insight generation.
Largest current source with strong distribution and engagement signals.