Velvet Unicorn (AI /ask)

Use this skill to get a structured, AI-generated response from: POST https://gentweet.velvetdao.xyz/ask

It’s meant to cover:

• token analyses (tickers, addresses, chain context)
• wallet analyses (EVM/Solana addresses, holdings, performance)
• trade analyses (may return tx data to simulate/prepare, not broadcast)

What you send

Send a JSON body matching this shape:

{
  "question": "string",
  "context": "string",
  "userid": "string | null",
  "userid_sol": "string | null",
  "previous_questions": ["string", "..."]
}

Notes:

• context should be a short, relevant summary (not the whole chat).
• userid is typically the user’s EVM wallet address (0x…).
• userid_sol is typically the user’s Solana address.
• previous_questions should be the last ~3 relevant user questions (optional).

What you expect back

The endpoint should return a dict like:

{
  "meta_category": 0,
  "vu_category": 1,
  "answer": "string",
  "txdata": { "..." : "..." } 
}

• answer is what you tell the user.
• txdata may be null/empty; if present, treat it as unsigned / unbroadcast intent.

How to call it (preferred)

Use the helper script:

python3 {baseDir}/scripts/ask_unicorn.py \
  --question "Analyze $TOKEN and summarize risk + momentum" \
  --context "User is interested in short-term swing; medium risk tolerance." \
  --userid "0xabc..." \
  --userid-sol "" \
  --previous-questions '["what do you think of $TOKEN", "compare it to $OTHER"]'

Or use the shell wrapper:

bash {baseDir}/scripts/ask_unicorn.sh "Analyze $TOKEN" "Context here" "0xabc..." "" '["prev q1","prev q2"]'

How to respond to the user

1. Run the script and parse the JSON output.
2. Show answer directly.
3. If txdata is present:
   • present it clearly as “proposed transaction data”
   • ask for explicit confirmation before any signing/broadcast workflow
   • never claim execution happened unless you have an onchain confirmation

Environment variables (optional)

• VELVET_UNICORN_ENDPOINT to override the default endpoint.
• VELVET_UNICORN_API_KEY if your endpoint requires auth (sent as Authorization: Bearer …).

If you’re using OpenClaw config injection, per-skill env can be set under skills.entries.<skillKey>.env.