fn2ai/fn2-openclaw-skill

Ask your OpenClaw agent “how did NVDA do this week and why?” or “set up a daily macro brief” — and it answers with FN2’s grounded, sourced research, or spins up an agent that does it on a schedule.

• 🔎 Research stocks, markets, earnings, and the economy — answers cite live prices, transcripts, filings, and economic data.
• 🤖 Agents that run on a schedule (daily brief, weekly recap, earnings monitor) and report back.
• 🪶 Zero dependencies. One small Python-3-stdlib CLI. No pip install.
• 🔓 No secrets in the repo. Auth is a FN2_API_KEY you provide.

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Install

From ClawHub:

openclaw skills install @fn2/fn2

Or from this repo — copy the skill into your OpenClaw workspace:

git clone https://github.com/fn2ai/fn2-openclaw-skill.git
mkdir -p ~/.openclaw/workspace/skills/fn2
cp -r fn2-openclaw-skill/{SKILL.md,scripts,references} ~/.openclaw/workspace/skills/fn2/

OpenClaw discovers the skill by its name/description and loads it on demand. Either path works — ClawHub keeps the owner-qualified path at skills/@fn2/fn2, while the manual copy uses the bare skills/fn2 path. The name: fn2 in SKILL.md identifies the skill at runtime in either layout.

Get an API key

New to FN2? Create a free account and API key here — it takes a minute:

→ fn2.ai/api-keys?ref=openclaw

(Give the key the chat, agents, and models scopes.) Then export it so the skill can use it:

export FN2_API_KEY=fn2_xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx

If you don’t have a key set, the skill points you to that link automatically.

🔒 Treat this key like a password. Never commit it or paste it into a chat. You can revoke it any time from the same page.

Use it

Just talk to your agent:

You: How did the semiconductor stocks do today, and what moved them?

You: Set up an agent that gives me a market brief every weekday at 8am ET.

You: What did Apple’s CFO say about guidance on the last call?

OpenClaw loads the skill and runs the bundled CLI with its exec tool.

Or run the CLI directly

fn2=~/.openclaw/workspace/skills/fn2/scripts/fn2.py

python3 "$fn2" research "What's the macro setup going into the next Fed meeting?"
python3 "$fn2" agents create --name "Macro Brief" \
     --prompt "Morning macro brief: overnight moves, key data, what to watch" \