通过单一 API 研究股票、期权、市场情绪与宏观数据,响应已为 AI 智能体预处理。
数据分析
FN2 skill for OpenClaw 🦞
试用Research stocks, markets, and the economy with FN2's grounded AI, and create, schedule, and manage research agents.
它能做什么
Research stocks, markets, and the economy with FN2's grounded AI, and create, schedule, and manage research agents.
技能文档
FN2 — market research & research agents
FN2 is an AI research platform for stocks, markets, and the economy. It answers questions with grounded, sourced analysis (live prices, earnings transcripts, SEC filings, economic data, prediction markets) and lets you run agents that research on a schedule and report back.
This skill calls FN2 through a small bundled CLI at
python3 {baseDir}/scripts/fn2.py (Python 3 standard library only — nothing
to install). Run it with the exec tool.
When to use this skill
Reach for FN2 whenever the user asks about:
- A stock or ticker — price action, "how did NVDA do this week and why", fundamentals
- Earnings, guidance, or what management said on a call
- The market or macro picture — the S&P/Nasdaq, the Fed, inflation, rates, jobs
- Comparing companies, screening, or "what's moving and why"
- Setting up recurring research — a daily brief, a weekly recap, an earnings-day monitor — that runs automatically
For one-off questions, use research. For anything recurring or that should keep
running on its own, create an agent.
Setup (once)
The CLI authenticates with the FN2_API_KEY environment variable.
If the user isn't connected to FN2 yet (no key set), the CLI prints a sign-up link — surface it to them as the next step. Don't try to work around a missing key; getting one is the onboarding:
You'll need a free FN2 account to use this. Create one and grab an API key here (it takes a minute): https://fn2.ai/api-keys?ref=openclaw Then run:
export FN2_API_KEY=fn2_...
The ?ref=openclaw link takes them straight to key creation. Once they've
exported the key, retry their request.
How to use it
Run the bundled CLI with exec. Add --json to any command when you want
machine-readable output to parse.
Research (the most common use)
python3 {baseDir}/scripts/fn2.py research "How did NVDA do this week, and what drove it?"
python3 {baseDir}/scripts/fn2.py research "What's the macro backdrop into the next Fed meeting?"
python3 {baseDir}/scripts/fn2.py research "Summarize Apple's latest earnings call" --model z-ai/glm-5.2
A research call can take 30–120 seconds because FN2 pulls live data and reads sources. The answer comes back as Markdown.
Agents — schedule recurring research
# Run once, right now:
python3 {baseDir}/scripts/fn2.py agents create --prompt "Deep dive on AMD vs NVDA in AI accelerators"
# Every weekday morning:
python3 {baseDir}/scripts/fn2.py agents create --name "Macro Brief" \
--prompt "Morning macro brief: overnight moves, key data, what to watch" \
--every weekdays --timezone America/New_York
# A specific cron schedule (Mondays at 9am):
python3 {baseDir}/scripts/fn2.py agents create --name "Weekly Tech Recap" \
--prompt "Recap the week in big-cap tech and call out next week's catalysts" \
--cron "0 9 * * 1" --timezone America/New_York
Manage agents and read their results
python3 {baseDir}/scripts/fn2.py agents list # see your agents
python3 {baseDir}/scripts/fn2.py agents run # trigger a run now
python3 {baseDir}/scripts/fn2.py runs list # list that agent's runs
python3 {baseDir}/scripts/fn2.py runs get # read a run's full answer
python3 {baseDir}/scripts/fn2.py agents pause # pause / resume
python3 {baseDir}/scripts/fn2.py agents resume
python3 {baseDir}/scripts/fn2.py agents delete # delete it and its history
Account & models
python3 {baseDir}/scripts/fn2.py models # which models you can use (★ = your default)
python3 {baseDir}/scripts/fn2.py usage # your plan and token usage
Good habits
- Quote the user's question closely in
research— FN2 does the interpreting. - After creating a scheduled agent, confirm its
idand schedule back to the user. - A run started with
agents runis asynchronous: pollruns getuntil its status iscompleted, then share the result text. - A
403 Missing scopemeans the user's key needs the relevant scope (chatfor research,agentsfor agents,modelsfor the model list) — they can edit it at https://fn2.ai. - A
429is a quota limit — showpython3 {baseDir}/scripts/fn2.py usage.
See references/api.md for the full command and endpoint
reference.
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