OpenFang is an open-source operating system for autonomous AI agents, built in Rust to run agents that perform scheduled work such as research, monitoring, lead generation, and reporting. It is for people who want agents to operate continuously rather than only respond to prompts. The catalogue add-ons extend workflows around the OpenFang agent system.
Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add skills/rightnow-ai/openfang/tradernpx skills add RightNow-AI/openfang --skill tradergit clone --depth 1 https://github.com/RightNow-AI/openfangWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/rightnow-ai/openfang/trader)<a href="https://agentmods.dev/skills/rightnow-ai/openfang/trader"><img src="https://agentmods.dev/badge/skills/rightnow-ai/openfang/trader.svg" alt="Measured on agentmods" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00028 | $0.11286 |
| Opus 5 | $0.00014 | $0.05643 |
| Sonnet 5 | $0.00006 | $0.02257 |
| Haiku 4.5 | $0.00003 | $0.01129 |
Grade D, and why
trader-hand-skill scanned grade D with 3 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 5d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Sends data to an external URLmediumData exfiltration
A POST to an outside endpoint may be telemetry or may be exfiltration; either way the mod talks to somewhere, and you should know where.
curl -s "$DATA_URL/v2/stocks/AAPL/bars?timeframe=5Min&start=$(date -d 'today' +%Y-%m-%d)&limit=78" $HEADERS Downloads and executes remote codehighSupply chain
curl | sh runs whatever the server returns today, which is not necessarily what it returned when this was reviewed.
curl -s URL | python3 -c "import sys,json; d=json.load(sys.stdin); print(d['equity'])" Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
curl -s "$BASE_URL/v2/account" $HEADERS Copies of this mod
2 near-identical copies found in the catalogue:
- trader-hand-skill — 100% identical, 2 lines differ
- trader-hand-skill — 100% identical, 2 lines differ
How it starts
The opening of the file, as written. The whole thing — 938 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Trading Expert Knowledge
Reference Knowledge
1. Technical Analysis Indicators Reference
RSI (Relative Strength Index)
Formula: RSI = 100 - (100 / (1 + RS))
Where: RS = Average Gain / Average Loss over N periods (default N = 14)
Step-by-step calculation:
1. For each period, compute change = Close(t) - Close(t-1)
2. Gains = max(change, 0), Losses = abs(min(change, 0))
3. First average: simple mean of first 14 gains/losses
4. Subsequent: AvgGain = (PrevAvgGain * 13 + CurrentGain) / 14 (Wilder smoothing)
5. RS = AvgGain / AvgLoss
6. RSI = 100 - (100 / (1 + RS))
Worked example (14-period):
Avg Gain over 14 periods = 1.02
Avg Loss over 14 periods = 0.68
RS = 1.02 / 0.68 = 1.50
RSI = 100 - (100 / (1 + 1.50)) = 100 - 40 = 60.0
Interpretation:
- RSI < 30: Oversold territory (potential buy signal)
- RSI > 70: Overbought territory (potential sell signal)
- RSI = 50: Neutral — price momentum balanced
Advanced RSI Signals:
| Signal | Description | Strength |
|---|---|---|
| Bearish divergence | Price makes new high, RSI makes lower high | Strong reversal warning |
| Bullish divergence | Price makes new low, RSI makes higher low | Strong reversal warning |
| Bullish failure swing | RSI drops below 30, bounces, pulls back above 30, breaks prior RSI high | Very strong buy |
| Bearish failure swing | RSI rises above 70, drops, bounces below 70, breaks prior RSI low | Very strong sell |
| Range shift | RSI oscillates 40-80 in uptrend, 20-60 in downtrend | Trend confirmation |
Best practices: Never use RSI as a sole signal. Combine with trend direction (moving averages) and volume. In strong trends, RSI can stay overbought/oversold for extended periods.
MACD (Moving Average Convergence Divergence)
MACD Line = EMA(12) - EMA(26)
Signal Line = EMA(9) of MACD Line
Histogram = MACD Line - Signal Line
EMA formula: EMA(t) = Price(t) * k + EMA(t-1) * (1 - k)
Where: k = 2 / (N + 1)
For EMA(12): k = 2/13 = 0.1538
For EMA(26): k = 2/27 = 0.0741
Worked example:
EMA(12) = 155.20
EMA(26) = 152.80
MACD Line = 155.20 - 152.80 = 2.40
Previous Signal Line = 1.80
Signal Line = 2.40 * (2/10) + 1.80 * (8/10) = 0.48 + 1.44 = 1.92
Histogram = 2.40 - 1.92 = 0.48 (positive = bullish momentum increasing)
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 5d ago First seen · 938 lines · 28 tokens per session scan D cae8909d1696
trader-hand-skill is a skill published in the GitHub repository RightNow-AI/openfang (18,166 stars, last pushed 2mo ago), licensed Apache-2.0. It adds 28 tokens to every session and 11,286 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it D with 3 findings (sends data to an external url, downloads and executes remote code, makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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