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/xingwudao/open-xquant/plot-indicatorsnpx skills add xingwudao/open-xquant --skill plot-indicatorsgit clone --depth 1 https://github.com/xingwudao/open-xquantWrote 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/xingwudao/open-xquant/plot-indicators)<a href="https://agentmods.dev/skills/xingwudao/open-xquant/plot-indicators"><img src="https://agentmods.dev/badge/skills/xingwudao/open-xquant/plot-indicators.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 | $0.00030 | $0.00325 |
| Opus 5 | $0.00015 | $0.00162 |
| Sonnet 5 | $0.00006 | $0.00065 |
| Haiku 4.5 | $0.00003 | $0.00032 |
Grade A, and why
plot-indicators scanned grade A with 0 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 4d 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.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
What it actually says
Chart Indicator
You create visual checks. Charts do not replace validation or audit.
Current Tool Signature
oxq.tools.chart.chart_indicator plots indicator columns from a stored
RunResult in the tool session:
from oxq.tools.chart import chart_indicator
result = chart_indicator(
run_id="run_1",
symbol="SPY",
columns=["sma_fast", "sma_slow"],
overlay=True,
)
print(result)
It does not accept raw data=..., indicators=..., or output=...
arguments. If you need a chart from raw bars, either run the strategy through
the tool/session flow first or write a one-off exploratory script and label it
as non-standard.
Dependency
Install chart dependencies before rendering:
uv sync --extra chart
If using pip:
python -m pip install -e ".[chart]"
What To Check
- requested columns exist in the run's symbol data
- NaN warmup regions are expected
- indicator scale matches overlay choice
- signal events line up with intended dates
- chart output path exists
Red Lines
- Do not use charts as proof of profitability.
- Do not hide missing indicator columns by plotting a different column.
- Do not infer causality from visual overlap alone.
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.
- 4d ago First seen · 61 lines · 30 tokens per session scan A 18616e38926e
plot-indicators is a skill published in the GitHub repository xingwudao/open-xquant (124 stars, last pushed 6d ago), licensed MIT. It adds 30 tokens to every session and 325 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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