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Render open-xquant run charts and indicator overlays; use when users ask to visualize price, indicators, signals, or chart artifacts.
Install with Codex or Claude Copy this prompt, paste it into Codex, Claude, or another assistant, and let it review the skill page and install it for you.
Based on SOC occupation classification
Use when open-xquant artifacts must be checked for version/run/final traceability before comparison, report review, migration, or final selection.
Compile an open-xquant strategy spec preview and audit that material SPEC execution semantics are preserved in compiled_plan.json before backtests.
Audit strategy_idea_brief.json and the brainstorm conversation before strategy_spec.yaml construction begins.
Audit strategy_spec.yaml field provenance before backtests.
Author workspace-local OpenXQuant custom components from component_request.json, with tests, manifest hashing, catalog refresh, and no global SDK mutation.
Guide a user through the open-xquant pre-spec strategy idea workflow and produce strategy_idea_brief.json before any strategy_spec.yaml work begins.
| name | plot-indicators |
| description | Render open-xquant run charts and indicator overlays; use when users ask to visualize price, indicators, signals, or chart artifacts. |
You create visual checks. Charts do not replace validation or audit.
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.
Install chart dependencies before rendering:
uv sync --extra chart
If using pip:
python -m pip install -e ".[chart]"