indicator-universes

indicator-universes is an Investment analysis & markets skill for AI agents, published by QuantConnect in the Documentation repository on GitHub. Skillspace rates indicator-universes D (65/100) and it passed the safety scan; the rating is based on static analysis only.

Use when selecting a QuantConnect/LEAN universe based on per-symbol indicators. Triggers — code uses py`add_universe(...)`cs`AddUniverse(...)` with a selection callback that builds per-symbol `SimpleMovingAverage`/`ExponentialMovingAverage`/`BollingerBands`/`RSI`/`ATR` etc., often via a `SelectionData` class kept in a per-symbol dict; questions like "rank stocks by 21-day SMA", "top N most volatile crypto pairs", "fundamentals universe with momentum filter", "why does my SMA spike around splits/dividends", "why does my universe shrink during warm-up", "how do I avoid history calls in universe selection". Skip when — universe doesn't need per-symbol indicators (use plain fundamentals/ETF/CryptoUniverse selection).

Grade
D
Quality
65 / 100
Safety
Passed
GitHub stars
257

Unproven: rated by static analysis only, not yet compared head-to-head.

Our two independent classifiers differ on this skill's category, so treat the placement as provisional.

This rating describes the version of the repository we crawled; it may have changed since, so go by its current files.

View source on GitHubQuantConnect/Documentation

Our review

Architecture
95 / 100
Maturity
Basic: a single SKILL.md
Security scan
No issues found
License
Apache-2.0
Adoption
Adopted by 0 other repositories, in 0 collections

Not checked yet

  • Category is a classifier prediction; no model has read this skill yet
  • Not judged on the rubric yet (not a contender in its category)
  • No blind task eval yet
  • Scope (portable / vendor / repo-internal) not assessed; only the top of each category is read for scope
  • Sibling files (scripts, references) not fetched; security scan covers SKILL.md only

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