debug-performance

debug-performance is a Runtime diagnostics & profiling skill for AI agents, published by QuantConnect in the Documentation repository on GitHub. Skillspace rates debug-performance D (59/100) and it passed the safety scan; the rating is based on static analysis only.

Diagnoses slow QuantConnect Python (.py) and C# (.cs) backtests using the Performance Chart first and Python cProfile only when the chart does not pinpoint the hot function. Trigger phrases: "slow backtest", "high CPU", "algorithm slow", "CPU usage", "RAM usage", "memory usage", "performance chart", "profiling", "bottleneck", "debug performance", "taking too long", "optimize algorithm".

Grade
D
Quality
59 / 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
84 / 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

  • 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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