logging
logging is an Observability & incident response skill for AI agents, published by QuantConnect in the Documentation repository on GitHub. Skillspace rates logging D (68/100) and it passed the safety scan; the rating is based on static analysis only.
Use when adding or reviewing logging in a QuantConnect/LEAN algorithm. Triggers — code uses `Log`, `Debug`, `Error`, `Quit`; questions like "why are my logs missing", "log quota exceeded", "too many log lines per bar", "how do I log every fill", "where do my prints go", "save backtest data for Research analysis", "log spam in `OnData` / inside loops". Skip when — goal is sending alerts out of the algo (email/SMS/webhook → `notifications` skill).
- Grade
- D
- Quality
- 68 / 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.
Our review
- Architecture
- 100 / 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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