arize-instrumentation
arize-instrumentation is an LLM evaluation & observability skill for AI agents, published by github in the awesome-copilot repository on GitHub. Skillspace rates arize-instrumentation D (66/100) and the safety scan flagged it for review; the rating is based on static analysis only.
Flagged for review. Read the source before running it.
Adds Arize AX tracing to an LLM application for the first time. Follows a two-phase agent-assisted flow to analyze the codebase then implement instrumentation after user confirmation. Use when the user wants to instrument their app, add tracing from scratch, set up LLM observability, integrate OpenTelemetry or openinference, or get started with Arize tracing.
- Grade
- D
- Quality
- 66 / 100
- Safety
- Needs review
- GitHub stars
- 38,964
Unproven: rated by static analysis only, not yet compared head-to-head.
This rating describes the version of the repository we crawled; it may have changed since, so go by its current files.
Our review
- Architecture
- 96 / 100
- Maturity
- Basic: a single SKILL.md
- Security scan
- Medium-risk patterns
- License
- Not declared. Check the repository before reusing it.
What the scanner flagged
- reads environment variables
- mentions secrets in text
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
Also published in 1 other repo
- Arize-ai/arize-skills Needs review
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