llm-app-patterns
llm-app-patterns is an LLM evaluation & observability skill for AI agents, published by diegosouzapw in the awesome-omni-skill repository on GitHub. Skillspace rates llm-app-patterns F (34/100) and it passed the safety scan; the rating is based on static analysis only.
Production-ready patterns for building LLM applications. Covers RAG pipelines, agent architectures, prompt IDEs, and LLMOps monitoring. Use when designing AI applications, implementing RAG, building agents, or setting up LLM observability.
- Grade
- F
- Quality
- 34 / 100
- Safety
- Passed
- GitHub stars
- 48
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
- 57 / 100
- Maturity
- Incomplete: missing or partial frontmatter
- Security scan
- Low-risk patterns
- License
- Not declared. Check the repository before reusing it.
- Adoption
- Adopted by 0 other repositories, in 1 collections
What the scanner flagged
- 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
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