llm-app-basics
llm-app-basics is an LLM app frameworks & APIs skill for AI agents, published by Shubchynskyi in the garda-agent-orchestrator repository on GitHub. Skillspace rates llm-app-basics D (68/100) and it passed the safety scan; the rating is based on static analysis only.
Production foundations for LLM-powered applications: prompt architecture, context assembly, structured output enforcement, guardrails, model fallback, cost/latency budgeting, and deterministic runtime behavior patterns. Use when a task creates or modifies prompt templates, model configuration, output schemas, guardrail/moderation layers, token-budget logic, or any code that sends requests to an LLM provider and processes the response in a production path. Trigger phrases: llm app, prompt architecture, structured output, guardrail, model config, llm production, model fallback, token budget. Do NOT use for RAG retrieval/chunking (use rag-patterns), multi-step tool orchestration (use tool-calling-patterns), or evaluation harness design (use evals-design).
- Grade
- D
- Quality
- 68 / 100
- Safety
- Passed
- GitHub stars
- 24
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
- 84 / 100
- Maturity
- Packaged: licensed, with a version or references
- Security scan
- Low-risk patterns
- License
- Apache-2.0
- Adoption
- Adopted by 0 other repositories, in 0 collections
What the scanner flagged
- mentions secrets in text
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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