llm-app-development skillA
llm-app-development is agent-read markdown (skill) from iuliandita/skills: Build LLM applications: RAG, embeddings, agents, structured outputs, evaluations, fine-tuning, and local inference..
Indexed from public GitHub and served as immutable, content-addressed versions. Install it pinned to an exact SHA-256 with the mdr CLI, and every file is verified against the hash recorded here before it reaches your agent. The deterministic audit below grades the latest version, and the same file always earns the same grade.
What the file says
# LLM Application Development Build, review, and architect applications that use AI models - from single-API calls to multi-agent systems with RAG pipelines. The goal is production-grade AI apps that are reliable, cost-effective, and don't hallucinate their way into an incident. **Target versions**: September 2026 snapshot. Read `references/target-versions.md` before pinning model IDs (Claude/OpenAI families), SDKs, runtimes, vector stores, or evaluation tools. ## When to use - Integrating LLM APIs (Anthropic, OpenAI, etc.) into applications - Building RAG pipelines (chunking, embedding, retrieval, generation) - Designing agent systems (tool use, loops, state, multi-agent) - Choosing between fine-tuning, RAG, and prompt engineering - Setting up vector stores for semantic search - Implementing structured output and tool use / function calling - Building evaluation and testing harnesses for AI features - Optimizing token costs, latency, and model routing - Setting up local inference with Ollama or vLLM - Adding safety guardrails (content filtering, PII handling, output validation) ## When NOT to use - Building MCP servers or tools (use **mcp** - it handles the protocol layer) …
Read the whole file at its exact version.
How to install
mdr add iuliandita/skills/llm-app-development@git:20260920.ebf9a3dmdr add iuliandita/skills/llm-app-development@sha256:66707cbbea8db2eePin to a label to follow the author's releases, or to a sha256 to freeze the exact bytes forever. Either way the resolved hash is written to mdr.lock, and mdr install reproduces it on any machine.
[](https://markdownregistry.com/a/art_552ozi2u7duxa6e7)
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Versions
| version | committed | commit | size | audit | |
|---|---|---|---|---|---|
| git:20260920.ebf9a3d latest | 2026-09-20 | ebf9a3d | 24,754 B | A | view · diff |
| git:20260920.ac01853 | 2026-09-20 | ac01853 | 24,643 B | A | view |
Audit of the latest version
- pass: Frontmatter block present
- pass: Frontmatter declares a name
- pass: Frontmatter declares a description
- pass: Size between 200 bytes and 200 KB (24754 bytes)
- pass: No zero-width or bidi control characters
- pass: No instruction hidden inside an HTML comment
- pass: No link to an exfiltration or paste host
- pass: No credential-shaped string
- pass: No instruction to send local credentials anywhere
- pass: No text hidden with inline styles
- pass: No prompt-injection phrasing
- pass: No curl or wget piped into a shell
- pass: No recursive delete of root, home or parent
- pass: No instruction to read or print local credentials
- pass: No base64 blob over 200 characters
- pass: No link to a raw IP address
- pass: No script tag
Source
iuliandita/skills · 7 stars · license MIT · pushed 2026-09-24 · branch main
API
GET https://markdownregistry.com/api/v1/artifacts/art_552ozi2u7duxa6e7 GET https://markdownregistry.com/api/v1/resolve?ref=iuliandita/skills/llm-app-development GET https://markdownregistry.com/api/v1/blob/66707cbbea8db2ee3de5112dfd194c96140380b5a614b9b1c95aeb770fa9b9d7
Your agent does the legwork. You hear about the deals worth your word. Hand yours the standing instructions at modelranch.com and it joins the network that reads files like this one.