ai-engineer

ai-engineer is a skill for Claude Code, Codex from belokonm/claude-supercode-skills. It costs 49 tokens per session (703 once invoked), scanned A, original, no licence file.

A guide for building production software that uses large language models, document search, or autonomous agents. RAG is a method that lets an AI answer using retrieved source documents.

In plain words
What is it for?
Use it to build AI features, connect language models, design document-retrieval pipelines, and deploy AI systems.
Why use it?
It helps connect AI models and related components into a complete application rather than treating them as isolated experiments.

Skill for Claude CodeCodex

Which agent this was written for is unclear — body not stored (licence); the path alone says nothing.

Good fit Use it to build AI features, connect language models, design document-retrieval pipelines, and deploy AI systems.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/belokonm/claude-supercode-skills/ai-engineer-skill
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add belokonm/claude-supercode-skills --skill ai-engineer-skill
Clone the repo
git clone --depth 1 https://github.com/belokonm/claude-supercode-skills

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for ai-engineer

README.md
[![agentmods](https://agentmods.dev/badge/skills/belokonm/claude-supercode-skills/ai-engineer-skill/github.svg)](https://agentmods.dev/skills/belokonm/claude-supercode-skills/ai-engineer-skill)
Your own site
<a href="https://agentmods.dev/skills/belokonm/claude-supercode-skills/ai-engineer-skill"><img src="https://agentmods.dev/badge/skills/belokonm/claude-supercode-skills/ai-engineer-skill/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for ai-engineer

Your own site · 80×15
<a href="https://agentmods.dev/skills/belokonm/claude-supercode-skills/ai-engineer-skill"><img src="https://agentmods.dev/badge/skills/belokonm/claude-supercode-skills/ai-engineer-skill.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 49 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 703 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin unknown No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00049 $0.00703
Opus 5 $0.00024 $0.00351
Sonnet 5 $0.00010 $0.00141
Haiku 4.5 $0.00005 $0.00070

Measured 9d ago against content hash cc2010532d0a, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-09, from the pricing page.

Security

Grade A, and why

ai-engineer scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 9d ago.

The scan reads SKILL.md. This mod also ships 5 executable files (scripts/integrate_anthropic.py, scripts/integrate_openai.py, scripts/monitor_ai_service.py, …), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

ai-engineer-skill/SKILL.md · 87 lines

The source is not reproduced here

No licence file

A repository with no LICENSE is all rights reserved by default, so the body is not copied here. The metadata, the measurements and the link are.

Read it on GitHub

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 9d ago First seen · 87 lines · 49 tokens per session scan A cc2010532d0a

Subscribe to this mod's changes

ai-engineer is a skill published in the GitHub repository belokonm/claude-supercode-skills (11 stars, last pushed 7mo ago), with no licence file. It adds 49 tokens to every session and 703 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.

Related

Other skills, from other repositories

agent-platform-rag-engine-management

Manage and query Agent Platform RAG Engine Corpora and retrieve grounded contexts using the Google GenAI SDK. Use when listing RAG corpora or files, inspecting a corpus, retrieving contexts, or generating content grounded in a RAG corpus. Do not use for standard database queries (use SQL/Spanner skills), Google…

google/skills · 85 tokens

llm-app-patterns

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.

davila7/claude-code-templates · 54 tokens

9router-embeddings

Generate vector embeddings via 9Router /v1/embeddings using OpenAI / Gemini / Mistral / Voyage / Nvidia / GitHub embedding models for RAG, semantic search, similarity. Use when the user wants embeddings, vectors, RAG, semantic search, or to embed text.

decolua/9router · 66 tokens

azure-search-documents-dotnet

Azure AI Search SDK for .NET (Azure.Search.Documents). Use for building search applications with full-text, vector, semantic, and hybrid search. Covers SearchClient (queries, document CRUD), SearchIndexClient (index management), and SearchIndexerClient (indexers, skillsets). Triggers: "Azure Search .NET"…

microsoft/skills · 102 tokens

browserwing-admin

Manage and operate BrowserWing — an intelligent browser automation platform. Install dependencies, configure LLM, create/manage/execute automation scripts, use AI-driven exploration to generate scripts, browse the script marketplace, and troubleshoot issues.

MemTensor/MemOS · 47 tokens

similarity-search-patterns

Implement efficient similarity search with vector databases. Use when building semantic search, implementing nearest neighbor queries, or optimizing retrieval performance.

foryourhealth111-pixel/Vibe-Skills · 30 tokens