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super-ai-ml-foundation

super-ai-ml-foundation is a skill for Codex from arpitexplores/skills-super. It costs 36 tokens per session (418 once invoked), scanned A, original, MIT.

A guide to the foundations of AI applications, including choosing models, writing prompts, retrieving relevant documents, and searching vector databases.

In plain words
What is it for?
Use it to plan model choices, prompts, safeguards, retrieval-augmented generation, embeddings, indexing, and vector search.
Why use it?
It helps establish the core design before building agents or operational systems, while considering quality, speed, cost, and failure cases.

Skill for Codex

Written for Codex: agents/openai.yaml present.

not rated 2repo 6mo ago A scan 36 tokens original MIT

Good fit Use it to plan model choices, prompts, safeguards, retrieval-augmented generation, embeddings, indexing, and vector search.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/arpitexplores/skills-super/super-ai-ml-foundation
View source ↗ arpitexplores/skills-super
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 arpitexplores/skills-super --skill super-ai-ml-foundation
Clone the repo
git clone --depth 1 https://github.com/arpitexplores/skills-super

Made for: 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 super-ai-ml-foundation

README.md
[![agentmods](https://agentmods.dev/badge/skills/arpitexplores/skills-super/super-ai-ml-foundation/github.svg)](https://agentmods.dev/skills/arpitexplores/skills-super/super-ai-ml-foundation)
Your own site
<a href="https://agentmods.dev/skills/arpitexplores/skills-super/super-ai-ml-foundation"><img src="https://agentmods.dev/badge/skills/arpitexplores/skills-super/super-ai-ml-foundation/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 super-ai-ml-foundation

Your own site · 80×15
<a href="https://agentmods.dev/skills/arpitexplores/skills-super/super-ai-ml-foundation"><img src="https://agentmods.dev/badge/skills/arpitexplores/skills-super/super-ai-ml-foundation.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 36 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 418 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 original 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 $0.00036 $0.00418
Opus 5.5 $0.00014 $0.00167
Sonnet 5.5 $0.00007 $0.00084
Haiku 4.5 $0.00004 $0.00042

Measured 2mo ago against content hash 73a402d3fad9, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

super-ai-ml-foundation 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 2mo ago.

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.

super-ai-ml-foundation/SKILL.md · 56 lines

What it actually says

Super AI/ML Foundation

Overview

Establish the core AI/ML architecture before building agents or ops layers.

User Intent Examples

  • "Need help with AI Engineering for my product/site."
  • "Create a plan for Prompt Engineering."
  • "Audit or improve RAG Engineering."

Workflow

  1. Confirm use case, success criteria, latency, and cost targets.
  2. Select model family and deployment approach (hosted vs self-hosted).
  3. Design prompts, tool interfaces, and guardrails.
  4. Plan and implement RAG: chunking, embeddings, indexing, retrieval.
  5. Validate relevance, quality, and failure modes with small tests.
  6. Document tradeoffs, risks, and next experiments.

Minimal Intake Questions

  • Primary goal or outcome
  • Scope (pages, systems, teams, or timeframe)
  • Constraints (tools, budget, timeline)

Output Format

  • Use-case brief and success metrics
  • Model choice with rationale
  • Prompt and tool plan
  • RAG architecture plan
  • Risks, mitigations, and next steps

Routing Map (Modules)

  • AI Engineering -> references/modules/ai-engineer.md
  • Prompt Engineering -> references/modules/prompt-engineering-patterns.md
  • RAG Engineering -> references/modules/rag-engineer.md

Bundled References

  • references/modules/
  • scripts/
  • assets/
  • agents/

Compatibility Notes

  • If any module references slash commands or tool-specific paths, translate them into plain-language steps.
  • Keep outputs platform-agnostic unless the user specifies a specific tool, stack, or agent.

Guardrails

  • Do not claim benchmark results without data.
  • Separate measured results from hypotheses.
  • Prefer the smallest viable model and simplest retrieval setup.
Files

What ships with it

9 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

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. 2mo ago First seen · 56 lines · 36 tokens per session scan A 73a402d3fad9

Subscribe to this mod's changes

super-ai-ml-foundation is a skill published in the GitHub repository arpitexplores/skills-super (2 stars, last pushed 6mo ago), licensed MIT. It adds 36 tokens to every session and 418 once invoked, about $0.0001 per session on Opus 5.5. 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.

Data and AIPromptingRAG and vectorsagent-skillsai-agentsai-codingautomationmarkdownsuper-skills
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