New: 98,000+ skills indexed from GitHub repos with 100+ stars · every skill safety-checkedBrowse top skillsTop skills
Esc to closeBrowse all skills
Submit a skillBrowse skills
Submit a skillBrowse skills

Agent skill

Operational Enterprise AI

by boraoztunc in boraoztunc/skills

Create or redesign enterprise AI, automation, security, and operations product pages that explain system boundaries, approvals, auditability, exceptions, and rollback.

Apache-2.0Auto-check passedDevOps & Cloud

Install Operational Enterprise AI

skills CLI
$ npx skills add boraoztunc/skills --skill operational-enterprise-ai -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install boraoztunc/skills operational-enterprise-ai --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/boraoztunc/skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/operational-enterprise-ai .claude/skills/operational-enterprise-ai && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
operational-enterprise-ai
GitHub stars
398
Used in
2 other repos
Token cost
~1.2k tokens
SKILL.md length
570 words
Files
2
Skills in repo
52
Repo updated
First seen
Licence
Apache-2.0

At a glance

Create or redesign enterprise AI, automation, security, and operations product pages that explain system boundaries, approvals, auditability, exceptions, and rollback.

  • Works in 5 steps: Open with the operational problem and… → Use a white interlude to quantify the… → Explain each capability as a workflow… → …
  • Dark cinematic heroes
  • SKILL.md covers Establish the Story, Build the Visual System, Compose the Page and Implement Operational Solution…, plus 4 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Operational Enterprise AI is an agent skill from boraoztunc/skills. Create or redesign enterprise AI, automation, security, and operations product pages that explain system boundaries, approvals, auditability, exceptions, and rollback. Use for dark cinematic heroes, hairline grids, metric pauses, expandable solution rows, case-study evidence, security proof, and qualified demo or waitlist handoffs.

Its SKILL.md is about 1.2k tokens, which your agent loads only when the skill is triggered. The skill folder holds 1 other file (for example `REFERENCES.md`).

It sits in DevOps & Cloud. The repository describes itself as: Claude Code skills for copywriting, SEO, design, and more. The licence is Apache-2.0.

When your agent uses it

  • Dark cinematic heroes
  • Expandable solution rows
  • Case-study evidence
  • Waitlist handoffs

Example prompts

  • “/operational-enterprise-ai”

Workflow steps

5 steps, taken from the first numbered list in SKILL.md.

  1. Open with the operational problem and one restrained product image or system trace.
  2. Use a white interlude to quantify the problem with verified metrics.
  3. Explain each capability as a workflow with permissions and controls.
  4. Address security, governance, exceptions, and rollback before the conversion ask.
  5. Move from verified case-study evidence into a qualified demo or waitlist handoff.

What it can do on your machine

Read from SKILL.md and the folder at commit 645553c. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md.

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Operational Enterprise AI loads about 1.2k tokens when it runs. Until then it costs about 90 tokens; SKILL.md has 570 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~90
When it runs · the whole SKILL.md, loaded when a task matches
~1.2k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from boraoztunc/skills at commit 645553c, republished under its Apache-2.0 licence (© boraoztunc). 570 words, ~1,160 tokens.

Download SKILL.mdSave it as .claude/skills/operational-enterprise-ai/SKILL.md (or your agent's skills folder). This skill also uses 1 other file; get the full folder from GitHub.
name
operational-enterprise-ai
description
Create or redesign enterprise AI, automation, security, and operations product pages that explain system boundaries, approvals, auditability, exceptions, and rollback. Use for dark cinematic heroes, hairline grids, metric pauses, expandable solution rows, case-study evidence, security proof, and qualified demo or waitlist handoffs.

Operational Enterprise AI

Build credibility by showing what the system does, where it stops, who approves actions, and how failures recover.

Establish the Story

  1. Open with the operational problem and one restrained product image or system trace.
  2. Use a white interlude to quantify the problem with verified metrics.
  3. Explain each capability as a workflow with permissions and controls.
  4. Address security, governance, exceptions, and rollback before the conversion ask.
  5. Move from verified case-study evidence into a qualified demo or waitlist handoff.

Replace source brands, customers, numbers, security badges, screenshots, and claims. Do not invent compliance or performance evidence.

Build the Visual System

  • Use near-black, warm white, muted gray, and one restrained spectral treatment.
  • Pair a high-x-height sans-serif with compact mono labels and tabular numerals.
  • Use hard grid lines, square media, low radii, and minimal shadow.
  • Keep data legibility ahead of atmosphere.
  • Reserve white chapters for operational explanation and metric pauses.
  • Avoid glowing AI orbs, particle fields, neon gradients, and generic cyber-security imagery.

Compose the Page

  • Header: show product, solutions, security, case studies, and one qualified action.
  • Hero: state the system boundary and pair it with one deliberate operational visual.
  • Metrics: use only verified numbers with scope, source, and timeframe.
  • Solution rows: summarize workflow, permissions, action, approval, output, audit, exception, and rollback.
  • Product demo: show real or clearly labeled sample data and deterministic state changes.
  • Security: connect controls to concrete risks; do not use unsupported badges.
  • Case studies: separate verified implementation facts from marketing interpretation.
  • Testimonials: use grayscale portrait evidence only when licensed and real.
  • FAQ: resolve ownership, data handling, integrations, review, failure, and procurement questions.
  • Final CTA: qualify who the product is for and explain what happens after submission.

Implement Operational Solution Rows

  • Keep summary, permissions, action, approval, output, audit, exception, and rollback in a stable data model.
  • Use semantic disclosure with equivalent hover and focus cues.
  • Support Enter and Space expansion and keep text equivalents for diagrams.
  • Design loading, unavailable integration, insufficient permission, stale data, denied approval, partial completion, rollback, and error states.
  • Keep the buyer able to evaluate scope and risk without animation.
Show full SKILL.md (221 more words)Show less

Implement the Case-Study Handoff

  • Connect each verified use case to the relevant demo or waitlist context.
  • Preserve attribution and separate facts, quotes, and inferred outcomes.
  • Prefill only non-sensitive intent data and only with consent.
  • Design filters, links, form fields, loading, disabled, duplicate, validation, network error, and success states.
  • Explain who receives the request, expected response, and data use.

Motion Defaults

  • Use 160–220ms for controls and 500–760ms for section entrances.
  • Favor slow background media, precise metric reveals, and restrained row transitions.
  • Use hard black-to-white handoffs instead of gratuitous smooth scrolling.
  • Keep parallax below 5%, pause offscreen work, and clean up observers.
  • Render settled states immediately under reduced motion.

Validate

  • Review every metric, case study, quote, badge, and compliance statement against evidence.
  • Test solution rows, filters, forms, errors, focus return, and browser history with keyboard and touch.
  • Verify diagram text alternatives, contrast, 200% zoom, mobile order, loading, stale data, and reduced motion.
  • Confirm the visitor can state what the product controls, what requires approval, and how rollback works.
  • Remove unsupported security, availability, performance, accessibility, or compliance claims.

Avoid

  • Magical automation claims with no permissions or exception model.
  • Fake dashboards, metrics, customers, badges, or case-study outcomes.
  • Glowing AI orbs, particle clouds, and cyberpunk decoration.
  • A generic sales leap from feature list to contact form.
  • Hiding risk, audit, failure, or rollback details behind vague copy.

© boraoztunc, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 1 other file in operational-enterprise-ai of boraoztunc/skills.

  • SKILL.md
  • REFERENCES.md

Open the folder on GitHubat commit 645553c

Used in 2 other repositories

We found 2 copies of this SKILL.md (exact, near-identical or edited) in other folders, from 2 other GitHub owners. This page covers the copy in boraoztunc/skills, which our catalogue first saw on October 7, 2026.

Compare with similar skills

Operational Enterprise AI next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Operational Enterprise AI compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Operational Enterprise AI this skillboraoztunc/skills3982 repos~1.2kAutomated safety check: PassApache-2.0
Monitor CInrwl/nx29k6 repos~4.7kAutomated safety check: PassMIT
Terraform and OpenTofu Guideagentscope-ai/QwenPaw36k6 repos~4.2kAutomated safety check: PassApache-2.0
Vercel Optimize Auditvercel-labs/agent-skills32k8 repos~4.3kAutomated safety check: PassNone
Analyze GitHub Action Logswithastro/astro63k1 repos~1.3kAutomated safety check: PassCustom licence
Openclaw Live Updateropenclaw/openclaw392k—~3.7kAutomated safety check: PassMIT

Similar skills

  • Monitor CI

    nrwl/nx

    Monitor Nx Cloud CI pipeline and handle self-healing fixes. An agent skill from nrwl/nx.

    29k GitHub starsUsed in 6 repos~4.7k tokens
    DevOps & CloudAuto-check passed

  • Terraform and OpenTofu Guide

    agentscope-ai/QwenPaw

    Guidance for writing and testing Terraform and OpenTofu code: module structure, naming, test approaches, CI/CD workflows, state handling and security scanning.

    36k GitHub starsUsed in 6 repos~4.2k tokens
    DevOps & CloudAuto-check passed

  • Vercel Optimize Audit

    vercel-labs/agent-skills

    Official

    Runs a metrics-first audit of a deployed Vercel project, gating investigations on real signals to produce ranked, citation-backed cost and performance recommendations.

    32k GitHub starsUsed in 8 repos~4.3k tokens
    DevOps & CloudAuto-check passed

  • Analyze GitHub Action Logs

    withastro/astro

    Official

    Analyze recent GitHub Actions workflow runs to identify patterns, mistakes, and improvements.

    63k GitHub starsUsed in 1 repo~1.3k tokens
    DevOps & CloudAuto-check passed

  • Openclaw Live Updater

    openclaw/openclaw

    Maintain the canonical live OpenClaw main checkout, macOS LaunchAgent-managed Gateway, local macOS app, exact-head main CI, and recurring full release validation.

    392k GitHub stars~3.7k tokensUpdated today
    DevOps & CloudAuto-check passed

  • Docs Learn PR Preview

    netdata/netdata

    Use only when the user explicitly asks to build, run, preview, inspect, or validate learn.netdata.cloud locally using the contents of a PR or documentation branch before merge.

    81k GitHub stars~2k tokensUpdated today
    DevOps & CloudAuto-check passed

More from boraoztunc/skills

All 52 skills in this repo

  • Gsap

    boraoztunc/skills

    GSAP animation reference for HyperFrames. An agent skill from boraoztunc/skills.

    398 GitHub starsUsed in 5 repos~1.9k tokens
    Auto-check passed

  • Hyperframes

    boraoztunc/skills

    Create video compositions, animations, title cards, overlays, captions, voiceovers, audio-reactive visuals, and scene transitions in HyperFrames HTML.

    398 GitHub starsUsed in 9 repos~7.6k tokens
    Auto-check passed

  • Remotion To Hyperframes

    boraoztunc/skills

    Translate an existing Remotion (React-based) video composition into a HyperFrames HTML composition.

    398 GitHub stars~2.2k tokensUpdated 1 mo ago
    Auto-check passed

  • Animejs

    boraoztunc/skills

    Anime.js adapter patterns for HyperFrames. An agent skill from boraoztunc/skills.

    398 GitHub starsUsed in 2 repos~828 tokens
    Auto-check passed

  • Beam Glow States

    boraoztunc/skills

    Create React loading, processing, selected, current, focus, and pressed states with the border-beam package's animated edge glow.

    398 GitHub starsUsed in 2 repos~3.2k tokens
    Auto-check passed

  • Minimal Zine Poster

    boraoztunc/skills

    Compile a theme, sentence, object, mood, article idea, or photo into a quiet Japanese/Korean zine-style editorial poster — tall aged paper, large negative space, one small image anchor, experimental…

    398 GitHub stars~2.5k tokensUpdated 1 mo ago
    Auto-check passed

Categories

Questions about Operational Enterprise AI

What does Operational Enterprise AI do?

Create or redesign enterprise AI, automation, security, and operations product pages that explain system boundaries, approvals, auditability, exceptions, and rollback. Operational Enterprise AI is an agent skill from boraoztunc/skills. Create or redesign enterprise AI, automation, security, and operations product pages that explain system boundaries, approvals, auditability, exceptions, and rollback.

When should I use Operational Enterprise AI?

Operational Enterprise AI fits situations like: dark cinematic heroes; expandable solution rows; case-study evidence; waitlist handoffs.

How do I install Operational Enterprise AI in Claude Code?

Run `npx skills add boraoztunc/skills --skill operational-enterprise-ai -a claude-code`. Or copy the skill folder (operational-enterprise-ai in boraoztunc/skills) into .claude/skills/operational-enterprise-ai in your project. Claude Code loads it when a task matches its description.

How do I install Operational Enterprise AI in Codex?

Run `npx skills add boraoztunc/skills --skill operational-enterprise-ai -a codex`. Or copy the skill folder (operational-enterprise-ai in boraoztunc/skills) into .agents/skills/operational-enterprise-ai in your project. Codex loads it when a task matches its description.

Can I use Operational Enterprise AI in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add boraoztunc/skills --skill operational-enterprise-ai -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/operational-enterprise-ai, .gemini/skills/operational-enterprise-ai, .github/skills/operational-enterprise-ai and .opencode/skills/operational-enterprise-ai in your project.

What does Operational Enterprise AI need to run?

SKILL.md names no scripts, command-line tools or credentials: Operational Enterprise AI is instructions for the agent only.

Does Operational Enterprise AI access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Operational Enterprise AI safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Operational Enterprise AI use?

Operational Enterprise AI is published under the Apache-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Operational Enterprise AI use?

About 1.2k tokens (SKILL.md is roughly 4.6k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Operational Enterprise AI?

Skills that share tags, products or a category with Operational Enterprise AI: Monitor CI (nrwl/nx, 29k stars), Terraform and OpenTofu Guide (agentscope-ai/QwenPaw, 36k stars), Vercel Optimize Audit (vercel-labs/agent-skills, 32k stars) and Analyze GitHub Action Logs (withastro/astro, 63k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Operational Enterprise AI?

boraoztunc (a GitHub user) maintains it in boraoztunc/skills, which has 398 GitHub stars. The repository holds 52 skills in this directory. The repository was last updated on August 15, 2026.

Source: boraoztunc/skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.