visual-intelligence-mcp: Skill for Claude Code

.agents/skills/openspec-onboard/SKILL.md

openspec-onboard is a skill for Claude Code from KOG123/visual-intelligence-mcp. It costs 26 tokens per session (4,072 once invoked), scanned A, a copy of openspec-onboard, MIT.

A guided introduction to OpenSpec, a workflow for describing software changes as structured specifications before or during implementation.

In plain words
What is it for?
Checking the CLI, creating and managing changes, reading and validating specifications, and completing a first workflow cycle.
Why use it?
It teaches the complete workflow while applying it to a real codebase, including how to select and use an OpenSpec repository.

Skill for Claude Code

Written for Claude Code: allowed-tools in frontmatter. Also seen: installed under .agents/ (shared by several agents); mentions Codex; $skill-name invocation.

This is KOG123/visual-intelligence-mcp's own configuration. It tells Claude Code how to work on visual-intelligence-mcp itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything visual-intelligence-mcp configures →

Reuse

Borrowing it

Nothing to install: this file belongs to KOG123/visual-intelligence-mcp. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file
curl -O https://raw.githubusercontent.com/KOG123/visual-intelligence-mcp/main/.agents/skills/openspec-onboard/SKILL.md
Clone the repo
git clone --depth 1 https://github.com/KOG123/visual-intelligence-mcp

Made for: Claude Code.

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 openspec-onboard

README.md
[![agentmods](https://agentmods.dev/badge/skills/kog123/visual-intelligence-mcp/openspec-onboard.svg)](https://agentmods.dev/skills/kog123/visual-intelligence-mcp/openspec-onboard)
Your own site
<a href="https://agentmods.dev/skills/kog123/visual-intelligence-mcp/openspec-onboard"><img src="https://agentmods.dev/badge/skills/kog123/visual-intelligence-mcp/openspec-onboard.svg" alt="Measured on agentmods" height="20"></a>
Per session 26 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 4,072 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin 92% copy Near-identical to another mod 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 $0.00026 $0.04072
Opus 5 $0.00013 $0.02036
Sonnet 5 $0.00005 $0.00814
Haiku 4.5 $0.00003 $0.00407

Measured 6d ago against content hash 2bcc69886e0c, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-06, from the pricing page.

Security

Grade A, and why

openspec-onboard 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 6d 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.

Origin

This is a copy

92% identical to openspec-onboard — 55 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

.agents/skills/openspec-onboard/SKILL.md · 562 lines

How it starts

The opening of the file, as written. The whole thing — 562 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Guide the user through their first complete OpenSpec workflow cycle. This is a teaching experience—you'll do real work in their codebase while explaining each step.

Store selection: If the user names a store (a store is a standalone OpenSpec repo registered on this machine) or the work lives in one, run openspec store list --json to discover registered store ids, then pass --store <id> on the commands that read or write specs and changes (new change, status, instructions, list, show, validate, archive, doctor, context, view). Once selected, treat --store <id> as sticky for the rest of the workflow. Every unscoped example of those commands below is shorthand: before running it, append the flag. For example, run openspec status --change "<name>" --json --store "<id>", not the unscoped form shown below. Other commands do not take the flag. Hints printed by commands already carry the flag; keep it on follow-ups. Without a store, commands act on the nearest local openspec/ root.


Preflight

Before starting, check if the OpenSpec CLI is installed:

# Unix/macOS
openspec --version 2>&1 || echo "CLI_NOT_INSTALLED"
# Windows (PowerShell)
# if (Get-Command openspec -ErrorAction SilentlyContinue) { openspec --version } else { echo "CLI_NOT_INSTALLED" }

If CLI not installed:

OpenSpec CLI is not installed. Install it first, then come back to $openspec-onboard (Codex) or /openspec-onboard (other agents).

Stop here if not installed.


Phase 1: Welcome

Display:

## Welcome to OpenSpec!

I'll walk you through a complete change cycle—from idea to implementation—using a real task in your codebase. Along the way, you'll learn the workflow by doing it.

**What we'll do:**
1. Pick a small, real task in your codebase
2. Explore the problem briefly
3. Create a change (the container for our work)
4. Build the artifacts: proposal → specs → design → tasks
5. Implement the tasks
6. Archive the completed change

**Time:** ~15-20 minutes

Let's start by finding something to work on.

Read the full file on GitHub · 562 lines

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. 6d ago First seen · 562 lines · 26 tokens per session scan A 2bcc69886e0c

Subscribe to this mod's changes

openspec-onboard is a skill published in the GitHub repository KOG123/visual-intelligence-mcp (2 stars, last pushed 12d ago), licensed MIT. It adds 26 tokens to every session and 4,072 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. It is 92% identical to openspec-onboard, differing in 55 lines, and is treated as a copy.

Related

Other skills, from other repositories

systematic-debugging

Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.

obra/superpowers · 21 tokens

local-ai-agents

Build local-first AI agents that run entirely on a developer workstation with Microsoft Foundry Local and Qwen function-calling models. Covers Small Language Models (SLMs), the OpenAI-compatible local endpoint, sandboxed local tools, local RAG with Chroma, local MCP servers, hybrid cloud/local routing, and the…

microsoft/ai-agents-for-beginners · 200 tokens

next-cache-components-adoption

Turn on Cache Components in a Next.js app and resolve the blocking routes it surfaces. Use when the user wants to enable, adopt, or migrate to Cache Components, flip the cacheComponents flag, work through a flood of blocking-prerender / instant validation errors, run the cache-components-instant-false codemod, or…

vercel/next.js · 95 tokens

chat-pet-sprite-creation

Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.

microsoft/vscode · 53 tokens

cpu-profile-analysis

Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…

microsoft/vscode · 71 tokens

insight-error-page

Write or audit an insight-kind error page for the Next.js dev overlay. Use when creating a new errors/ .mdx page, auditing an existing one, or checking that a page matches the framework fix cards. Covers page structure, title alignment, FixCard cards with Copy prompt button, code snippets, terminology verification…

vercel/next.js · 83 tokens