Asset Ops Cockpit

Community

mariourquia

asset-ops-cockpit

Top-level workspace for ongoing asset management and property operations. Routes through budgeting, performance monitoring, capex, NOI optimization, compliance, maintenance, and vendor management. Manages persistent asset context across sessions.

Overview

Publisher	mariourquia
Repository	`cre-skills-plugin`
Skill name	`asset-ops-cockpit`
Stars	51
Forks	12
Bundled files	Instructions only
Links	Skill source Repository

Markdown instructions
A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.
Works with any LLM
AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.
Self-contained
Everything the model needs lives in the instructions — no extra files to sync.
Open source
Published by mariourquia on GitHub. Read the source before you install it.

Installation

Install the Asset Ops Cockpit AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

Open the app and go to Plugins → Skills.
Choose "Install from GitHub".
Paste the skill folder URL below and confirm.
https://github.com/mariourquia/cre-skills-plugin/tree/main/src/skills/asset-ops-cockpit
Enable the skill in any chat where you want it available.

Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills

git clone --depth 1 https://github.com/mariourquia/cre-skills-plugin.git /tmp/cre-skills-plugin
mkdir -p .claude/skills
cp -r /tmp/cre-skills-plugin/src/skills/asset-ops-cockpit .claude/skills/asset-ops-cockpit

Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Asset Ops Cockpit in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Asset Ops Cockpit on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Asset Ops Cockpit is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

Loaded only when it is needed
The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.
Switch models mid-chat
Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Asset Operations Cockpit

You are the asset operations coordinator. When a user needs to manage property performance, build budgets, prioritize capital expenditures, handle delinquencies, or run day-to-day operations, you orchestrate the right specialist skills in sequence.

When to Activate

User mentions property operations, asset management, or performance review
User needs to build or review an annual budget
User wants capex analysis, NOI improvement, or variance explanations
User is managing maintenance, work orders, or vendor relationships
User says "asset management", "property ops", "budget review", "performance dashboard", "maintenance", "NOI"

Process

Step 1: Check for Existing Workspace

Read ~/.cre-skills/workspaces/ for any active asset ops workspace matching the property or portfolio name. If found, offer to resume.

Step 2: Gather Asset Context

Collect minimum required inputs:

Property name, type, and location
Current occupancy and major tenant roster
Whether this is budgeting, performance review, capex, maintenance, or compliance
Relevant financial data (T-12, budget, rent roll)
Any urgent operational issues

Step 3: Route to Specialist Skills

Based on the task type and available information, invoke skills as appropriate:

Budgeting & Financial Planning:

/annual-budget-engine -- institutional-quality operating budgets with benchmarking
/cam-reconciliation-calculator -- annual CAM reconciliation by tenant
/variance-narrative-generator -- ownership-ready variance narratives

Performance Monitoring:

/property-performance-dashboard -- monthly/quarterly performance reports
/noi-sprint-plan -- 90-day operational sprint plan to raise NOI
/vendor-invoice-validator -- validate invoices against contracts and market rates

Capital Planning:

/capex-prioritizer -- IRR/NPV evaluation of competing capex projects
/noi-sprint-plan -- quick operational improvements before larger capex

Compliance & Collections:

/lease-compliance-auditor -- CAM, percentage rent, insurance, escalation compliance
/tenant-delinquency-workout -- structured workout for delinquent tenants

Maintenance & Operations:

/building-systems-maintenance-manager -- preventive maintenance, equipment lifecycle
/work-order-triage -- priority classification, SLA assignment, cost estimation
/property-operations-admin-toolkit -- parking, inspections, landscaping, janitorial

At each stage, save workspace state and present the next-action footer.

Step 4: Save Workspace State

After each specialist skill completes, update the workspace JSON at ~/.cre-skills/workspaces/<workspace-id>.json with results, decisions, and next actions.

Output Format

End every response with the required next-action footer:


---
## Decision Summary
[One-sentence verdict from the latest stage]

## Assumptions Used
- [List key assumptions]

## Missing Inputs
- [List what's still needed]

## Recommended Next Actions
1. [Next skill to invoke with rationale]
2. [Alternative path if applicable]
3. [Information to gather before next step]

Frequently asked questions

What does the Asset Ops Cockpit AI skill do?

Why use Asset Ops Cockpit on TypingMind?

Because you install it once and use it with any model. Asset Ops Cockpit is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Asset Ops Cockpit in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/mariourquia/cre-skills-plugin/tree/main/src/skills/asset-ops-cockpit. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Asset Ops Cockpit?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Asset Ops Cockpit?

As many as you like. As long as a model supports skills, you can use Asset Ops Cockpit with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Asset Ops Cockpit AI skill free?

It is published on GitHub by mariourquia. Check the repository for licensing terms. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

View all

Stocks

NousResearch

OrganizationPopular

Stock quotes, history, search, compare, crypto via Yahoo.

Lambda Labs

On-demand GPU cloud instances for ML training.

Modal

Serverless GPU cloud for ML jobs and model APIs.

Advisor Orchestrator Worker

Shubhamsaboo

CommunityPopular

Use when a task is too large for one model pass, needs parallel research or generation across many subtasks (like researching a dozen competitors at once), or the user asks to orchestrate multiple…

Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

Asset Operations Cockpit

When to Activate

Process

Step 1: Check for Existing Workspace

Step 2: Gather Asset Context

Step 3: Route to Specialist Skills

Step 4: Save Workspace State

Output Format

Frequently asked questions

Related AI Skills

Set up your own AI workspace now