Automated summary
Continuously monitors an entity (machine, station, work order, operator) and logs AI insights to the activity log upon detecting changes.
Strengths
- Automatic detection of status changes and new alarms
- Context-aware AI insight generation via MCP
- Configurable polling interval
Limitations
- Requires access to wecr8mcp MCP tools
- May produce noise if change threshold is too low
- Runs indefinitely until manually interrupted
For real-time supervision of machine or work order status with intelligent alerting.
For one-off checks or when MCP API call costs are a concern.
Security analysis
SafeThe skill only uses safe monitoring tools (wecr8mcp_observe, wecr8mcp_enrich) and does not perform any destructive, exfiltrating, or obfuscated actions. No high-risk tools are used.
No concerns found
How this analysis is madeExamples
/loop-skill machine abc123 30/loop-skill work_order 300loop-skill
Continuously monitor a machine or work-order for changes and surface AI insights to the activity log.
Usage
/loop-skill [entity_type] [entity_id] [interval_seconds]
entity_type— one of:machine,station,work_order,operatorentity_id— UUID to watch. Omit to watch all.interval_seconds— poll interval (default: 60)
What it does
- Calls
wecr8mcp_observeto read current state. - Compares against the previous snapshot to detect changes.
- If a meaningful change is detected (status change, new alarm, quality flag), calls
wecr8mcp_enrichto log an AI insight. - Reschedules itself at the requested interval.
Example
/loop-skill machine abc123 30
Watches machine abc123 every 30 seconds and logs anomaly/insight notes when status changes.
From the file to a first result
The download contains exactly the content displayed on this page. This copy may differ from the latest version in the source repository.
View the source and supporting filesThis download contains SKILL.md only. Any scripts, references, templates and dependencies are not included. Get the required files from the source, preserving their directory structure, before continuing.
1. Download the file
Download SKILL.mdFrom the root of a test project, save the file as .skill-downloads/loop-skill-mrx3y09h/SKILL.md, or use the command below. This folder is for inspecting the skill before installation.
Command for macOS/Linux or WSL: requires a POSIX shell and curl. On Windows without WSL, use the download button and create the folder manually.
mkdir -p '.skill-downloads/loop-skill-mrx3y09h' && curl --fail --show-error --location 'https://skills-guides.com/api/skills/loop-skill-mrx3y09h/download' --output '.skill-downloads/loop-skill-mrx3y09h/SKILL.md.part' && mv '.skill-downloads/loop-skill-mrx3y09h/SKILL.md.part' '.skill-downloads/loop-skill-mrx3y09h/SKILL.md'2. Check prerequisites
Read SKILL.md before using it. If it references scripts or external services, inspect them and prepare the required access in your test environment.
No recognized prerequisites section in this file. This does not mean it is self-contained: libraries, tools and access requirements may be mentioned elsewhere in the content or source repository.
The platforms on this page are catalog indications. The paths below follow tool documentation; they do not prove this skill has been run in those tools. No minimum tool version is confirmed for this listing.
3. Load the skill
This file does not provide a usable name/description header for this native procedure. It remains available to download and inspect; use the manual method below.
Manual method or another tool: attach SKILL.md to a conversation, or open it in an agent that can read files. Include any required supporting resources. No universal folder is recognized by every tool.
4. Try a first task
Use a short, synthetic input: an API endpoint, a small document or an interface brief. In a new conversation, attach the file or give the agent its path, then adapt this request:
Read .skill-downloads/loop-skill-mrx3y09h/SKILL.md and apply its instructions to this example: [describe a test input]. Identify any missing files, dependencies or access. Produce the result requested by the skill without inventing data or running unreviewed scripts.Expected result: output matching the skill instructions, or a precise list of missing prerequisites. A read confirmation alone does not validate a first use. If an external resource is unavailable, that path remains untested.
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