Uplo Manufacturing

v1.0.0

AI-powered manufacturing knowledge management. Search work orders, quality inspections, production schedules, and equipment maintenance records with structur...

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Install

OpenClaw Prompt Flow

Install with OpenClaw

Best for remote or guided setup. Copy the exact prompt, then paste it into OpenClaw for roojenkins/uplo-manufacturing.

Previewing Install & Setup.
Prompt PreviewInstall & Setup
Install the skill "Uplo Manufacturing" (roojenkins/uplo-manufacturing) from ClawHub.
Skill page: https://clawhub.ai/roojenkins/uplo-manufacturing
Keep the work scoped to this skill only.
After install, inspect the skill metadata and help me finish setup.
Use only the metadata you can verify from ClawHub; do not invent missing requirements.
Ask before making any broader environment changes.

Command Line

CLI Commands

Use the direct CLI path if you want to install manually and keep every step visible.

OpenClaw CLI

Bare skill slug

openclaw skills install uplo-manufacturing

ClawHub CLI

Package manager switcher

npx clawhub@latest install uplo-manufacturing
Security Scan
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Purpose & Capability
Name, README, SKILL.md and skill.json consistently describe a connector to an UPLO manufacturing knowledge service. The declared capabilities (search_knowledge, search_with_context, export_org_context, etc.) match the stated purpose of querying work orders, inspections, PM logs and SOPs.
Instruction Scope
Runtime instructions only call MCP tools like use_mcp_tool: search_knowledge / search_with_context / export_org_context and recommend pulling identity/context. These actions are within scope for a knowledge-management connector. No instructions to read local OS files or unrelated credentials are present.
Install Mechanism
There is no top-level install spec, but skill.json contains an MCP command that runs `npx -y @agentdocs1/mcp-server --http`. That implies npm downloads and execution at runtime (moderate risk if the package or publisher is untrusted). This is expected for a connector but worth validating the npm package and publisher.
Credentials
skill.json requires an UPLO instance URL (agentdocs_url) and an API key (api_key). Those are proportionate for accessing corporate manufacturing data, but they are sensitive credentials that grant access to potentially large amounts of PII/IP/trade-secret data (especially via export_org_context). Also note a mild inconsistency: registry metadata reported 'no required env vars' while skill.json declares required config fields.
Persistence & Privilege
always is false and the skill does not request system-wide or persistent privileges. It does include an identity_patch that biases the agent to query UPLO first — this modifies assistant behavior but is consistent with the skill's purpose.
Assessment
This connector will need your UPLO instance URL and an API key to access manufacturing documents — that is expected, but those credentials are sensitive. Before installing: 1) Verify you trust the UPLO instance domain you will configure (do not point to unknown or personal servers). 2) Check the npm package @agentdocs1/mcp-server (publisher reputation, version history) because the MCP command runs via npx and will fetch/execute code. 3) Use a least-privilege API key or scoped token (limit export/get rights if possible) and monitor/rotate the key. 4) Be cautious about the export_org_context capability — it can return large, sensitive snapshots; restrict who can invoke this skill. 5) Note the metadata inconsistency about required env/config fields; confirm the platform will prompt you for agentdocs_url and api_key before enabling the skill. If you want higher assurance, ask the publisher for a signed release, an alternative vetted install mechanism, or for a review of the @agentdocs1/mcp-server npm package source.

Like a lobster shell, security has layers — review code before you run it.

latestvk970r5sxnv94a3wja59xgtmn2h839g91
166downloads
0stars
1versions
Updated 1mo ago
v1.0.0
MIT-0

UPLO Manufacturing

Connects your AI assistant to the structured knowledge layer built from your plant floor documentation — work orders, inspection reports, preventive maintenance schedules, CAPA records, production batch logs, and equipment manuals. When a machine goes down at 2am or a customer reports a defect, you need answers from your own data, not a web search.

Session Start

Pull your manufacturing context first. This loads your role (maintenance engineer, quality manager, production supervisor), active production priorities, and any open quality holds or equipment issues.

use_mcp_tool: get_identity_context
use_mcp_tool: search_knowledge query="open quality holds production line stoppages equipment downtime alerts"

Check directives if you need to understand current throughput targets or quality improvement initiatives:

use_mcp_tool: get_directives

When to Use

  • Investigating a non-conformance: what were the process parameters for batch #4471 on Line 3?
  • Finding the torque specification and calibration schedule for the CNC mill in Cell B
  • Pulling the FMEA (Failure Mode and Effects Analysis) for the new product introduction
  • Checking if a specific raw material lot passed incoming inspection before it hit the floor
  • Reviewing OEE trends for a production line to justify a capital expenditure request
  • Locating the lockout/tagout procedure for the hydraulic press before a maintenance window
  • Determining which shifts had the highest scrap rate last month and what corrective actions were taken

Example Workflows

Root Cause Analysis for Customer Complaint

A customer received parts with dimensional non-conformances. You need to trace back through your process.

use_mcp_tool: search_knowledge query="part number 7842-A dimensional inspection results CMM data last 90 days"
use_mcp_tool: search_with_context query="work order production batch part 7842-A process parameters tool wear records"
use_mcp_tool: search_knowledge query="CAPA corrective actions dimensional tolerance issues machining"

The structured extraction links inspection data back to specific work orders, machine settings, and operator certifications — giving you a complete traceability chain for your 8D report.

Preventive Maintenance Planning

You're building next quarter's PM schedule and need to consolidate equipment data.

use_mcp_tool: search_knowledge query="preventive maintenance schedules all production equipment Q2 upcoming"
use_mcp_tool: search_knowledge query="equipment breakdown history unplanned downtime root causes 2025"
use_mcp_tool: export_org_context

Cross-reference PM intervals against actual failure data to shift from calendar-based to condition-based maintenance where the data supports it.

Key Tools for Manufacturing

search_knowledge — Query across work orders, inspection records, PM logs, and SOPs simultaneously. The structured extraction means you get typed fields (part numbers, batch IDs, measurement values) not just raw text. Example: "SPC control chart data injection mold press 12 cavity pressure"

search_with_context — Follows the relationships between documents. A work order connects to the BOM, which connects to incoming material certs, which connect to supplier audits. Example: "material traceability lot number RM-2025-0892 from receiving through finished goods"

report_knowledge_gap — Found a machine with no documented setup procedure? A process with no control plan? Flag it. This feeds back into your quality system and ensures gaps get closed. Example: report that the new laser welder has no documented process validation (IQ/OQ/PQ).

propose_update — When an SOP is wrong or a spec has changed, propose the correction directly. It enters the review queue for the document owner. Example: update the anodizing bath concentration range after a process optimization study.

flag_outdated — Critical for manufacturing where revision control is everything. Mark superseded drawings, expired calibration certs, or obsolete work instructions before someone on the floor uses the wrong version.

Tips

  • Search by part number, work order number, or equipment asset ID for the most precise results — the extraction engine indexes these as structured fields, not just text tokens.
  • Manufacturing data is deeply interconnected. If a simple search_knowledge doesn't give you the full picture, switch to search_with_context to traverse the relationships (part -> BOM -> supplier -> cert -> inspection).
  • Always check document revision levels in results. If you spot an outdated revision, flag it immediately — in manufacturing, the wrong revision can mean scrapped parts or a safety incident.
  • When logging conversations about quality issues, include the NCR or CAPA number — it makes the audit trail searchable when regulators or customers ask about corrective actions taken.

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