Uplo Operations

AI-powered operations knowledge management. Search process documentation, capacity plans, resource allocation data, and KPI dashboards with structured extraction.

Operations is the connective tissue of any organization — the processes, playbooks, capacity models, and performance metrics that keep everything running. This skill connects your AI assistant to UPLO's structured extraction of operational knowledge: SOPs, runbooks, capacity plans, incident postmortems, vendor SLAs, and the KPI data that tells you whether things are actually working.

Session Start

Load your ops context to understand your role, team scope, and current operational priorities:

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use_mcp_tool: get_identity_context

Then pull the latest on anything that might need immediate attention:

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use_mcp_tool: search_knowledge query="active incidents open action items SLA breaches capacity warnings"
use_mcp_tool: get_directives

Directives for operations teams typically cover efficiency targets, cost reduction mandates, and service level commitments — knowing these frames every decision you make.

When to Use

• A process just broke and you need the runbook — fast. What are the exact steps for failover?
• Calculating whether you have enough capacity (people, systems, physical space) for a projected demand increase next quarter
• Pulling the vendor SLA terms for a service that's been underperforming so you can initiate a formal review
• Building a business case for process automation by finding where manual steps create the most bottlenecks
• Preparing for an operational review meeting with executive leadership — need KPI trends, not just snapshots
• Investigating why cycle time increased on a key process and what changed in the last 60 days
• Onboarding a new operations manager who needs to understand the full process landscape

Example Workflows

Incident Response and Postmortem

Something went wrong and you need to contain it, then learn from it.

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use_mcp_tool: search_knowledge query="runbook incident response procedure for payment processing failures"
use_mcp_tool: search_knowledge query="previous incidents payment processing root cause analysis postmortem"
use_mcp_tool: search_with_context query="payment processing system dependencies upstream downstream SLA obligations"

The first search gets you the immediate playbook. The second surfaces prior incidents so you can check whether this is a recurring pattern. The context search maps system dependencies so you understand blast radius.

Quarterly Capacity Planning

You need to model whether current resources can handle projected Q3 volume.

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use_mcp_tool: search_knowledge query="capacity utilization rates by team department Q1 Q2 actual vs planned"
use_mcp_tool: search_knowledge query="demand forecast projections Q3 volume transaction throughput"
use_mcp_tool: search_knowledge query="hiring plan headcount approved positions open requisitions operations"
use_mcp_tool: export_org_context

The org context export gives you the current organizational structure overlaid with capacity data, making it clear where you have headroom and where you're already running hot.

Key Tools for Operations

search_knowledge — Your primary tool for finding SOPs, runbooks, KPI data, and process documentation. Operations data is often spread across wikis, shared drives, and ticketing systems — UPLO consolidates it into searchable structured records. Example: "order fulfillment process cycle time SLA target vs actual last 6 months"

search_with_context — Operations is all about dependencies. A process change in one area cascades through others. This tool follows those connections. Example: "upstream dependencies for the monthly close process including data feeds handoffs and approval gates"

export_org_context — Generates a snapshot of your operational structure: teams, systems, processes, and their interconnections. Use it to brief new team members or to give leadership a helicopter view of operational health.

flag_outdated — Stale runbooks are dangerous. If you encounter a procedure that references a decommissioned system, an old vendor, or a changed approval chain, flag it immediately. Example: flag a disaster recovery plan that still references the on-prem data center you migrated off of 18 months ago.

propose_update — After a process improvement, push the updated procedure back into the knowledge base. Don't let the documentation drift from reality. Example: update the customer onboarding SOP to reflect the new automated verification step.

Tips

• Operations documents tend to use internal jargon and acronyms heavily. Search using both the acronym and the full name: "MTTR mean time to repair" or "NPS net promoter score customer operations" — this catches documents regardless of which form they used.
• When you find conflicting SOPs (two different procedures for the same process), don't just pick one. Use flag_outdated on the stale version AND report_knowledge_gap to note the conflict so the process owner can reconcile them.
• Time-series KPI data is most useful when you search with specific date ranges rather than asking for "the latest" — this lets you build trend lines and spot degradation patterns.
• After any significant operational change (new vendor, process redesign, system migration), use log_conversation to document the rationale and expected outcomes. This creates an audit trail that's invaluable when someone later asks "why did we change this?"