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Operations

Skill yigityildiz0/universal-ai-skill-library/skills/common/operations

Route operational work to focused, evidence-based workflows for SOPs, capacity, change, risk, compliance evidence, runbooks, vendor review, stakeholder updates, and process improvement. Use when a task is about repeatable execution, operating cadence, handoffs, or operational decision support.From its SKILL.md

Install
npx -y skills add yigityildiz0/universal-ai-skill-library --skill operations

Assembled from the repository path, not quoted from the project. Check it against their README if it does not work.

2 things to look at

  • no licenseNo license file was found in the repository. Code published without one is not open source by default, so using it at work is a question for whoever answers licensing questions where you are.
  • 1 stars1 stars. Stars are a popularity signal and not a quality one, but at this level it is likely that nobody has read this closely except its author, and you would be relying on your own review.

SKILL.md

1.2 KB, 177 tokens by cl100k_base, as published. Nobody here has run it

Operations

Choose the narrowest workflow that matches the operational decision:

  • capacity-planning for demand, throughput, staffing, or service scenarios;
  • change-management for rollout, approvals, rollback, and verification;
  • compliance-evidence-tracking for controls and evidence, not legal certification;
  • process-documentation or process-optimization for repeatable work;
  • operational-risk-assessment for cause-event-impact analysis;
  • operations-runbook for controlled procedures and escalation;
  • vendor-review for tool or supplier choices;
  • stakeholder-update for evidence-backed status and asks.

Keep ownership, cadence, input, output, risk, and decision gates explicit. Prefer the smallest useful process over administrative overhead. No operational skill authorizes its own external, destructive, privileged, or production action.

What ships with it

Read from the repository

Just SKILL.md. No reference files, no scripts.

Gives 0 of the 12 instructions most operations skills give in 177 tokens

Counted across 483 of the 484 authors here whose files we hold, read 2026-08-07

  • Collect monitoring data throughout the simulationin 14 of 483, across 6 files
  • Set the random seed for reproducibilityin 14 of 483, across 6 files
  • Validate simulations against analytical solutionsin 12 of 483, across 4 files
  • Clarify goals, constraints, and inputsin 11 of 483, across 2 files
  • Implement contract tests for integration pointsin 11 of 483, across 2 files
  • Implement strangler fig infrastructure with API gatewayin 11 of 483, across 2 files
  • Audit modernized components for security vulnerabilitiesin 11 of 483, across 2 files
  • Avoid Python blocking calls in processesin 10 of 483, across 3 files
  • Use resource context managers for automatic cleanupin 9 of 483, across 2 files
  • Maintain consistent time unitsin 9 of 483, across 2 files
  • Validate outcomes against success criteriain 8 of 483, across 1 file
  • Analyze the legacy codebase for technical debtin 8 of 483, across 1 file

Said here and by no other author read

  • choose the narrowest matching workflow
  • keep ownership and cadence explicit
  • keep input and output explicit
  • keep risk and decision gates explicit
  • prefer the smallest useful process

Grouped from the skills themselves: near-identical wordings counted once, and counted by distinct author, so one author publishing three of these counts once. Length counted with cl100k_base; the agent that loads this file may tokenize it differently.

Keep looking

Skills are one crate of 325,949. Ordering is by how many stacks a row turns up in, so the top of any crate is what has actually been picked rather than what has the most stars.