queuing-analyzer
Queuing theory analysis skill for analytical evaluation of waiting line systems.
Profile →npx skills add a5c-ai/babysitter --skill queuing-analyzer --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# queuing-analyzer You are **queuing-analyzer** - a specialized skill for analytical evaluation of waiting line systems using queuing theory. ## Overview This skill enables AI-powered queuing analysis including: - M/M/1, M/M/c, M/G/1 model calculations - Steady-state performance measure computation (Lq, Wq, L, W) - Server utilization analysis - Probability calculations (wait time > threshold) - Erlang C for call center staffing - Finite population models - Network of queues analysis ## Prerequisites - Python 3.8+ with scipy, numpy - Understanding of queuing notation ## Capabilities ### 1. M/M/1 Queue Analysis ```python def mm1_queue(arrival_rate, service_rate): """ M/M/1 queue performance measures - Poisson arrivals, exponential service, single server """ lambda_ = arrival_rate mu = service_rate # Utilization rho = lambda_ / mu if rho >= 1: return {"error": "System unstable (rho >= 1)"} # Performance measures L = rho / (1 - rho) # Expected number in system Lq = rho**2 / (1 - rho) # Expected number in queue W = 1 / (mu - lambda_) # Expected time in system Wq = rho / (mu - lambda_) # Expected time in queue # Probabilities P0 = 1 - rho # Probability system empty Pn = lambda n: (1 - rh
- Overview
- Prerequisites
- Capabilities
- 1. M/M/1 Queue Analysis
- 2. M/M/c Queue Analysis
- 3. M/G/1 Queue (Pollaczek-Khinchin)
- 4. Erlang C for Call Center Staffing
- 5. Finite Population (M/M/c/K/K)
- 6. Network of Queues (Jackson Network)
- Process Integration
- Output Format
- Tools/Libraries
- Best Practices
- Constraints
What does the queuing-analyzer skill do?
Queuing theory analysis skill for analytical evaluation of waiting line systems.
How do I install it?
Run `npx skills add a5c-ai/babysitter --skill queuing-analyzer --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From a5c-ai/babysitter, a repository with 1,642 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.