Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add skills/kinhluan/skills/scheduling-algorithmsnpx skills add kinhluan/skills --skill scheduling-algorithmsgit clone --depth 1 https://github.com/kinhluan/skillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/kinhluan/skills/scheduling-algorithms)<a href="https://agentmods.dev/skills/kinhluan/skills/scheduling-algorithms"><img src="https://agentmods.dev/badge/skills/kinhluan/skills/scheduling-algorithms.svg" alt="Measured on agentmods" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00043 | $0.05885 |
| Opus 5 | $0.00022 | $0.02942 |
| Sonnet 5 | $0.00009 | $0.01177 |
| Haiku 4.5 | $0.00004 | $0.00588 |
Grade A, and why
scheduling-algorithms scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 6d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 790 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Scheduling Algorithms
Comprehensive guide to scheduling algorithms spanning operating systems, parallel/distributed systems, cloud computing, real-time systems, and machine learning-based approaches.
"Scheduling is the art of allocating scarce resources to competing demands over time."
1. When to Use
- Designing OS process/thread schedulers
- Allocating tasks in HPC clusters or cloud environments
- Optimizing workflow execution (DAGs, task graphs)
- Research on scheduling optimization and comparison
- Real-time embedded systems with deadlines
- Container orchestration and resource management
2. Fundamental OS Scheduling Algorithms
First-Come First-Served (FCFS)
Simplest non-preemptive scheduler.
Process queue: P1(24), P2(3), P3(3)
Timeline: | P1(0-24) | P2(24-27) | P3(27-30) |
Waiting times: P1=0, P2=24, P3=27 → Avg = 17
Pros: Simple, no starvation
Cons: Convoy effect (short jobs wait behind long ones)
Complexity: O(1) per decision
Shortest Job First (SJF) / Shortest Remaining Time First (SRTF)
Optimal for minimizing average waiting time.
Preemptive (SRTF):
Arrival: P1(0,7), P2(2,4), P3(4,1), P4(5,4)
Timeline: | P1(0-2) | P2(2-4) | P3(4-5) | P2(5-7) | P4(7-11) | P1(11-16) |
Pros: Minimizes average waiting time
Cons: Requires prediction of burst time; starvation of long jobs
Prediction: Exponential averaging: τₙ₊₁ = α·tₙ + (1-α)·τₙ
Round Robin (RR)
Time-quantum based preemptive scheduling.
Quantum = 4, Processes: P1(10), P2(3), P3(5)
Timeline: | P1(0-4) | P2(4-7) | P3(7-11) | P1(11-15) | P3(15-18) | P1(18-20) |
Quantum selection:
- Too large → FCFS behavior
- Too small → excessive context switches (overhead > 80%)
- Rule of thumb: 80% of CPU bursts should be < quantum
Complexity: O(1)
Best for: Time-sharing systems
Priority Scheduling
Priority queue with aging to prevent starvation:
Effective priority = Base priority + (waiting_time / aging_factor)
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 6d ago First seen · 790 lines · 43 tokens per session scan A 17008c171c08
scheduling-algorithms is a skill published in the GitHub repository kinhluan/skills (4 stars, last pushed 9d ago), licensed MIT. It adds 43 tokens to every session and 5,885 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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