Menu

Individual skill

online-resource-scheduling

0upvotes

Design deterministic online scheduling policies from current observations. Use when assigning arriving work to limited resources without seeing future requests.

tasks-extra/gpu-cluster-online-scheduling/environment/skills/online-resource-scheduling/SKILL.md

Read pinned source

Source commit f860ecf02ef53412a030f8661c83d644b739ff01

What was checked

Matches the observed repository HEAD
Yes
Scanner rules are current
Yes
Repository scan complete
No
Skill scan complete
Yes
Observed behavior
Instructions only
Last checked
Nov 9, 2026

These are observations at the recorded commit, not a guarantee of safety. Review the source before running it.

Install this skill

Choose an agent in your Stack or copy a command below. Commands fetch the pinned commit and copy only this skill directory. Existing destinations are refused. Copying a command does not install anything.

An install command is unavailable: current rules, complete repository and skill scans, an eligible behavior level and a permitted license are required.

Repository context

Repository stars (not skill ratings)
1,915
Repository last updated
Nov 4, 2026
License
Apache-2.0

Observed agent integration: No specific integration evidence. Standard SKILL.md installation does not imply verified compatibility.

Files and excerpt

File metadata and permitted, redacted excerpts come from the recorded scan. Source links are pinned to that commit.

Browse files
Read excerpt

# Online Resource Scheduling

Use this skill to build online schedulers that make deterministic decisions from the current observation only.

## Core Workflow

Convert each observation into a temporary state, rank pending work, score feasible actions by weighted marginal cost, update the temporary state immediately, then replay the final action list before returning it.

```text
actions = []
temporary_state = copy_resources(observation)

for item in ranked_pending_items(observation):
  candidates = enumerate_feasible_actions(item, temporary_state)
Back to top