zellij
Skill1 starsChanged 2 months agoNo licenceView on GitHub
Zellij 終端多工管理操作指南。Use for: (1) 在 zellij pane 中啟動/停止服務, (2) 讀取其他 pane 的畫面輸出, (3) 多 pane 佈局管理, (4) 從 claude pane 遠端控制其他 pane。Use when: 需要在多個終端中同時運行前後端服務、需要讀取其他 pane 的日誌輸出、需要管理 zellij session 和 pane。
2 other projects use a version of this.
Adopted by
Most recently taken up by
- Voronenko/ai-filestheir own version, first seen Nov 1, 2026
- ryanmaclean/skillstheir own version, first seen Sep 23, 2026
Other versions2 projects use a version of this.
Word for word · 0
None found.
Edited · 0
None found.
Wrote their own version · 2
- ryanmaclean/skills★ 1same name
- Voronenko/ai-files★ 0same name
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
In this repository75 other files it gives its agents.
- 5w1h-decisionSkill
- agent-teamSkill
- asd-ste100Skill
- blank-slate-reviewSkill
- branch-worktree-guardianSkill
- broken-link-checkSkill
- bulk-evaluateSkill
- business-analysisSkill
- business-researchSkill
- case-first-module-workflowSkill
- cc-release-impact-reviewSkill
- chrome-extension-mcp-debugSkill
- cognitive-load-assessmentSkill
- component-contract-designSkill
- compositional-writingSkill
- content-extension-evaluationSkill
- continuous-learningSkill
- dart-comment-traceabilitySkill
- dart-domain-modelingSkill
- dart-provider-architectureSkill
- dart-style-guardianSkill
- dart-test-async-guardianSkill
- data-extractionSkill
- decision-tree-helperSkill
- design-decision-frameworkSkill
- dispatch-strategy-reviewSkill
- doc-flowSkill
- docSkill
- error-patternSkill
- event-flow-arbitration-designSkill
- evidence-driven-bugfixSkill
- foundation-designSkill
- framework-issueSkill
- frontend-with-playwrightSkill
- golden-path-validationSkill
- impeccableSkill
- knowledge-cardsSkill
- linux-install-debugSkill
- lsp-firstSkill
- mermaid-asciiSkill
- methodology-writingSkill
- migration-playbook-methodologySkill
- multi-round-reviewSkill
- multi-session-orchestrationSkill
- neurodivergent-outputSkill
- observability-stackSkill
- parallel-evaluationSkill
- pre-fix-evalSkill
- project-analysisSkill
- project-initSkill
- requirement-protocolSkill
- saas-tech-selectionSkill
- scope-confirmationSkill
- search-tools-guideSkill
- skill-design-guideSkill
- skill-syncSkill
- specSkill
- startup-checkSkill
- strategic-compactSkill
- system-designSkill
- The first 60 shown.
The file
Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
No reviews yet
People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.
- It worked
- Partly
- It didn't
Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.
Your trail
Files you open will collect here, so you can find them again.
Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.
Now do this for your own.
Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.