git-advanced
Skill30 starsChanged 13 months agoNo licenceView on GitHub
Advanced Git operations and workflows including interactive rebasing, conflict resolution, history manipulation, bisecting for bugs, cherry-picking, reflog recovery, and branch management strategies. Use for: (1) Interactive rebasing and commit cleanup, (2) Complex merge conflict resolution, (3) Git bisect for bug hunting, (4) History rewriting and cleanup, (5) Branch strategy implementation (Git Flow, trunk-based), (6) Recovering lost commits with reflog
- Deletes or force-pushes
- Commits and pushes
5 other projects use a version of this.
Adopted by
Most recently taken up by
- rcdelfin/agentkittheir own version, first seen Aug 28, 2026
- Kashyap-001/second-brain-templatetheir own version, first seen Jul 23, 2026
- bybren-llc/safe-agentic-workflowtheir own version, first seen Jul 20, 2026
- adyba/pi-safe-workflowtheir own version, first seen Jul 10, 2026
- AgentJDrew/claude-skill-kittheir own version, first seen Jul 6, 2026
Used with
Projects with it also use safe-workflow, spec-creation and 2 more.
Other files people use alongside this one.
Files found in the same public projects as a version of this one, more often than they turn up anywhere else. Each project counts once, large collections count for less, and this file's own repository is left out.
adybaSkillsafe-workflow
SAFe Agentic Workflow orchestrator. Teaches the full SAFe methodology adapted for AI agents: pattern discovery, exit states, quality gates, agent personas, and specs-driven development. Use when setting up a project with SAFe workflow, understanding the multi-agent methodology, or coordinating work across agent personas. Triggers: "SAFe workflow", "agent workflow", "safe harness", "specs-driven", "exit states", "quality gates", "multi-agent workflow".
Also in 3 projects that use this
- adybaSkill
spec-creation
Spec creation with pattern references, acceptance criteria, and demo scripts. Use when creating implementation specs, defining acceptance criteria, breaking down user stories, or translating business requirements to technical specs. Do NOT use for implementation work -- this is for planning and specification only.
Also in 3 projects that use this
LangChainSkilltesting-patterns
Unit testing and integration testing best practices
Also in 3 projects that use this
CloudflareSkillsecurity-audit
Security guidance and vulnerability review for codebases, APIs, services, CLI tools, libraries, and daemons. Use for security questions, focused reviews, vulnerability research, security audits, or pen tests. Run the complete workflow only for explicit codebase audit or pen-test requests, full/comprehensive/end-to-end reviews, or requested report artifacts.
Also in 3 projects that use this
Other versions5 projects use a version of this.
Word for word · 0
None found.
Edited · 0
None found.
Wrote their own version · 5
- bybren-llc/safe-agentic-workflow★ 405same name
- rcdelfin/agentkit★ 2same name
- adyba/pi-safe-workflow★ 0same name
- AgentJDrew/claude-skill-kit★ 0same name
- Kashyap-001/second-brain-template★ 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 repository15 other files it gives its agents.
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The file
Show its rules and text
We split this skill into the rules it gives an agent
20 rules. 0 are common, 18 are distinctive, and 2 are very specific to this project.
0
Common
Most of the 5 edited versions we read keep these.
18
Distinctive
This author's own choices. Worth a look.
2
Very specific
Tied to their project's names, files or tools. Probably skip.
No licence file, so all rights are reserved — read it at the source. We count its rules but don't quote them. Read them on GitHub.
“Common” is measured: kept by at least 6 in 10 of the 5 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
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Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
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