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/j-pster/psters_ai_workflow/git-worktreenpx skills add J-Pster/Psters_AI_Workflow --skill git-worktreegit clone --depth 1 https://github.com/J-Pster/Psters_AI_WorkflowWrote 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/j-pster/psters_ai_workflow/git-worktree)<a href="https://agentmods.dev/skills/j-pster/psters_ai_workflow/git-worktree"><img src="https://agentmods.dev/badge/skills/j-pster/psters_ai_workflow/git-worktree.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 | $0.00028 | $0.00269 |
| Opus 5 | $0.00014 | $0.00134 |
| Sonnet 5 | $0.00006 | $0.00054 |
| Haiku 4.5 | $0.00003 | $0.00027 |
Grade A, and why
git-worktree 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 5d 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.
What it actually says
Git Worktree
Create and use Git worktrees so multiple branches can be worked on in separate directories.
Commands (run from repo root):
- List:
git worktree list - Add:
git worktree add <path> <branch>(e.g.git worktree add ../project-feat ../feature-branch) - Remove:
git worktree remove <path>(after switching away and committing or discarding)
Use case: Run a separate agent or human in another branch in a different folder without touching the current branch. Each worktree has its own working directory but shares the same .git history.
Note: Repo root is the workspace root; backend/frontend/lambdas may be sibling folders or monorepo structure. Create worktrees from the repo that contains the branch you need.
Branch/worktree closure discipline
When implementation in a worktree is complete, use finishing-a-development-branch to close with a consistent decision flow:
- Merge locally
- Push and create PR
- Keep as-is
- Discard
This avoids dangling worktrees and branch confusion.
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.
- 5d ago First seen · 29 lines · 28 tokens per session scan A acbff2fa8308
git-worktree is a skill published in the GitHub repository J-Pster/Psters_AI_Workflow (290 stars, last pushed 5mo ago), licensed MIT. It adds 28 tokens to every session and 269 once invoked, about $0.0001 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 2026-08-30.
Other skills, from other repositories
html-ppt-hermes-cyber-terminal
OpenDesign + BYOK: choosing and wiring your own model, hands-on — cost, quality, and the routing decision. Built as a decision-grade AI literacy deck for engineers, IT, applied-AI teams.
development
开发语言能力索引。Python、Go、Rust、TypeScript、Java、C++、Shell。当用户提到编程、开发、代码、语言时路由到此。.
post-build-flow
Handles workflow verification and setup after build-workflow succeeds, or when the message contains workflow-verification-follow-up or workflow-setup-required. Load after direct builds, when verificationReadiness requires action, or on orchestrator verify/setup follow-up turns.
n8n:human-like-code-review
Reviews a GitHub pull request like a thoughtful human reviewer and writes the feedback to a markdown file. Prioritizes context, architecture fit, solution complexity, bugs, security edge cases, and missing tests. Use when given a PR URL to review, or when the user says /human-like-code-review.
n8n:create-pr
Creates GitHub pull requests with properly formatted titles that pass the check-pr-title CI validation. Use when creating PRs, submitting changes for review, or when the user says /pr or asks to create a pull request.
n8n:reproduce-bug
Reproduce a bug from a Linear ticket with a failing test. Expects the full ticket context (title, description, comments) to be provided as input.