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 commands/gullitmiranda/.cursor/basic-usagegit clone --depth 1 https://github.com/gullitmiranda/.cursorWhat 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 | $0.00000 | $0.00423 |
| Opus 5 | $0.00000 | $0.00211 |
| Sonnet 5 | $0.00000 | $0.00085 |
| Haiku 4.5 | $0.00000 | $0.00042 |
Grade A, and why
basic-usage 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 yesterday.
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
Basic Usage Examples
This document provides practical examples of how to use the skill-driven workflows (git, pr, k8s, plan) in real development scenarios. Behavior is implemented by Agent Skills in .cursor/skills/.
🚀 Getting Started
Follow the Quick Start guide to set up .cursor, then test basic functionality:
# Check git status
/git-status
# Create a feature branch
/git-branch feature/example
📝 Git Workflow Examples
Feature Development
Scenario: Adding a new authentication feature
# 1. Create feature branch
/git-branch feature/auth-jwt
# 2. Make changes and stage them
git add src/auth/jwt.js
# 3. Commit with conventional format
/commit
# 4. Create pull request
/pr
Bug Fix Workflow
Scenario: Fixing a login bug
# 1. Create fix branch
/git-branch fix/login-bug
# 2. Make changes
git add src/auth/login.js
# 3. Commit
/commit
# 4. Create PR
/pr
🔧 Kubernetes Examples
Safe Resource Inspection
# Check pods
/k8s-check pods
# Validate manifests
/k8s-validate deployment.yaml
# Show differences
/k8s-diff deployment.yaml
📋 Planning Examples
Project Planning
# Create project plan
/plan "Implement user authentication system"
# Check workspace status
/workspace-status
🎯 PR Management
Complete PR Workflow
# Create PR
/pr
# Validate PR
/pr check
# Mark ready for review
/pr ready
💡 Tips and Best Practices
- Always use feature branches for new work
- Use conventional commit format
- Validate changes before committing
- Use safe commands for Kubernetes operations
- Plan your work before starting
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.
- yesterday First seen · 104 lines · 0 tokens per session scan A 8913c1bd8037
basic-usage is a command published in the GitHub repository gullitmiranda/.cursor (2 stars, last pushed 6mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 423 tokens. 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.
Other commands, from other repositories
checklist
Generate a custom checklist for the current feature based on user requirements.
clarify
Identify underspecified areas in the current feature spec by asking up to 5 highly targeted clarification questions and encoding answers back into the spec.
specify
Create or update the feature specification from a natural language feature description.
analyze
Perform a non-destructive cross-artifact consistency and quality analysis across spec.md, plan.md, and tasks.md after task generation.
converge
Assess the current codebase against the feature's spec, plan, and tasks, then append any remaining unbuilt work as new tasks to tasks.md so implement can complete it.
implement
Execute the implementation plan by processing and executing all tasks defined in tasks.md.