Garbage Collection

Expert skill for garbage collector design and implementation including various collection algorithms

509 stars

Best use case

Garbage Collection is best used when you need a repeatable AI agent workflow instead of a one-off prompt.

Expert skill for garbage collector design and implementation including various collection algorithms

Teams using Garbage Collection should expect a more consistent output, faster repeated execution, less prompt rewriting.

When to use this skill

  • You want a reusable workflow that can be run more than once with consistent structure.

When not to use this skill

  • You only need a quick one-off answer and do not need a reusable workflow.
  • You cannot install or maintain the underlying files, dependencies, or repository context.

Installation

Claude Code / Cursor / Codex

$curl -o ~/.claude/skills/garbage-collection/SKILL.md --create-dirs "https://raw.githubusercontent.com/a5c-ai/babysitter/main/library/specializations/programming-languages/skills/garbage-collection/SKILL.md"

Manual Installation

  1. Download SKILL.md from GitHub
  2. Place it in .claude/skills/garbage-collection/SKILL.md inside your project
  3. Restart your AI agent — it will auto-discover the skill

How Garbage Collection Compares

Feature / AgentGarbage CollectionStandard Approach
Platform SupportNot specifiedLimited / Varies
Context Awareness High Baseline
Installation ComplexityUnknownN/A

Frequently Asked Questions

What does this skill do?

Expert skill for garbage collector design and implementation including various collection algorithms

Where can I find the source code?

You can find the source code on GitHub using the link provided at the top of the page.

SKILL.md Source

# Garbage Collection Skill

## Overview

Expert skill for garbage collector design and implementation including various collection algorithms.

## Capabilities

- Implement mark-sweep collection
- Implement copying/semi-space collectors
- Implement generational collection with write barriers
- Implement concurrent/incremental marking (tri-color)
- Design object header layouts and type info
- Implement precise vs conservative root scanning
- Design card table and remembered set implementations
- Implement finalizers and weak references

## Target Processes

- garbage-collector-implementation.js
- memory-allocator-design.js
- interpreter-implementation.js
- bytecode-vm-implementation.js

## Dependencies

GC Handbook literature (Jones, Hosking, Moss)

## Usage Guidelines

1. **Algorithm Selection**: Start with simple mark-sweep, evolve to generational as needed
2. **Write Barriers**: Design write barriers early if considering generational/concurrent GC
3. **Root Scanning**: Implement precise root scanning for safety
4. **Pause Times**: Measure pause times and optimize for application requirements
5. **Testing**: Build GC stress tests and allocation-heavy benchmarks

## Output Schema

```json
{
  "type": "object",
  "properties": {
    "algorithm": {
      "type": "string",
      "enum": ["mark-sweep", "copying", "mark-compact", "generational", "concurrent"]
    },
    "writeBarrier": {
      "type": "string",
      "enum": ["none", "card-table", "remembered-set", "snapshot-at-beginning", "incremental-update"]
    },
    "rootScanning": {
      "type": "string",
      "enum": ["conservative", "precise"]
    },
    "generatedFiles": {
      "type": "array",
      "items": { "type": "string" }
    }
  }
}
```

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