Skills

Fractal

Spawn and manage child nodes -- recursive autonomous agent loops.

Install

npx skills add plasma-ai/fractal --skill fractal -g -a claude-code -y
Repository
plasma-ai/fractal789
Category
AI and agents
Updated
5d ago
License
Apache-2.0
Context cost
Mediumabout 3,000 tokens
Runs scripts
No, instructions only

What it does

Spawn and manage child nodes -- recursive autonomous agent loops.

Fractal

A fractal is a tree of autonomous loops, each running in an isolated Git worktree. You are one node; spawn a child to own a subtask that is well-defined, separable, large enough for its own iteration cycle, and able to be run in parallel without conflicting with your work. Pay careful attention to your NODE.md instructions to guide you on how and when to spawn sub-nodes.

If $MAX_DEPTH, $MAX_CHILDREN, or $MAX_DESCENDANTS is 0, you are a leaf -- you cannot spawn, so this skill (spawning and managing children) does not apply; skip it and focus on executing your task directly. Otherwise, default to spawning. If a task has separable parts, decompose it into children rather than doing it yourself -- the fractal's power is multiplicative parallelism -- don't waste it by tackling tasks one at a time.

Don't spawn what you can easily and reliably finish yourself. However, when a child's task is itself complex, be a manager: give it resources and detailed instructions on how to decompose further. Deep trees of focused nodes outperform shallow trees of overloaded ones.

Run fractal node --help and fractal node <command> --help for the CLI.

Limits (check before spawning)

VarMeaning
$MAX_DEPTHMaximum nesting depth below this node. -1 unlimited, 0 leaf.
$MAX_CHILDRENMaximum direct children of this node. -1 unlimited, 0 leaf.
$MAX_DESCENDANTSMaximum total descendants in this node's subtree. -1 unlimited, 0 leaf.

-1 is how an unset cap displays; no setter accepts it. Leave a child uncapped by omitting the flag at init, or lift a cap with fractal node config set <key>=null --path=<child worktree>.

Read the whole SKILL.md on GitHub

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