planning

A planning workflow that turns a validated predicate into an executable plan. A predicate here is a clearly stated claim or problem to investigate; the plan includes deliverables, dependencies, and approval points.

In plain words
What is it for?
Use it after a fractal run to break work into independent deliverables with steps, constraints, and acceptance criteria.
Why use it?
It makes a plan specific enough for separate agents to execute and test without needing missing context.

Command

Install

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.

agentmods
npx agentmods add commands/rmolines/fractal-loop/planning
Clone the repo
git clone --depth 1 https://github.com/rmolines/fractal-loop
Per session 34 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 4,982 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5 $0.00034 $0.04982
Opus 5 $0.00017 $0.02491
Sonnet 5 $0.00007 $0.00996
Haiku 4.5 $0.00003 $0.00498

Measured yesterday against content hash cd0ad59e9f41, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

planning 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.

commands/planning.md · 559 lines

How it starts

The opening of the file, as written. The whole thing — 559 lines — stays where its author put it; the contents beside it link to each section on GitHub.

/fractal:planning

Human gates

Every time this skill needs human input, use the AskUserQuestion tool instead of printing the question as text output.

Context header (REQUIRED on every question when state is available): Prefix the question string with:

📍 | 🎯 <active_predicate (max 80 chars)>

Variables come from the pre-loaded State section. If state is not yet loaded (e.g., early steps of /fractal:propose before tree detection), omit the header.

IMPORTANT: The header must be plain text. No markdown formatting (no **, ##, *, etc.) in the question string. Emojis are fine as visual anchors.

You are an execution architect. Your job is to transform a validated predicate into a plan that subagents can execute without questions — not documentation, but a program of execution.

Input: $ARGUMENTS


Core principle

The plan is not documentation. It's a program.

Each deliverable must be a falsifiable slice: the smallest unit of work that (a) delivers value, (b) can be independently tested, and (c) contains everything a subagent needs to execute it — context, constraints, steps, and acceptance criteria.

A Sonnet that receives only the deliverable's prompt must be able to complete it without asking anything, without session context, without reading other deliverables.


On entry: locate the predicate

$ARGUMENTS is the path to the active fractal node directory, passed by the fractal primitive.

REPO_ROOT=$(git rev-parse --show-toplevel 2>/dev/null)
NODE_DIR="${REPO_ROOT}/${ARGUMENTS}"
PREDICATE="${NODE_DIR}/predicate.md"

If $ARGUMENTS is empty: read .fractal/root.md → get active_node → use that. If predicate.md not found: stop with "No predicate found. Run /fractal:run first."

Read in parallel:

  1. predicate.md — the falsifiable condition. This IS the requirement.
  2. .claude/project.md — build, test, hot files, stack.

Load standards

After reading project.md, check for a standards file in the target repo:

Read the full file on GitHub · 559 lines

Changes

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.

  1. yesterday First seen · 559 lines · 34 tokens per session scan A cd0ad59e9f41

Subscribe to this mod's changes

planning is a command published in the GitHub repository rmolines/fractal-loop (13 stars, last pushed 5mo ago), licensed MIT. It adds 34 tokens to every session and 4,982 once invoked, about $0.0002 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 2026-08-31.