ql-plan

A planning skill that turns a product requirements document, or PRD, into quantum.json: a machine-readable list of small tasks with dependencies and execution details.

In plain words
What is it for?
Creating the execution plan after a design specification, recording the plan handoff, and tracking whether the source documents changed.
Why use it?
It replaces a broad feature description with a structured plan that an automated development loop can follow and skip safely when inputs have not changed.

Skill for Claude CodeCodex

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 skills/andyzengmath/quantum-loop/ql-plan
Any agent
npx skills add andyzengmath/quantum-loop --skill ql-plan
Clone the repo
git clone --depth 1 https://github.com/andyzengmath/quantum-loop

Made for: Claude Code, Codex.

Per session 85 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 9,807 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 1 finding. 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 $0.00085 $0.09807
Opus 5 $0.00043 $0.04903
Sonnet 5 $0.00017 $0.01961
Haiku 4.5 $0.00009 $0.00981

Measured 2d ago against content hash a3df0d89aa22, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

ql-plan scanned grade A with 1 finding 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 2d 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.

Makes network callslowCapability

Not a fault in itself. Listed so you know the mod talks to something, and to what.

> curl -sO https://raw.githubusercontent.com/andyzengmath/quantum-loop/main/templates/quantum-loop.sh && chmod +x quantum-loop.sh
skills/ql-plan/SKILL.md · 794 lines

How it starts

The opening of the file, as written. The whole thing — 794 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Quantum-Loop: Plan

You are converting a Product Requirements Document (PRD) into a machine-readable quantum.json file that will drive autonomous execution. Every decision you make here determines whether the execution loop succeeds or fails.

Phase 0: Phase-skip check (Phase 18 / P2.4)

Before reading the PRD, check whether a prior /ql-plan run already converted the same PRD + spec handoff into quantum.json:

PRD=$(ls -t tasks/prd-*.md 2>/dev/null | head -1)
SPEC_HANDOFF=".handoffs/spec.md"
ARGS=()
[[ -n "$PRD" ]]             && ARGS+=("$PRD")
[[ -f "$SPEC_HANDOFF" ]]    && ARGS+=("$SPEC_HANDOFF")

if bash lib/phase-skip.sh skip plan . "${ARGS[@]}"; then
  echo "[SKIP] plan is up-to-date — PRD + spec handoff unchanged."
  bash lib/handoff.sh read plan | jq '.'
  exit 0
fi

After writing quantum.json and .handoffs/plan.md, record the fingerprint:

PRD_H=$(bash lib/phase-skip.sh hash "$PRD")
SPEC_H=$(bash lib/phase-skip.sh hash "$SPEC_HANDOFF")
FP=$(jq -cn --arg pp "$PRD" --arg ph "$PRD_H" --arg sp "$SPEC_HANDOFF" --arg sh "$SPEC_H" \
  '{artifacts: [{path: $pp, sha256: $ph}, {path: $sp, sha256: $sh}]}')
bash lib/phase-skip.sh record plan "$FP" . >/dev/null

Prerequisite: read prior-stage handoffs (Phase 15 / P2.3)

Before reading the PRD, ingest every prior-stage handoff so decisions, rejected alternatives, and risks carry forward across context compaction:

bash lib/handoff.sh all | jq '.'
bash lib/handoff.sh read brainstorm | jq '.'
bash lib/handoff.sh read spec | jq '.'

Treat spec.decided as binding (these are the ACs you MUST plan for), spec.rejected as closed (don't re-introduce), spec.remaining as explicit gaps you should surface to the user before finalizing the DAG, and the union of brainstorm.risks ∪ spec.risks as mandatory inputs to every story's risk consideration.

At the end of /ql-plan, write .handoffs/plan.md:

bash lib/handoff.sh write plan "$(cat <<'JSON'
{
  "decided":   ["<each DAG + wave decision>", "<contract materialization picks>"],
  "rejected":  ["<each alternative story split / ordering considered>"],
  "risks":     ["<carried from upstream + any new planning risks>"],
  "files":     ["quantum.json"],
  "remaining": ["<any AC you could not resolve into a concrete story>"],
  "notes":     "<notes on parallelism, file-conflict sets, contract choices>"
}
JSON
)"

Read the full file on GitHub · 794 lines

Files

What ships with it

2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

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. 2d ago First seen · 794 lines · 85 tokens per session scan A a3df0d89aa22

Subscribe to this mod's changes

ql-plan is a skill published in the GitHub repository andyzengmath/quantum-loop (24 stars, last pushed 2mo ago), licensed MIT. It adds 85 tokens to every session and 9,807 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

Related

Other skills, from other repositories