graph

graph is a skill for Claude Code from smallnest/goal-workflow. It costs 129 tokens per session (4,085 once invoked), scanned A, a copy of graph, MIT.

A task-planning tool that turns work items into a dependency graph, a map showing which tasks must come first, and runs independent tasks in parallel.

In plain words
What is it for?
Use it to split a PRD, specification, or issue list into task waves, assign independent tasks to separate agents, and combine their results between waves.
Why use it?
It helps teams handle work with dependencies while avoiding conflicts between tasks being developed at the same time.

Skill for Claude Code

Written for Claude Code: allowed-tools in frontmatter. Also seen: mentions subagents.

Needs its repository: it reads a path above its own folder, which exists only inside the repository. The line is git worktree add -b feat/node-{N}-{slug} ../.graph-worktrees/node-{N} main.

Part of the goal-workflow-skills plugin — 20 skills shipped together

Good fit Use it to split a PRD, specification, or issue list into task waves, assign independent tasks to separate agents, and combine their results between waves.

Compare 6 skills from other repositories ↓
Install

Getting it into your agent

It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.

Clone the repo
git clone --depth 1 https://github.com/smallnest/goal-workflow
agentmods
npx agentmods add skills/smallnest/goal-workflow/graph

Made for: Claude Code.

Or install goal-workflow-skills, the plugin that ships this one along with the rest of its 20 skills.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for graph

README.md
[![agentmods](https://agentmods.dev/badge/skills/smallnest/goal-workflow/graph/github.svg)](https://agentmods.dev/skills/smallnest/goal-workflow/graph)
Your own site
<a href="https://agentmods.dev/skills/smallnest/goal-workflow/graph"><img src="https://agentmods.dev/badge/skills/smallnest/goal-workflow/graph/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for graph

Your own site · 80×15
<a href="https://agentmods.dev/skills/smallnest/goal-workflow/graph"><img src="https://agentmods.dev/badge/skills/smallnest/goal-workflow/graph.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 129 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 4,085 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin 98% copy Near-identical to another mod 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 5.1 $0.00129 $0.04085
Opus 5.5 $0.00052 $0.01634
Sonnet 5.5 $0.00026 $0.00817
Haiku 4.5 $0.00013 $0.00409

Measured 1mo ago against content hash 787a3694c019, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

graph 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 1mo ago.

The scan reads SKILL.md. This mod also ships 1 executable file (scripts/render_graph_html.py), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

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.

Origin

This is a copy

98% identical to graph — 2 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

skills/graph/SKILL.md · 330 lines

How it starts

The opening of the file, as written. The whole thing — 330 lines — stays where its author put it; the contents beside it link to each section on GitHub.

graph — Task/PRD to Parallel Execution Graph

Turn a task (or PRD / SPEC / issue set) into a directed acyclic graph of work units, layer it into supersteps (waves), and implement each wave's independent nodes concurrently using subagents. Each node runs the full /goal → /review-it → /ship-it pipeline inside its own git worktree, so parallel nodes never clobber each other's working tree. Between waves, a fan-in barrier merges results and re-plans the next wave.

This is the parallel sibling of /loop-it. /loop-it is strictly sequential (one worktree, one issue at a time). /graph fans out every independent node in a wave at once.


Mental Model (borrowed from LangGraph / graph engineering)

Concept Here
Node One implementable unit of work (an issue / subtask)
Edge A dependency: B depends on A → edge A → B
Superstep / wave A set of nodes whose deps are all satisfied — run concurrently
Fan-out Dispatch one subagent per node in the current wave
Fan-in (barrier) Wait for all nodes in the wave before starting the next
State channel .graph_state — shared checkpoint, rewritten between waves (resume source)
Live tracker graph.html — Claude-style light-theme dashboard, re-rendered from .graph_state at every checkpoint
Dynamic re-plan After a wave, revise the graph if new work/deps emerged

Core principle: Independent nodes in the same wave have no shared state and no ordering dependency, so they can run in true parallel. Dependencies define the only ordering. Everything else runs at once.


Overview

Input (task / PRD / SPEC / issues)
        │
        ▼
1. Decompose into nodes  ─────────►  nodes = {id, title, deps, criteria, scope}
        │
        ▼
2. Build DAG + validate  ─────────►  detect cycles, orphan deps
        │
        ▼
3. Topological layering  ─────────►  waves = [[n1,n2,n3], [n4,n5], [n6]]
        │
        ▼
4. Render graph + confirm with user
        │
        ▼  (write .graph_state + graph.html — open graph.html to watch live)
┌──────────── per wave (superstep) ────────────┐
│                                               │
│  FAN-OUT: 1 subagent per node (parallel)      │
│    each subagent, in its own git worktree:    │
│      /goal (inline implement) → /review-it    │
│                              → /ship-it        │
│                                               │
│  FAN-IN barrier: wait for ALL nodes           │
│    integrate, update .graph_state             │
│    re-render graph.html                        │
│    re-plan next wave if graph changed         │
│                                               │
└───────────────────────────────────────────────┘
        │
        ▼
All waves done → final summary

Read the full file on GitHub · 330 lines

Files

What ships with it

1 file 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. 1mo ago First seen · 330 lines · 129 tokens per session scan A 787a3694c019

Subscribe to this mod's changes

graph is a skill published in the GitHub repository smallnest/goal-workflow (293 stars, last pushed 1mo ago), licensed MIT. It adds 129 tokens to every session and 4,085 once invoked, about $0.0005 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 98% identical to graph, differing in 2 lines, and is treated as a copy.

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