graph-new

A command that turns a plain-language requirement into a registered execution graph. An execution graph is a set of connected steps, decisions, commands, and possible loops.

In plain words
What is it for?
It is for planning reproducible workflows such as builds and tests, adding approval checkpoints before irreversible actions, and defining branches or retries.
Why use it?
It helps make complex work explicit, including which steps need tests, human decisions, approvals, or failure handling.

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/sciencemj/graph-engineering/graph-new
Clone the repo
git clone --depth 1 https://github.com/sciencemj/graph-engineering
Per session 19 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 434 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 $0.00019 $0.00434
Opus 5 $0.00010 $0.00217
Sonnet 5 $0.00004 $0.00087
Haiku 4.5 $0.00002 $0.00043

Measured yesterday against content hash 2c686a76396a, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

graph-new 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/graph-new.md · 33 lines

What it actually says

Read the "Building a graph" and "Four ways to build a graph that blows up" sections of the graph-engineering skill first.

Requirement: $ARGUMENTS

Do this:

  1. Decompose the requirement into nodes. Hard rules while decomposing:
    • Reproducible work — tests, builds, lints, formatters, migrations — must be a command node. Do not wrap it in an ai_task.
    • Every point that needs a human decision (spec choice, naming policy, deploy approval) is a user_input or a checkpoint.
    • Always put a checkpoint in front of anything irreversible (deploy, migration, force push).
    • A node whose failure should still flow downstream needs an explicit on_failure: "continue". With the default halt, a failing test kills the run before it can reach the node that fixes it.
    • Express a backwards path as a kind: "loop" edge. A cycle made of forward edges is rejected at save.
  2. Check yourself before registering:
    • Does the path that decides success or failure have at least one command or condition? Branching on an ai_task's report about itself produces well-organized nonsense.
    • Did you create branches that all merge back into the same node?
    • If there is a loop, does something inside it change state, and can the exit condition ever become true?
  3. Register it with graph_create. If validation rejects it, fix it and register again.
  4. Summarize the nodes and edges in a table, and point out where a human will be asked to step in.

Do not run it. End with "review the graph, edit it if needed, lock it, then run /graph-engineering:graph-run <name>".

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 · 33 lines · 19 tokens per session scan A 2c686a76396a

Subscribe to this mod's changes

graph-new is a command published in the GitHub repository sciencemj/graph-engineering (0 stars, last pushed 1mo ago), licensed MIT. It adds 19 tokens to every session and 434 once invoked, about $0.0001 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.