slfg

slfg is a skill for Claude Code, Codex from marcusrbrown/systematic. It costs 13 tokens per session (463 once invoked), scanned A, original, MIT.

An autonomous software-development workflow that plans a task, optionally deepens the plan for higher-risk work, implements it with multiple agents, and then reviews the result. Swarm mode means several agents can work on separate parts in parallel.

In plain words
What is it for?
Use it for end-to-end feature or maintenance work that needs planning, implementation, review, and final checks. It is intended to continue through the workflow without stopping between stages.
Why use it?
It structures a large coding task from planning through verification so implementation and review are not skipped. Parallel work can divide independent engineering tasks among agents.

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/marcusrbrown/systematic/slfg
Any agent
npx skills add marcusrbrown/systematic --skill slfg
Clone the repo
git clone --depth 1 https://github.com/marcusrbrown/systematic

Made for: Claude Code, Codex.

Per session 13 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 463 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 $0.00013 $0.00463
Opus 5 $0.00006 $0.00231
Sonnet 5 $0.00003 $0.00093
Haiku 4.5 $0.00001 $0.00046

Measured 3d ago against content hash 3c799a746cf2, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

slfg 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 3d 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.

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.

skills/slfg/SKILL.md · 40 lines

What it actually says

Swarm-enabled LFG. Run these steps in order, parallelizing where indicated. Do not stop between steps — complete every step through to the end.

Sequential Phase

  1. Optional: If the ralph-loop skill is available, run /ralph-loop:ralph-loop "finish all slash commands" --completion-promise "DONE". If not available or it fails, skip and continue to step 2 immediately.
  2. /ce:plan $ARGUMENTS
  3. Conditionally run /systematic:deepen-plan
    • Run the deepen-plan workflow only if the plan is Standard or Deep, touches a high-risk area (auth, security, payments, migrations, external APIs, significant rollout concerns), or still has obvious confidence gaps in decisions, sequencing, system-wide impact, risks, or verification
    • If you run the deepen-plan workflow, confirm the plan was deepened or explicitly judged sufficiently grounded before moving on
    • If you skip it, note why and continue to step 4
  4. /ce:workUse swarm mode: Make a Task list and launch an army of agent swarm subagents to build the plan

Parallel Phase

After work completes, launch steps 5 and 6 as parallel swarm agents (both only need code to be written):

  1. /ce:review mode:report-only — spawn as background Task agent
  2. /systematic:test-browser — spawn as background Task agent

Wait for both to complete before continuing.

Autofix Phase

  1. /ce:review mode:autofix — run sequentially after the parallel phase so it can safely mutate the checkout, apply safe_auto fixes, and emit residual todos for step 8

Finalize Phase

  1. /systematic:todos (resolve) — resolve findings, compound on learnings, clean up completed todos
  2. Output <promise>DONE</promise> when work is complete

Start with step 1 now.

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. 3d ago First seen · 40 lines · 13 tokens per session scan A 3c799a746cf2

Subscribe to this mod's changes

slfg is a skill published in the GitHub repository marcusrbrown/systematic (24 stars, last pushed today), licensed MIT. It adds 13 tokens to every session and 463 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 2026-08-30.