slfg

slfg is a skill for Claude Code, Codex from James-Traina/compound-science. It costs 13 tokens per session (363 once invoked), scanned A, original, MIT.

An end-to-end workflow for autonomous research tasks, using multiple agents to work on independent parts at the same time. It moves from brainstorming and planning through implementation, review, and documentation.

In plain words
What is it for?
Use it to create brainstorm and plan documents, split implementation into parallel tasks, and run review and follow-up documentation after code changes are made.
Why use it?
It provides checkpoints and a fixed sequence for carrying a research or coding task from an idea to completed, reviewed changes.

Skill for Claude CodeCodex

Part of the compound-science plugin — 20 skills shipped together

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/james-traina/compound-science/slfg
Any agent
npx skills add James-Traina/compound-science --skill slfg
Clone the repo
git clone --depth 1 https://github.com/James-Traina/compound-science

Made for: Claude Code, Codex.

Or install compound-science, 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 slfg

README.md
[![agentmods](https://agentmods.dev/badge/skills/james-traina/compound-science/slfg.svg)](https://agentmods.dev/skills/james-traina/compound-science/slfg)
Your own site
<a href="https://agentmods.dev/skills/james-traina/compound-science/slfg"><img src="https://agentmods.dev/badge/skills/james-traina/compound-science/slfg.svg" alt="Measured on agentmods" height="20"></a>
Per session 13 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 363 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 5.1 $0.00013 $0.00363
Opus 5 $0.00006 $0.00181
Sonnet 5 $0.00003 $0.00073
Haiku 4.5 $0.00001 $0.00036

Measured 5d ago against content hash 615c96b0b527, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-05, 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 5d 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 · 45 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. /workflows:brainstorm $ARGUMENTS Gate: must produce a file in docs/brainstorms/ before proceeding.

  2. /workflows:plan Gate: must produce a file in docs/plans/ before proceeding.

  3. /workflows:workUse swarm mode: Break the plan into independent tasks and launch parallel subagents via Task tool to build them concurrently. Each subagent handles one task from the plan. See references/orchestration-patterns.md for parallel dispatch patterns. Gate: must produce at least one code change (committed or staged) before proceeding. If work fails with no changes, stop and report the failure.

Parallel Phase

After work completes, launch steps 4 and 5 as parallel swarm agents (both only need completed code to operate):

  1. /workflows:review — spawn as background Task agent
  2. /workflows:compound — spawn as background Task agent

Wait for both to complete before finishing.

Output

When all steps are done, output:

Research workflow complete.

Brainstorm: [brainstorm file path]
Plan: [plan file path]
Work: [summary of implementation]
Review: [summary of findings]
Documentation: [docs/solutions/ path if created]

Start with step 1 now.

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. 5d ago First seen · 45 lines · 13 tokens per session scan A 615c96b0b527

Subscribe to this mod's changes

slfg is a skill published in the GitHub repository James-Traina/compound-science (13 stars, last pushed 5mo ago), licensed MIT. It adds 13 tokens to every session and 363 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.

Related

Other skills, from other repositories

systematic-debugging

Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.

obra/superpowers · 21 tokens

local-ai-agents

Build local-first AI agents that run entirely on a developer workstation with Microsoft Foundry Local and Qwen function-calling models. Covers Small Language Models (SLMs), the OpenAI-compatible local endpoint, sandboxed local tools, local RAG with Chroma, local MCP servers, hybrid cloud/local routing, and the…

microsoft/ai-agents-for-beginners · 200 tokens

next-cache-components-adoption

Turn on Cache Components in a Next.js app and resolve the blocking routes it surfaces. Use when the user wants to enable, adopt, or migrate to Cache Components, flip the cacheComponents flag, work through a flood of blocking-prerender / instant validation errors, run the cache-components-instant-false codemod, or…

vercel/next.js · 95 tokens

next-cache-components-optimizer

Drive a Next.js route to instant navigation by setting up an agentic loop, under Cache Components / PPR, on initial load (hard navigation) and client-side navigation (soft navigation). Encode the goal as a failing @next/playwright instant() e2e and work it to green, one verified route at a time; the shipped test then…

vercel/next.js · 170 tokens

next-partial-prefetching-adoption

Turn on Partial Prefetching in a Next.js app and work through the insights it surfaces. Use when the user wants to enable or adopt Partial Prefetching, flip the partialPrefetching flag, opt routes in with export const prefetch = 'partial', audit Link prefetch={true} behavior, preserve existing prefetched UI with…

vercel/next.js · 103 tokens

chronicle

Analyze Copilot session history for standup reports, usage tips, session search, and session reindexing. Use when the user asks for a standup, daily summary, usage tips, workflow recommendations, wants to search or find past sessions by keyword/file/PR, wants to reindex their session store, or asks about deleting…

microsoft/vscode · 72 tokens