slfg

slfg is a skill for Claude Code from gvkhosla/compound-engineering-pi. It costs 13 tokens per session (435 once invoked), scanned A, original, MIT.

An autonomous software-engineering workflow that plans work, optionally deepens the plan for high-risk changes, and uses multiple agents to implement and review it in parallel.

In plain words
What is it for?
Use it for larger engineering tasks that benefit from a structured plan, swarm-based parallel coding, risk review, and a final implementation review.
Why use it?
It coordinates the full path from planning through implementation and review without requiring the developer to manually start each stage.

Skill for Claude Code

Written for Claude Code: disable-model-invocation in frontmatter. Also seen: mentions subagents.

Part of the compound-engineering plugin — 41 skills, 1 MCP server shipped together

Good fit Use it for larger engineering tasks that benefit from a structured plan, swarm-based parallel coding, risk review, and a final implementation review.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/gvkhosla/compound-engineering-pi/slfg
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.

Any agent
npx skills add gvkhosla/compound-engineering-pi --skill slfg
Clone the repo
git clone --depth 1 https://github.com/gvkhosla/compound-engineering-pi

Made for: Claude Code.

Or install compound-engineering, the plugin that ships this one along with the rest of its 41 skills, 1 MCP server.

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/gvkhosla/compound-engineering-pi/slfg.svg)](https://agentmods.dev/skills/gvkhosla/compound-engineering-pi/slfg)
Your own site
<a href="https://agentmods.dev/skills/gvkhosla/compound-engineering-pi/slfg"><img src="https://agentmods.dev/badge/skills/gvkhosla/compound-engineering-pi/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 435 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 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 $0.00435
Opus 5 $0.00006 $0.00217
Sonnet 5 $0.00003 $0.00087
Haiku 4.5 $0.00001 $0.00044

Measured 8d ago against content hash 94ff370e4607, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-07, 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 8d 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.

plugins/compound-engineering/skills/slfg/SKILL.md · 36 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 /compound-engineering: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 — spawn as background Task agent
  2. /compound-engineering:test-browser — spawn as background Task agent

Wait for both to complete before continuing.

Finalize Phase

  1. /compound-engineering:resolve-todo-parallel — resolve findings, compound on learnings, clean up completed todos
  2. /compound-engineering:feature-video — record the final walkthrough and add to PR
  3. Output <promise>DONE</promise> when video is in PR

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. 8d ago First seen · 36 lines · 13 tokens per session scan A 94ff370e4607

Subscribe to this mod's changes

slfg is a skill published in the GitHub repository gvkhosla/compound-engineering-pi (51 stars, last pushed 4mo ago), licensed MIT. It adds 13 tokens to every session and 435 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

codex-claude-worker

Translate natural-language user requests into bounded Claude Code worker tasks while Codex or ChatGPT remains the supervisor. Use when the user gives an ordinary prompt and wants Codex to clarify scope, choose a safe work boundary, generate a worker prompt, approve or defer worker execution, read run summaries and…

zhuzai-2007/claude-code-mcp-harness · 86 tokens

write-swift

How to write modern Swift well — modeling with value types, Swift 6 data-race safety and approachable concurrency (@concurrent, main-actor-by-default, actors, task groups), protocols and generics (some vs any), API design, performance and ARC, Swift Testing, macros, and the modern language features agents don't know…

wangmiaozero/pi-harness · 107 tokens

apple-design

Apple's approach to interface design and fluid, physical motion, translated for the web. Use when building or reviewing gesture-driven UI, spring animations, drag/swipe/sheet interactions, momentum and interruptible transitions, translucent materials and depth, typography (optical sizing, tracking, leading)…

wangmiaozero/pi-harness · 80 tokens

emil-design-eng

This skill encodes Emil Kowalski's philosophy on UI polish, component design, animation decisions, and the invisible details that make software feel great.

wangmiaozero/pi-harness · 35 tokens

provider-model-discovery

Descobre e seleciona modelos de providers LLM de forma report-only: inventário read-only de modelos, docs oficiais, quota/billing/rate gates e shortlist para canary protegido. Use antes de adicionar providers, escolher modelos ou migrar monitores/roteamento.

aretw0/agents-lab · 60 tokens

source-research

Research open-source libraries with evidence-backed answers and GitHub permalinks. Use when the user asks about library internals, needs implementation details with source code references, wants to understand why something was changed, or needs authoritative answers backed by actual code. Excels at navigating large…

aretw0/agents-lab · 71 tokens