tfx-prune

tfx-prune is a skill for Claude Code, Codex from tellang/triflux. It costs 51 tokens per session (2,394 once invoked), scanned A, original, MIT.

A cleanup workflow that asks three AI coding assistants to independently identify unnecessary code, then removes only issues they agree are unwanted. It checks for duplication, needless abstractions, excessive error handling, and similar readability problems.

In plain words
What is it for?
Use it for an explicitly requested TFX cleanup or three-way review of code clutter. It can inspect code structure, implementation efficiency, and readability before proposing removals.
Why use it?
AI-generated code can contain extra layers, repeated logic, or handling for impossible cases. Agreement from three reviewers provides a defined check before cleanup changes are made.

Skill for Claude CodeCodex

Written for Claude Code and Codex: argument-hint in frontmatter, but also runs codex exec. Also seen: names the AskUserQuestion tool; mentions Codex; mentions Gemini CLI.

Part of the triflux plugin — 29 skills, 1 agent, 12 hooks shipped together

Good fit Use it for an explicitly requested TFX cleanup or three-way review of code clutter. It can inspect code structure, implementation efficiency, and readability before proposing removals.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/tellang/triflux/tfx-prune
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 tellang/triflux --skill tfx-prune
Clone the repo
git clone --depth 1 https://github.com/tellang/triflux

Made for: Claude Code, Codex.

Or install triflux, the plugin that ships this one along with the rest of its 29 skills, 1 agent, 12 hooks.

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 tfx-prune

README.md
[![agentmods](https://agentmods.dev/badge/skills/tellang/triflux/tfx-prune/github.svg)](https://agentmods.dev/skills/tellang/triflux/tfx-prune)
Your own site
<a href="https://agentmods.dev/skills/tellang/triflux/tfx-prune"><img src="https://agentmods.dev/badge/skills/tellang/triflux/tfx-prune/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 tfx-prune

Your own site · 80×15
<a href="https://agentmods.dev/skills/tellang/triflux/tfx-prune"><img src="https://agentmods.dev/badge/skills/tellang/triflux/tfx-prune.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 51 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,394 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. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
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 $0.00051 $0.02394
Opus 5 $0.00026 $0.01197
Sonnet 5 $0.00010 $0.00479
Haiku 4.5 $0.00005 $0.00239

Measured 10d ago against content hash e50470d2ccd8, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-09, from the pricing page.

Security

Grade A, and why

tfx-prune 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 10d 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.

packages/triflux/skills/tfx-prune/SKILL.md · 197 lines

How it starts

The opening of the file, as written. The whole thing — 197 lines — stays where its author put it; the contents beside it link to each section on GitHub.

tfx-prune — Tri-Verified AI Slop Remover

라우팅 정본 D8은 .claude/rules/tfx-routing.md를 따른다.

ARGUMENTS 처리: 이 스킬이 ARGUMENTS: <값>과 함께 호출되면, 해당 값을 사용자 입력으로 취급하여 워크플로우의 첫 단계 입력으로 사용한다. ARGUMENTS가 비어있거나 없으면 기존 절차대로 사용자에게 입력을 요청한다.

OMC ai-slop-cleaner 오마주. 핵심 차별점: 단일 판단이 아닌 3자 독립 감지 + 합의 기반 제거. "AI가 만든 슬롭은 AI 3명이 합의해야 슬롭이다."

HARD RULES

headless-guard가 이 규칙 위반을 자동 차단한다. 우회 불가.

  1. codex exec 직접 호출 및 deprecated Gemini CLI 직접 호출 절대 금지
  2. Codex·Antigravity → Bash("tfx multi --auto-attach --dashboard --assign 'cli:프롬프트:역할' --timeout 1800", run_in_background=true) 사용 — teammate mode는 생략해 auto 기본값을 쓰며, foreground Bash는 하니스가 600s에 강제 종료. 결과는 task-notification 후 회수
  3. Claude → Agent(run_in_background=true)
  4. Bash + Agent를 같은 메시지에서 동시 호출하여 병렬 실행

MODEL ROLES

CLI 역할 감지 관점
Claude (Opus) 코드 품질 분석 + 합의 중재 설계 원칙, 코드 구조, 불필요 추상화
Codex AI 슬롭 탐지 구현 효율, 중복 패턴, 과잉 에러 핸들링
Antigravity 가독성 평가 가독성/DX, 과잉 주석, 과잉 타입

슬롭 카테고리

카테고리 설명 예시
불필요 추상화 단일 용도인데 인터페이스/팩토리/전략 패턴 적용 UserFactory for 1 user type
중복 코드 같은 로직의 반복 동일 validation을 3곳에 복붙
과잉 에러 핸들링 발생 불가능한 에러를 처리 catch (e) { /* impossible */ }
과잉 주석 코드가 이미 명확한데 주석 // increment i by 1 i++
과잉 타입 불필요하게 복잡한 타입 정의 5단계 중첩 제네릭
사용되지 않는 코드 import 했지만 사용 안 함 dead imports, unused variables
과잉 로깅 불필요한 console.log/debug console.log("here")

EXECUTION STEPS

Step 0: 슬롭 제거 범위 선택

인자 없이 호출된 경우 사용자에게 범위를 선택받는다:

1. 최근 변경 파일만 (git diff)
2. 전체 프로젝트
3. 특정 디렉토리 지정
  • 1번 → git diff HEAD로 최근 변경 파일 대상
  • 2번 → 프로젝트 전체 소스 파일 대상 (대규모 주의 경고 표시)
  • 3번 → 추가 AskUserQuestion으로 대상 디렉토리 경로 입력받음

파일 경로나 git diff 범위가 인자로 이미 제공된 경우 이 단계를 건너뛴다.

Step 1: 대상 파일 수집

대상 결정 우선순위:

  1. 파일 경로 지정 → 해당 파일만
  2. git diff 범위 지정 → diff에 포함된 파일
  3. 입력 없음 → git diff --name-only HEAD~1로 최근 변경 파일
  4. "all" → 프로젝트 전체 소스 파일 (주의: 대규모)

소스 파일만 필터: .ts, .js, .mjs, .tsx, .py 등. node_modules, dist, build 제외.

Read the full file on GitHub · 197 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. 10d ago First seen · 197 lines · 51 tokens per session scan A e50470d2ccd8

Subscribe to this mod's changes

tfx-prune is a skill published in the GitHub repository tellang/triflux (7 stars, last pushed yesterday), licensed MIT. It adds 51 tokens to every session and 2,394 once invoked, about $0.0003 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.

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