tfx-auto

tfx-auto is a skill for Claude Code, Codex from tellang/triflux. It costs 139 tokens per session (16,879 once invoked), scanned C, original, MIT.

A command-line coordinator for coding-agent work. It classifies implementation and code-change requests, then sends them to a chosen workflow, with flags to override its decisions.

In plain words
What is it for?
Use it for requests to build, implement, fix, or modify code. It is also for choosing the operating mode, parallel execution, retries, isolation, or remote handling through command flags.
Why use it?
It removes the need to decide which coding workflow or command should handle each request. It can also split work into parallel tasks when explicitly requested.

Skill for Claude CodeCodex

Written for Claude Code and Codex: argument-hint in frontmatter, but also runs codex exec. Also seen: reads .claude/ paths; mentions subagents; mentions Claude Code.

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

Good fit Use it for requests to build, implement, fix, or modify code. It is also for choosing the operating mode, parallel execution, retries, isolation, or remote handling through command flags.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/tellang/triflux/tfx-auto
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-auto
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-auto

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

Your own site · 80×15
<a href="https://agentmods.dev/skills/tellang/triflux/tfx-auto"><img src="https://agentmods.dev/badge/skills/tellang/triflux/tfx-auto.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 139 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 16,879 The whole file, excluding the scripts and references it only reads on demand.
Security scan C 2 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 $0.00139 $0.16879
Opus 5 $0.00069 $0.08440
Sonnet 5 $0.00028 $0.03376
Haiku 4.5 $0.00014 $0.01688

Measured 10d ago against content hash f2890c43e984, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-09, from the pricing page.

Security

Grade C, and why

tfx-auto scanned grade C with 2 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.

Downloads and executes remote codehighSupply chain

curl | sh runs whatever the server returns today, which is not necessarily what it returned when this was reviewed.

- codex: `npm install -g @openai/codex` | antigravity: `curl -fsSL https://antigravity.google/cli/install.sh | bash`

Makes network callslowCapability

Not a fault in itself. Listed so you know the mod talks to something, and to what.

- codex: `npm install -g @openai/codex` | antigravity: `curl -fsSL https://antigravity.google/cli/install.sh | bash`
packages/triflux/skills/tfx-auto/SKILL.md · 1,114 lines

How it starts

The opening of the file, as written. The whole thing — 1,114 lines — stays where its author put it; the contents beside it link to each section on GitHub.

tfx-auto — 통합 CLI 오케스트레이터

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.

Step 0: 스마트 라우팅 (tfx-auto 진입 시 자동 실행)

preamble에서 routing-weights.json을 읽고, 사용자 입력을 분석하여 dispatch 결정.

SLUG=$(basename "$(git rev-parse --show-toplevel 2>/dev/null)" 2>/dev/null || echo "unknown")
WEIGHTS_FILE="$HOME/.gstack/projects/$SLUG/routing-weights.json"
USER_MODE=""
if [ -f "$WEIGHTS_FILE" ]; then
  USER_MODE=$(node -e "
    const w=JSON.parse(require('fs').readFileSync('$WEIGHTS_FILE','utf8'));
    const m=w.weights?.mode_bias||{};
    const top=Object.entries(m).sort((a,b)=>b[1]-a[1])[0];
    if(top && top[1]>0.3) console.log(top[0]);
  " 2>/dev/null)
fi
echo "USER_PREFERRED_MODE: ${USER_MODE:-none}"

판단 기준 (우선순위 순):

  1. 명시 플래그 (최우선, 추론 스킵): ARGUMENTS 에 --cli/--mode/--risk-tier/--shape/--cli-set/--parallel/--retry/--isolation/--remote 플래그가 있으면 분류/추론을 건너뛰고 플래그 값대로 즉시 dispatch. 자세한 플래그 동작은 아래 "플래그 오버라이드" 섹션 참조.

    • --parallel swarm → tfx-swarm 엔진 위임 (PRD 필요)
    • --parallel N → tfx-multi 엔진 위임 (auto: 리드 tmux면 interactive pane, 없으면 in-process)
    • --cli codex|antigravityTFX_CLI_MODE 설정 + 단일 실행
    • --mode deep-t/--thorough 동일 동작 (pipeline init)
    • --risk-tier low|medium|high → risk-tier 기준으로 verification 강도와 mode 결정
    • --mode ... 명시 시 --risk-tier 는 무시 (mode 우선)
    • --mode consensus --shape debate|panel → prompt ensemble fold 경로
    • --mode livetfx-live 엔진 위임 (분해/트리아지 스킵)
    • --retry ralph → stderr 경고 후 bounded 3회 degrade (Phase 2 미구현)
  2. 사용자 명시 키워드 (플래그 없을 때):

    • "swarm", "PRD 돌려", "격리해서", "충돌 없이 돌려" → --parallel swarm --mode consensus --isolation worktree
    • "병렬", "동시에", "multi", "협업"(단순 동시 작업 의미) → --parallel N --mode deep — 여기서 미리 swarm으로 단정하지 않는다. 실제 코드 변경이 여러 파일에 걸치면 "멀티 태스크 라우팅"의 자동 분류가 swarm으로 승격시킨다 ("병렬" 한 단어만으로 곧장 worktree 격리+3-CLI 합의까지 가는 건 과함)
    • "팀"은 모호하다: 서로 메시지를 주고받는 영속 협업을 원하면 정답은 OMC 네이티브 /team이고(tfx-auto 관할 밖), 그냥 여러 작업을 동시에 처리해달라는 뜻이면 바로 위 --parallel N 행을 따른다. "팀"만 보고 바로 --parallel N으로 단정하지 말고 어느 쪽인지 애매하면 되묻는다
    • "꼼꼼히", "제대로", "deep" → --mode deep
    • "끝까지", "멈추지마", "ralph" → --retry ralph
    • "codex로", "antigravity로" → --cli codex 또는 --cli antigravity
    • "원격으로", "다른 기기에서", "리모트로 돌려" → --remote <host> (--parallel swarm 자동 동반. host 미지정 시 hosts.json 목록에서 질의)
    • "논쟁시켜", "서로 반박하게 해", "계속 대화하면서 풀게", "왕복으로 주고받게" → --mode live (tfx-live peer 고정). "협업"/"팀"과 겹쳐 보여도 이 쪽은 "논쟁/반박/대화를 계속 이어간다"는 뉘앙스가 명시적으로 있을 때만 해당

Read the full file on GitHub · 1,114 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 · 1,114 lines · 139 tokens per session scan C f2890c43e984

Subscribe to this mod's changes

tfx-auto is a skill published in the GitHub repository tellang/triflux (7 stars, last pushed yesterday), licensed MIT. It adds 139 tokens to every session and 16,879 once invoked, about $0.0007 per session on Opus 5. A static security scan graded it C with 2 findings (downloads and executes remote code, makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.

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