tfx-research

tfx-research is a skill for Claude Code, Codex from tellang/triflux. It costs 149 tokens per session (2,284 once invoked), scanned A, original, MIT.

A web-research workflow that searches several sources and compares the results. It supports quick searches, automatic query creation, and deeper research reports.

In plain words
What is it for?
Use it to find current information, investigate unfamiliar topics, check whether a tool or feature exists, and create a structured research report.
Why use it?
It reduces the need to search repeatedly and check each source by hand. Comparing sources can help identify conflicting or incomplete information.

Skill for Claude CodeCodex

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

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

Good fit Use it to find current information, investigate unfamiliar topics, check whether a tool or feature exists, and create a structured research report.

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

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

Your own site · 80×15
<a href="https://agentmods.dev/skills/tellang/triflux/tfx-research"><img src="https://agentmods.dev/badge/skills/tellang/triflux/tfx-research.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 149 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,284 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 $0.00149 $0.02284
Opus 5 $0.00075 $0.01142
Sonnet 5 $0.00030 $0.00457
Haiku 4.5 $0.00015 $0.00228

Measured 11d ago against content hash d634f9fc653e, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-10, from the pricing page.

Security

Grade A, and why

tfx-research 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 11d 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-research/SKILL.md · 214 lines

How it starts

The opening of the file, as written. The whole thing — 214 lines — stays where its author put it; the contents beside it link to each section on GitHub.

tfx-research — Web Research (Deep by Default)

ARGUMENTS 처리: --quick → Quick. --auto → Auto. 그 외 → Deep (기본).

AI makes completeness near-free. 기본은 Claude(Exa/학술) + Codex(Brave/실용) 2-CLI 멀티소스 교차검증 합의 (Antigravity/Tavily는 agy --print idle 미도달 행으로 Deep 제외; Quick 단일 검색만 유지). 빠른 단일 Google Search 는 --quick. 자율 쿼리생성+구조화 보고서 는 --auto.


모드 분기

플래그 모드 특징
(없음) Deep (기본) 2-CLI 멀티소스 교차검증, consensus score
--quick Quick Antigravity 단일 Google Search
--auto Auto 자율 쿼리생성(3-5개) + 검색 + 구조화 보고서

Deep 모드 (기본)

HARD RULES

  1. codex exec 직접 호출 및 deprecated Gemini CLI 직접 호출 금지
  2. Codex/Antigravity → Bash("tfx multi ...")
  3. Claude → Agent(run_in_background=true)
  4. Bash + Agent 동시 호출

모델/소스 역할

CLI MCP 관점
Claude Exa (neural semantic) 학술/기술 깊이, 공식 문서, 벤치마크
Codex Brave Search 실용/구현/산업 사례

Depth 모드 (--depth 플래그)

모드 서브쿼리 소스/쿼리 라운드 토큰 시간
quick 3 2 1 ~20K 2-3분
standard 5 3 1-2 ~40K 5-8분 (기본)
deep 8-10 5 2-3 ~80K 10-15분

EXECUTION

Pre-Phase: Depth 선택

--depth 미지정 시 AskUserQuestion.

Step 1: 주제 분석 및 쿼리 분해 (Claude Opus)
  • depth 에 따른 서브쿼리 생성
  • 각 쿼리에 관점(학술/실용/DX) 매핑
Step 2: 2-CLI 독립 병렬 검색 (Anti-Herding) — Bash + Agent 동시 호출

Agent (Claude + Exa):

Agent(
  subagent_type="claude",
  model="opus",
  run_in_background=true,
  prompt="서브쿼리를 Exa web_search_exa 로 검색. 서브쿼리: {sub_queries}. 관점: 학술/기술. category='research paper' 우선, highlights=true, numResults=5. 각 결과 제목/URL/핵심 추출."
)

Bash (Codex + Brave): (Antigravity/agy 제외 — agy --print 는 무거운 리서치에서 idle 미도달 시 5분 행; route 에서 --print-timeout 180s 로 bound)

Bash("tfx multi --auto-attach --dashboard \
  --assign 'codex:서브쿼리를 Brave Search 로 검색. 서브쿼리: {sub_queries}. 관점: 실용/산업. brave_web_search + brave_news_search, freshness=pw. 각 쿼리 상위 5개 구조화.:researcher' \
  --timeout 1800", run_in_background=true)

Read the full file on GitHub · 214 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. 11d ago First seen · 214 lines · 149 tokens per session scan A d634f9fc653e

Subscribe to this mod's changes

tfx-research is a skill published in the GitHub repository tellang/triflux (7 stars, last pushed 2d ago), licensed MIT. It adds 149 tokens to every session and 2,284 once invoked, about $0.0007 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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