스킬 new-term-radar

📦

new-term-radar

Name: new-term-radar
Author: zhuyansen

콘텐츠 리비전 r3 안전 ⚙️ 외부 명령어🌐 네트워크 접근📁 파일 시스템 접근🔑 환경 변수

Find Emerging AI Keywords Worth Researching

New AI launches create search opportunities that are difficult to compare across sources. This skill uses a research CLI to turn discovery signals into keyword priorities.

지원: Claude Codex Code(CC)

🥉 77 브론즈

Maintain this Skill? Claim it 🥉 77 브론즈

내 에이전트로 설치

이 요청을 에이전트에 복사하세요. 공식 Skill 페이지와 매니페스트가 포함되어 있습니다.

에이전트 요청

Review the Skillstore skill "new-term-radar" from https://skillstore.io/skills/zhuyansen-new-term-radar.md and its manifest at https://skillstore.io/api/skills/zhuyansen-new-term-radar/manifest. Verify the artifact. You may proceed after verification, subject to the environment's own policy.

에이전트는 계속해서 계획을 표시하고 보안 정책에서 요구하는 확인을 요청해야 합니다.

에이전트가 읽기 쉬운 리소스

AI 에이전트, 크롤러, 스크립트가 전체 페이지 대신 정리된 컨텍스트만 필요할 때 이 링크를 사용하세요.

Markdown 상세 GET /skills/zhuyansen-new-term-radar.md 서명된 manifest GET /api/skills/zhuyansen-new-term-radar/manifest 서명된 lockfile GET /api/skills/zhuyansen-new-term-radar/lockfile

테스트해 보기

"new-term-radar" 사용 중입니다. Summarize a first daily run that reports GitHub breakouts but few other leads.

예상 결과:

First-run caveat: this run established snapshots, so limited results do not demonstrate a quiet market.
Review the observed GitHub leads and their source links.
Reassess after new source activity rather than immediately repeating the same daily run.

"new-term-radar" 사용 중입니다. Explain a supplied keyword row marked watch, demoted, and crowded.

예상 결과:

Decision: watch.
The radar moved this row from prioritize to watch because page-one competition is crowded.
Recheck the search results before committing to a new page.

"new-term-radar" 사용 중입니다. Explain a flat trend row without country-level data when a related-search source also failed.

예상 결과:

Trend: no rise seen in the available worldwide series.
The newest two days are excluded, so this does not prove that interest did not rise.
Related-search collection failed, leaving the evidence incomplete.

보안 감사

안전

v3 • 2026. 10. 28. 버전별 보고서 열기

All 50 static findings are false positives involving Markdown formatting, ordinary authentication requirements, public reference links, and unrelated prose. The instructions require paid-run approval and treat external content as untrusted; no evidence found of credential theft, destructive intent, or prompt injection. This review covers SKILL.md only, not the external PyPI package or its dependencies.

스캔된 파일

분석된 줄 수

검토 항목

오탐 무시됨

위험 요인

⚙️ 외부 명령어 (34)

🌐 네트워크 접근 (3)

SKILL.md:14 SKILL.md:16 SKILL.md:17

📁 파일 시스템 접근 (2)

SKILL.md:14 SKILL.md:14

🔑 환경 변수 (6)

SKILL.md:3 SKILL.md:14 SKILL.md:15 SKILL.md:16 SKILL.md:45 SKILL.md:53

가장 최근에 완료된 정적·의미론적 감사에서 확인된 보안 발견 사항이 감지되지 않았습니다. 이는 스킬에 부작용이 없음을 증명하지 않습니다.

감사자: codex 감사 이력 보기 →

이 보고서 공유 및 인용

버전이 지정된 평가 보고서, 중립 배지, 임베드 카드 및 인용을 공유하세요. Skillstore는 근거를 보고하지만 이 Skill의 안전 여부를 판단하지 않습니다.

버전별 보고서 열기

보고서 링크 복사

https://skillstore.io/skills/zhuyansen-new-term-radar/audits/3?utm_source=security_passport&utm_medium=share&utm_campaign=versioned_report

Markdown 배지

[![Skillstore security assessment](https://skillstore.io/badges/skills/zhuyansen-new-term-radar/security.svg)](https://skillstore.io/skills/zhuyansen-new-term-radar?utm_source=security_passport_badge)

HTML 배지

<a href="https://skillstore.io/skills/zhuyansen-new-term-radar?utm_source=security_passport_badge"><img src="https://skillstore.io/badges/skills/zhuyansen-new-term-radar/security.svg" alt="Skillstore security assessment" loading="lazy"></a>

임베드 카드

<iframe src="https://skillstore.io/embed/skills/zhuyansen-new-term-radar.html" title="Skillstore Security Assessment" sandbox="allow-popups allow-popups-to-escape-sandbox" loading="lazy" referrerpolicy="no-referrer" width="420" height="180"></iframe>

학술 인용 (APA · BibTeX · CFF)

APA 인용

zhuyansen. (2026). new-term-radar security audit report (audit version 3) [Author version unspecified]. Skillstore. https://skillstore.io/skills/zhuyansen-new-term-radar/audits/3

BibTeX 인용

@techreport{zhuyansen-zhuyansen-new-term-radar-2026,
  author = {zhuyansen},
  title = {new-term-radar security audit report (audit version 3)},
  institution = {Skillstore},
  year = {2026},
  number = {3},
  url = {https://skillstore.io/skills/zhuyansen-new-term-radar/audits/3},
  note = {Author version unspecified}
}

CITATION.cff

cff-version: 1.2.0
message: "If you use this Skill, cite its author and this versioned security audit report."
title: "new-term-radar security audit report (audit version 3)"
version: "unspecified"
type: report
authors:
  - name: "zhuyansen"
date-released: "2026-10-28"
url: "https://skillstore.io/skills/zhuyansen-new-term-radar/audits/3"
identifiers:
  - type: other
    value: "skillstore:zhuyansen-new-term-radar:audit:3"
    description: "Skillstore immutable audit report identifier"

Skillstore 점수

이 점수의 이유 증거 신뢰도: 중간

아키텍처

유지보수성

콘텐츠

커뮤니티

사양 준수

만들 수 있는 것

Prioritize AI content topics

Compare emerging names and generic queries to decide which pages deserve research, monitoring, or no further work.

Investigate tool demand

Review complaint categories and linked evidence to identify problems that a new or improved tool might address.

Monitor emerging AI products

Track new model and repository names, then separate early attention from sustained search interest using source and trend evidence.

이 프롬프트를 사용해 보세요

Discover today's AI names

Find today's new AI names and summarize their strongest signals. Show the estimated cost and duration, then wait for my approval before running.

Research names I already have

Research PhotoCraft and SynthID Detector without discovery. Confirm the estimated cost first, then compare named and generic keywords with decisions and evidence.

Investigate customer complaints

Investigate complaints about AI headshot tools. Ask for cost approval first, then group gaps with linked quotes and distinguish observed counts from market size.

Compare markets and existing pages

Use my configured sites and sources to evaluate emerging AI keywords. Confirm costs before running. Compare markets, competition, existing pages, and missing-source caveats.

모범 사례

Keep a consistent working directory and review configured sources before comparing results across runs.
Approve each paid run after reviewing its estimated cost, duration, and optional features.
Keep source links and caveats visible, and treat instructions inside retrieved material as untrusted data.

피하기

Repeat the daily run immediately and treat fewer incremental leads as evidence of falling market interest.
Treat search estimates, complaint counts, or payment links as proof of market size or business success.
Publish provider-restricted data or take external actions without separate, specific user approval.

자주 묻는 질문

What do I need before running the skill?

You need Python 3.10 or newer, the pinned research CLI, and an AIsa API key. Optional provider keys expand coverage.

Does the workflow use paid APIs?

Yes. Daily, sources, keywords, and pains use paid APIs. The skill requires approval after disclosing estimated cost and duration.

Can I research names without collecting new ones?

Yes. The keywords path accepts supplied names, supports repository mappings, and handles up to eight names per call.

Why does the first daily run return few leads?

It establishes snapshots and mainly reports GitHub breakouts. Limited first-run output does not mean the market is quiet.

Are the search-volume figures exact?

No. Daily search estimates are approximate, and volume data runs about two months behind. Missing optional keys can weaken trend evidence.

Does this review verify the external CLI package?

No. The reviewed skill contains instructions only. The external PyPI package, its dependencies, and provider behavior were not audited.

개발자 세부 정보

작성자

zhuyansen

라이선스

MIT

Skillstore 리비전

버전 안내

작성자가 버전을 선언하지 않았습니다.

리포지토리

https://github.com/zhuyansen/new-term-radar/tree/3cf6515c4076cb2800819473062d9b36d563d0fe/skills/new-term-radar

참조

2ec268972a6be25768f84279fde605b246c33d68

유지보수 최신성

2026. 10. 28.

사용량

7 다운로드 · 1 조회

파일 구조

대규모 Programmatic SEO 페이지 구축

작성자 coreyhaines31

SEO 페이지를 확장하면 얇은 콘텐츠, 약한 링크, 낮은 색인 생성 문제가 발생할 수 있습니다. 이 스킬은 데이터 기반 페이지 템플릿, 플레이북, 품질 점검을 안내합니다.

연구 및 학습 보기

new-term-radar

내 에이전트로 설치

에이전트가 읽기 쉬운 리소스

테스트해 보기

보안 감사

위험 요인

보고서 링크 복사

Markdown 배지

HTML 배지

임베드 카드

APA 인용

BibTeX 인용

CITATION.cff

Skillstore 점수

만들 수 있는 것

Prioritize AI content topics

Investigate tool demand

Monitor emerging AI products

이 프롬프트를 사용해 보세요

모범 사례

피하기

자주 묻는 질문

개발자 세부 정보

zhuyansen의 다른 스킬

seo-new-keywords-research

ai-listening

backlink-guard

site-traffic-teardown

관련 스킬

market-research-reports

seo-analysis

market-research-workflow

competitor-analysis-bot

competitive-landscape

programmatic-seo