스킬 feeling-search
📦

feeling-search

v1.1.2 콘텐츠 리비전 r4 중간 위험 ⚙️ 외부 명령어🌐 네트워크 접근📁 파일 시스템 접근🔑 환경 변수

Find Visual Styles from Mood Descriptions

Mood descriptions often lack precise visual vocabulary. This skill matches short descriptions to ranked styles, defining terms, and optional reference-image metadata.

지원: Claude Codex Code(CC)
Maintain this Skill? Claim it 📊 74 적절함

내 에이전트로 설치

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

에이전트 요청
Review the Skillstore skill "feeling-search" from https://skillstore.io/skills/xixi048-feeling-search.md and its manifest at https://skillstore.io/api/skills/xixi048-feeling-search/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/xixi048-feeling-search.md 서명된 manifest GET /api/skills/xixi048-feeling-search/manifest 서명된 lockfile GET /api/skills/xixi048-feeling-search/lockfile

테스트해 보기

"feeling-search" 사용 중입니다. Summarize the documented rainy convenience-store example.

예상 결과:

  • Documented local matches include light and white.
  • Style candidates include Delft School, Ash Winter, and De Stijl.
  • These are vocabulary matches, not a definitive interpretation of the scene.

"feeling-search" 사용 중입니다. Explain the documented cold-light lookup.

예상 결과:

  • English term: cold even light.
  • Meaning: uniform, high-temperature lighting with pale blue or white tones.
  • Related styles include Luminism.

보안 감사

중간 위험
v4 • 2026. 10. 28. 버전별 보고서 열기

Most alerts are false positives involving Markdown backticks, multilingual prose, ordinary Python indexing, and documented application configuration. Confirmed risks concern quota tokens in GET URLs and token files created without restrictive permissions. Configurable endpoints also lack HTTPS enforcement; no evidence found for prompt injection, obfuscated execution, or deliberate credential exfiltration.

3
스캔된 파일
1,099
분석된 줄 수
3
검토 항목
0
오탐 무시됨

확인된 보안 우려 사항 (1)

중간
scripts/fs_api.py:75-80scripts/fs_api.py:111-113scripts/fs_api.py:532-548
Quota Credentials Can Be Sent to Insecure Configured Endpoints
env_base accepts FS_API_BASE without HTTPS validation. Quota and image commands reuse saved bearer tokens against that endpoint, exposing credentials over plaintext HTTP.
The code directly concatenates the configured base with authenticated routes without checking its scheme. Exploitation requires an insecure endpoint configuration; the default uses HTTPS.
기능 검토 항목 (3)

이 스킬에 대해 예상될 수 있는 실제 로컬 기능이므로 검토가 필요하지만, 확인된 악의적 동작으로는 집계되지 않습니다.

중간
scripts/fs_api.py:122
Python file write/append
with open(tmp, "w", encoding="utf-8") as fh:
save_quota writes bearer tokens using ordinary open without enforcing private permissions. Under permissive umasks, other local users can read accessible credential files.
낮음
scripts/fs_api.py:156
Python HTTP libraries
req = urllib.request.Request(url, method="GET")
The GET helper accepts quota_url output containing the bearer token in its query string. Token validation and balance requests expose credentials to URL logging.
낮음
scripts/fs_api.py:161
Python HTTP libraries
with urllib.request.urlopen(req, timeout=TIMEOUT) as resp:
urlopen transmits GET requests used by quota validation and balance commands. Their URLs include bearer tokens, creating credential exposure through server or proxy logs.

위험 요인

⚙️ 외부 명령어 (50)
scripts/fs_api.py:103 scripts/fs_api.py:112 scripts/fs_api.py:221 scripts/fs_api.py:417 scripts/fs_api.py:418 scripts/fs_api.py:502 scripts/fs_api.py:503 SKILL.md:17-21 SKILL.md:21-36 SKILL.md:36-37 SKILL.md:37-38 SKILL.md:38 SKILL.md:43-45 SKILL.md:45-50 SKILL.md:50-52 SKILL.md:52-55 SKILL.md:55-57 SKILL.md:57 SKILL.md:66-67 SKILL.md:67-73 SKILL.md:73-75 SKILL.md:75-77 SKILL.md:77-78 SKILL.md:78-82 SKILL.md:82-84 SKILL.md:84-86 SKILL.md:86-91 SKILL.md:91-97 SKILL.md:97-100 SKILL.md:100 SKILL.md:102-106 SKILL.md:106-111 SKILL.md:111-113 SKILL.md:113-114 SKILL.md:114-117 SKILL.md:117 SKILL.md:120 SKILL.md:121-122 SKILL.md:122-126 SKILL.md:126-129 SKILL.md:129-133 SKILL.md:133-136 SKILL.md:136-138 SKILL.md:138 SKILL.md:139 SKILL.md:144-150 SKILL.md:150-151 SKILL.md:151-152 SKILL.md:152-153 SKILL.md:153
🌐 네트워크 접근 (10)
scripts/fs_api.py:46 scripts/fs_api.py:156 scripts/fs_api.py:161 scripts/fs_api.py:180 scripts/fs_api.py:186 scripts/fs_api.py:27 scripts/fs_api.py:31 scripts/fs_api.py:54 SKILL.md:122 SKILL.md:168
📁 파일 시스템 접근 (12)
scripts/fs_api.py:33 scripts/fs_api.py:33 scripts/fs_api.py:122 scripts/fs_api.py:227 scripts/fs_api.py:117 scripts/fs_api.py:225 SKILL.md:78 SKILL.md:120 SKILL.md:169 SKILL.md:78 SKILL.md:120 SKILL.md:169
🔑 환경 변수 (4)
scripts/fs_api.py:76 scripts/fs_api.py:80 scripts/fs_api.py:84 scripts/fs_api.py:148
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
보안 평가

보고서 링크 복사

https://skillstore.io/skills/xixi048-feeling-search/audits/4?utm_source=security_passport&utm_medium=share&utm_campaign=versioned_report

Markdown 배지

[![Skillstore security assessment](https://skillstore.io/badges/skills/xixi048-feeling-search/security.svg)](https://skillstore.io/skills/xixi048-feeling-search?utm_source=security_passport_badge)

HTML 배지

<a href="https://skillstore.io/skills/xixi048-feeling-search?utm_source=security_passport_badge"><img src="https://skillstore.io/badges/skills/xixi048-feeling-search/security.svg" alt="Skillstore security assessment" loading="lazy"></a>

임베드 카드

<iframe src="https://skillstore.io/embed/skills/xixi048-feeling-search.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

xixi048. (2026). feeling-search security audit report (audit version 4) [Author version 1.1.2]. Skillstore. https://skillstore.io/skills/xixi048-feeling-search/audits/4

BibTeX 인용

@techreport{xixi048-xixi048-feeling-search-2026, author = {xixi048}, title = {feeling-search security audit report (audit version 4)}, institution = {Skillstore}, year = {2026}, number = {4}, url = {https://skillstore.io/skills/xixi048-feeling-search/audits/4}, note = {Author version 1.1.2} }

CITATION.cff

cff-version: 1.2.0 message: "If you use this Skill, cite its author and this versioned security audit report." title: "feeling-search security audit report (audit version 4)" version: "1.1.2" type: report authors: - name: "xixi048" date-released: "2026-10-28" url: "https://skillstore.io/skills/xixi048-feeling-search/audits/4" identifiers: - type: other value: "skillstore:xixi048-feeling-search:audit:4" description: "Skillstore immutable audit report identifier"

Skillstore 점수

이 점수의 이유 증거 신뢰도: 중간
64
아키텍처
100
유지보수성
87
콘텐츠
65
커뮤니티
91
사양 준수

만들 수 있는 것

Explore Concept-Art Directions

Translate a scene's atmosphere into candidate styles and inspect which words produced each match.

Compare Brand Visual Vocabulary

Compare style definitions and associated words before selecting a visual direction for a campaign.

Research Image-Prompt Terms

Find style names and related vocabulary to refine prompts for a separate image-generation tool.

이 프롬프트를 사용해 보세요

Find Initial Style Candidates 
Find visual styles for a rainy walk past a convenience store under cold white lights. Show style names and matched words.
Refine Local Matches 
Analyze my description using the local dictionary, then compare fuzzy matching. Explain changed matches and do not enable cloud analysis.
Investigate a Named Style 
Look up the words associated with cyberpunk. Explain distinctive vocabulary and request my approval before retrieving images or using paid endpoints.
Build a Traceable Style Comparison 
Compare up to five matched styles for my brief. Separate local and cloud results, preserve image credits, and obtain approval before cloud or paid requests.

모범 사례

  • Start with a short scene description and review matched words before accepting a style recommendation.
  • Use a trusted HTTPS endpoint, protect quota credentials, and approve cloud transmission or paid requests explicitly.
  • Keep image credits and licensing metadata, and exclude placeholder images from style references.

피하기

  • Treating lexical rankings as objective judgments or expecting this skill to generate finished images.
  • Assuming every command works offline or that cloud fallback works without a token because the documentation describes free service.
  • Sharing quota tokens in prompts or logs, or sending confidential briefs to unapproved cloud endpoints.

자주 묻는 질문

What does this skill return?
It returns matched feeling words and ranked visual styles. Results can include names, definitions, scores, parent styles, and reference-image metadata.
What software does the client require?
The client requires Python 3.8 or later and uses only the standard library.
Can I use it without an internet connection?
Local analysis can use a fresh cached dictionary with offline mode. The initial dictionary download and remote lookup or image requests need connectivity.
Is cloud analysis free?
The documentation reports free service, but pricing can change. This client still requires a quota token before attempting cloud fallback.
Does it generate images or image prompts?
It supplies style vocabulary and retrieves image references. It does not generate finished images or run an image-generation model.
Can I reuse every reference image commercially?
Verify each image's license and source before reuse. Preserve attribution and do not treat placeholder images as real style samples.

개발자 세부 정보

작성자

xixi048

라이선스

MIT

작성자 버전

v1.1.2

Skillstore 리비전

r4

리포지토리

https://github.com/xixi048/feeling-search-skill/tree/e1f69931a1416ba91897ac66488d137d208729db/skills/feeling-search

참조

81dcba714ae5ba0c5bcfb8914fb9bc2fbb2bb48a

유지보수 최신성

2026. 10. 28.

사용량

1 다운로드 · 1 조회

파일 구조

📁 references/

📄 api-contract.md

📁 scripts/

📄 fs_api.py

📄 SKILL.md

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