Track A-Share News Attention with Lava
Stock researchers need consistent measures of news attention across companies and market themes. This skill guides authenticated Lava queries and summarizes mentions, source coverage, rankings, and historical trends.
이 요청을 에이전트에 복사하세요. 공식 Skill 페이지와 매니페스트가 포함되어 있습니다.
Review the Skillstore skill "lava-news-heat" from https://skillstore.io/skills/dustinliang666-blip-lava-news-heat.md and its manifest at https://skillstore.io/api/skills/dustinliang666-blip-lava-news-heat/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.
AI 에이전트, 크롤러, 스크립트가 전체 페이지 대신 정리된 컨텍스트만 필요할 때 이 링크를 사용하세요.
"lava-news-heat" 사용 중입니다. Show a sample seven-day company attention summary.
예상 결과:
"lava-news-heat" 사용 중입니다. Show a sample concept ranking summary.
예상 결과:
All 31 static alerts are false positives involving documented URLs, Markdown formatting, public discovery metadata, source identifiers, or readable Chinese text. No evidence found of prompt injection, credential exfiltration, executable payloads, or local system reconnaissance. The remote service implementation was not supplied, so its behavior and data handling remain unverified.
버전이 지정된 평가 보고서, 중립 배지, 임베드 카드 및 인용을 공유하세요. Skillstore는 근거를 보고하지만 이 Skill의 안전 여부를 판단하지 않습니다.
https://skillstore.io/skills/dustinliang666-blip-lava-news-heat/audits/1?utm_source=security_passport&utm_medium=share&utm_campaign=versioned_report[](https://skillstore.io/skills/dustinliang666-blip-lava-news-heat?utm_source=security_passport_badge)<a href="https://skillstore.io/skills/dustinliang666-blip-lava-news-heat?utm_source=security_passport_badge"><img src="https://skillstore.io/badges/skills/dustinliang666-blip-lava-news-heat/security.svg" alt="Skillstore security assessment" loading="lazy"></a><iframe src="https://skillstore.io/embed/skills/dustinliang666-blip-lava-news-heat.html" title="Skillstore Security Assessment" sandbox="allow-popups allow-popups-to-escape-sandbox" loading="lazy" referrerpolicy="no-referrer" width="420" height="180"></iframe>dustinliang666-blip. (2026). lava-news-heat security audit report (audit version 1) [Author version unspecified]. Skillstore. https://skillstore.io/skills/dustinliang666-blip-lava-news-heat/audits/1@techreport{dustinliang666-blip-dustinliang666-blip-lava-news-heat-2026,
author = {dustinliang666-blip},
title = {lava-news-heat security audit report (audit version 1)},
institution = {Skillstore},
year = {2026},
number = {1},
url = {https://skillstore.io/skills/dustinliang666-blip-lava-news-heat/audits/1},
note = {Author version unspecified}
}cff-version: 1.2.0
message: "If you use this Skill, cite its author and this versioned security audit report."
title: "lava-news-heat security audit report (audit version 1)"
version: "unspecified"
type: report
authors:
- name: "dustinliang666-blip"
date-released: "2026-10-28"
url: "https://skillstore.io/skills/dustinliang666-blip-lava-news-heat/audits/1"
identifiers:
- type: other
value: "skillstore:dustinliang666-blip-lava-news-heat:audit:1"
description: "Skillstore immutable audit report identifier"
Summarize a company over seven days using mention counts, source participation, related concepts, and returned viewpoints.
Compare concept rankings, newly mentioned stocks, and attention acceleration to prioritize daily research.
Request daily heat panels and coverage counts to study attention changes alongside other research data.
Check news attention for [stock name] over seven days. Report mentions, source count, time window, and three returned viewpoints.
Rank the five most-mentioned stocks in [concept] over seven days. Report mention counts and summarize available structured viewpoints without inventing missing data.
Compare market heat and acceleration rankings over 24 hours with newly mentioned stocks. Identify overlaps and report returned attention metrics and source identifiers.
For [stock], request a 90-day heat panel, 30-day coverage counts, and available point-in-time source scores. Separate observations from hypotheses and report gaps.
라이선스
MIT
Skillstore 리비전
r1
버전 안내
작성자가 버전을 선언하지 않았습니다.
리포지토리
https://github.com/dustinliang666-blip/lava-mcp/tree/f9369732c3956024666c80835b72dc7d22df5a43/참조
4699d5d8d8b53ee8ddbe0a18430bcdf40abcc835
유지보수 최신성
2026. 10. 28.
사용량
0 다운로드 · 0 조회
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