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.
Copia esta solicitud en tu Agente. Incluye la página canónica del Skill y el manifiesto.
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.Tu Agente debe seguir mostrando su plan y solicitar cualquier confirmación exigida por la política de seguridad.
Usa estos enlaces cuando un agente de IA, crawler o script necesite contexto limpio en vez de leer la página completa.
Usando "lava-news-heat". Show a sample seven-day company attention summary.
Resultado esperado:
Usando "lava-news-heat". Show a sample concept ranking summary.
Resultado esperado:
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.
Comparte el informe de evaluación versionado, la insignia neutral, la tarjeta insertable y las citas. Skillstore presenta evidencias sin decidir si este Skill es seguro.
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.
Autor
dustinliang666-blipLicencia
MIT
Revisión de Skillstore
r1
Aviso de versión
El autor no declaró una versión.
Repositorio
https://github.com/dustinliang666-blip/lava-mcp/tree/f9369732c3956024666c80835b72dc7d22df5a43/Ref.
4699d5d8d8b53ee8ddbe0a18430bcdf40abcc835
Actualidad del mantenimiento
28/10/2026
Uso
0 descargas · 0 vistas
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