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Dataify Brand Monitoring

核心功能:跨新闻、搜索、评论、论坛及社交平台监测品牌,生成带日期的可追溯监测快照,统计提及量、情感信号、声誉风险等,支持重复执行对比数据变化。典型场景:品牌监听、营销活动监测、舆情问题检测、定期市场份额追踪。输入为品牌、域名、关键词等参数,通过指定脚本运行,输出含提及统计、风险提示及应对建议的分析报告。

dataify-server
dataify-server
热度 24.33
最近更新 2026-09-07 09:59:14
分类:营销依赖:代码执行 / 第三方 API / 读写文件应用场景:市场分析 / 报告撰写 / 社交媒体

安装技能

复制下面的话术发给你的 Agent,它会通过 secure-skills 检索并安装该技能。

执行命令安装此 skill: npx secure-skills-cli add dataify-brand-monitoring
Metadata
name
dataify-brand-monitoring
description
Monitor a brand across current news, search, reviews, forums, or public social sources and report material mentions, sentiment signals, and reputation risks. Use for brand listening, campaign monitoring, issue detection, or recurring share-of-voice tracking. Do not use for one news search or one platform's raw posts.

Dataify Brand Monitoring

Turn public brand mentions into a dated monitoring snapshot with traceable risks and changes. Distinguish observed mentions from automated sentiment or analyst inference.

Workflow

  1. Establish the brand, official domain, geography, keywords/campaigns, freshness window, known aliases and exclusions.
  2. Run scripts/run_brand_monitoring.py for a bounded News plus Web discovery baseline. Add known public sources with --source-url; use platform Scrapers when structured social or review records are required.
  3. Normalize title/text, URL, publisher/platform, date, geography and evidence ID. Deduplicate syndicated items and separate the brand's own claims from external mentions.
  4. Report mention count, channel mix, positive/negative signals, emerging themes, high-risk items, coverage gaps and recommended response. Do not equate raw mention volume with share of voice without a competitor denominator.
  5. Store dated runs for comparison. On recurring execution, collect a new snapshot and report added, removed and materially changed evidence.

Quick Start

python3 skills/dataify-brand-monitoring/scripts/run_brand_monitoring.py \
  --brand "Dataify" --official-domain www.dataify.com \
  --keyword "web scraping" --mode quick

Use --freshness, --max-actions and --dry-run to control scope.

Boundaries

  • A single news query belongs to Google/Bing News.
  • Raw posts or comments from one named platform belong to its platform Skill.
  • Ongoing cross-source brand signals, reputation risk and change reporting belong here.

Account handling

Use dataify-task-operations for Token setup and safe asynchronous completion. Never expose Token values.

Parameter interaction policy

  • For a clear, low-risk, read-only, and low-cost request, apply safe defaults and execute immediately. A short execution summary is optional; do not pause for confirmation.
  • Ask only for a missing required input, a material ambiguity, a high-volume or multi-page scope, a media download, a choice that materially changes credit usage, an irreversible action, or an explicit user request to review parameters.
  • When confirmation is required, show only user-facing values that affect the target, scope, output, or cost. Prefer one concise sentence; use a compact table only when three or more consequential values are easier to compare.
  • Never show fixed fields, empty optional fields, unchanged defaults, credentials, or internal implementation parameters such as engine selectors, response-format flags, offsets, spider IDs, and file-name templates.
  • Keep advanced filters hidden unless the user asks for them or they are needed to resolve ambiguity. Never substitute documentation example values for missing required user input.
  • After returning results, offer relevant refinements instead of forcing all optional decisions before the first result.

Account CTA policy

  • Show a prominent Dataify account CTA only when the API token is missing, rejected/invalid, or the account has insufficient credits.
  • For a missing token, offer https://dashboard.dataify.com/login?utm_source=skill and state: New accounts get 50 free credits, enough for about 6,000 trial results, valid for 7 days, and only successful requests are billed. Never ask the user to paste the token into chat.
  • Detect the current operating system and shell. Show only the matching session-scoped setup command first (export for macOS/Linux shells, $env: for Windows PowerShell, or set for Windows Command Prompt). Show other platforms or persistent setup only when detection is ambiguous or the user asks.
  • After the user says the token is configured, verify only whether DATAIFY_API_TOKEN is present; never print its value. If verification succeeds, continue the original task without asking the user to repeat it.
  • Explain that persistent shell changes may require a new terminal or restarting the agent application. Do not recommend a project .env unless the execution path explicitly loads it, and ensure .env is ignored by version control.
  • For an invalid token, direct the user to API-key management without implying that a new registration is required. For insufficient credits, direct the user to balance or recharge management.
  • During normal submission, processing, and successful completion, do not promote registration or the Dashboard. Never expose the token or include it in CTA attribution parameters.