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hlzd-market-report

hlzd-market-report

B2B 工业品海外市场情报报告生成 —— 9 节结构 HTML 自包含报告(cover / TOC / signals / platforms / comparison / actions / methodology / sources)+ Markdown 简化版。从 hlzd-b2b-research 输出或原始 web 信号自动组装。Use when 用户说'出报告'、'海外调研报告'、'市场情报'、'跨境选品报告'、'做份 deliverable'、'跨境市场扫描 HTML'、'generate B2B market report'、'market intelligence brief'。

Independent GitHub snapshot · Automated classification · Original documentation governs

Skill-Dokumentation

GitHub

name: hlzd-market-report description: "B2B 工业品海外市场情报报告生成 —— 9 节结构 HTML 自包含报告(cover / TOC / signals / platforms / comparison / actions / methodology / sources)+ Markdown 简化版。从 hlzd-b2b-research 输出或原始 web 信号自动组装。Use when 用户说'出报告'、'海外调研报告'、'市场情报'、'跨境选品报告'、'做份 deliverable'、'跨境市场扫描 HTML'、'generate B2B market report'、'market intelligence brief'。" license: MIT metadata: author: HLZD (海联智达 / 海良数科) version: 0.1.0 industry: cross-border-b2b category: report-generation triggered_by: - 出报告 - 海外调研报告 - 市场情报 - 跨境选品报告 - 跨境市场扫描 - HTML 报告 - B2B market report - market intelligence brief - generate report - deliverable

HLZD 市场情报报告

把"调研出来的信号"组装成 9 节自包含 HTML 报告,便于发给客户、董事会议或朋友圈。


When to use

调用本 Skill 当用户:

  • 跑完 hlzd-b2b-research 拿到 JSON,想打包成可视报告
  • 跑完 hlzd-buyer-finder 拿到买家名单,想附市场分析
  • 要给客户/老板看"我做了什么"的市场扫描
  • 想在 5 分钟内交付一份视觉 + 数据 都达标的报告

不要调用本 Skill 当:

  • 用户只想要一份纯文本摘要 —— 用 hlzd-b2b-research 的 Markdown 输出即可
  • 用户要做实时仪表盘 —— 这是静态报告(v0.1)

How this skill is invoked

# 全自动:topic + 关键词 → 一键 HTML + Markdown
py scripts/pipeline.py --topic "OCTG casing export to UAE" \
                        --keywords "OCTG casing" "API 5CT" "Aramco tender" \
                        --output-html report.html --output-md report.md

# 复用 hlzd-b2b-research 的 JSON
py scripts/pipeline.py --topic "auto" \
                        --from-research b2b-research-output.json \
                        --output-html report.html

9-节报告结构

┌── Cover ────────────────────────┐
│  ★ Headline (L1: 56-72px)         │
│  Tagline (L2: 16-18px)            │
│  4 KPI cards                      │
│  3-step action plan (L1 action)    │
│  Meta line (L3: 13px)              │
└────────────────────────────────┘
       ↓
TOC  (9 anchored links)
       ↓
1. Solution Overview
   - Recap (16-18px)
   - 5-row conclusion table
       ↓
2. 3 Core Signals
   - User pain quote (blockquote)
   - Root cause
   - Market implication
   - Source chips
       ↓
3. Platform Deep Dive (×4-5 platforms)
   - Stat chip
   - 5 findings each (with inline source link)
       ↓
4. Strategic Comparison Table
   - 10 dimensions × 3 vendors
       ↓
5. 3-Step Action Plan
   - Green card with options / risk / execution
       ↓
6. Methodology & Limitations
   - 5-step process / 5-dim signal judgement / 7-limitations
   - Yellow callout box
       ↓
7. Sources (grouped by category)
   - Sources grid
       ↓
Footer (HLZD brand + license)

Output schema (input 数据契约)

{
  "$schema": "hlzd/market-report/v1",
  "meta": { "topic": str, "audience": str, "window_days": int, "language": str },
  "cover": {
    "headline": str, "tagline": str,
    "kpis": [ {"label": str, "value": str, "unit": str?}, ... ],
    "three_step_plan": [ {"step": str, "action": str}, ... ]
  },
  "toc": [ {"id": str, "title": str}, ... ],
  "solution_overview": {
    "recap": str,
    "conclusion_table": [ {"metric": str, "finding": str, "implication": str}, ... ]
  },
  "three_signals": {
    "signals": [
      { "title": str, "user_pain_quote": str, "root_cause": str,
        "market_implication": str, "sources": [ {"name": str, "url": str}, ... ] }
    ]
  },
  "platform_deep_dive": {
    "platforms": [
      { "name": str, "stat": str,
        "findings": [ {"headline": str, "body": str, "source_name": str, "source_url": str}, ... ] }
    ]
  },
  "strategic_comparison": {
    "vendors": [ { "name": str, "attr_1": str, ... }, ... ],
    "attributes": [str, ...]
  },
  "action_plan": {
    "actions": [ {"title": str, "options": [str, ...], "risk": str, "execution": str}, ... ]
  },
  "methodology": {
    "five_step": [str, ...], "five_dim": [str, ...], "seven_limitations": [str, ...]
  },
  "footer_sources": {
    "sources": [ {"name": str, "url": str, "category": str}, ... ]
  }
}

Voice Contract (LAW 7 条)

继承自 b2b-overseas-market-report spec,落地为可执行检查:

LAW含义实施位置
1Body 开头 = "What I learned:"lib.check_law_1
2永远用 - 不用 em-dash / en-dashlib.normalize_dashes 自动替换
3引用必须 [name](url) inline linklib.md_link
4无 trailing Sources: block(footer 替代)lib.check_law_4
5每个 claim 必须有 URL 或 engagement signallib.validate_voice_contract
6"best X 2026" 按信号质量排heuristic,由 agent 做
7不假设用户是某个品牌lib.validate_voice_contract (brand_assumption)

输出前 validate_voice_contract() 跑一遍,violations 列表可由 pipeline 选 warn 或 block。


Integration with hlzd-b2b-research

# 跑完 b2b-research → 出 Markdown
py ../hlzd-b2b-research/scripts/run_research.py \
    --product "OCTG casing" --markets "UAE Saudi" \
    --output-json b2b-output.json

py scripts/pipeline.py --topic "auto" --from-research b2b-output.json \
    --output-html report.html --output-md report.md

from_b2b_research() adapter 自动把 b2b-research 的 trade_data / trends / buyers 转成 report schema:

  • 每个 market = 一个 signal
  • trade_data → platforms
  • HS code + 中国份额 → comparison data

Sample outputs

规模HTMLMarkdown
Standard (auto)~14 KB~4 KB
With data (full)~16 KB~5 KB

CSS 内嵌(自包含),无外部字体 / CDN 依赖。Print-friendly:自动翻转为高对比黑白版。


Anti-pattern / Limitations

限制处置
Brave API 需要 HLZD_BRAVE_API_KEYfallback 到 ddgs;都没有则手动输入信号
pip install ddgs 是 v0.1 唯一可选外部依赖需要网络爬取能力
报告不含 LLM 调用 — signals 是 heuristic 提炼上层 Agent 可接 LLM 增强 from_b2b_research 提炼 3 core signals
Voice Contract 检查是 advisory — 不阻断上层 Agent 可硬 fail 在 violation > 0
多人多语言一次性渲染:v0.1 仅 en 模板二期加 zh / es / ar 多语言模板

Versioning

版本说明
0.1.0首版:9 节 HTML + 8 节 Markdown + 从 hlzd-b2b-research 接入

升级轨迹见仓库根 VERSIONS.md。


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