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Topic Research

在首轮信息收集之后对选定主题做二轮深度研究：读取含 YAML frontmatter 的 Markdown 请求，调用 Tavily 命令行工具获取结果，再规范化写成研究简报并附写作决策章节；tvly 缺失或未登录时不降级。

abigale-cyber
abigale-cyber
热度 46.24
最近更新 2026-05-11 17:41:04
分类：搜索依赖：代码执行 / 读写文件 / 第三方 API应用场景：研究 / 报告撰写 / 摘要总结

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 topic-research
Metadata
name
topic-research
description
Run a second-hop deep research pass through the Tavily CLI after an initial scan, then normalize the result into a local `research.md` contract. Use when Codex needs cited follow-up research for a chosen topic from `news-collect`, or wants a reusable research report saved into `content-production/inbox/`.

Topic Research

This skill deepens a selected topic after news-collect or any manually chosen theme. It does not replace first-pass collection. The report now also produces a local writing decision layer.

Quick Start

Run the default command:

.venv/bin/python -m skill_runtime.cli run-skill topic-research --input content-production/inbox/20260405-agent-topic-research.md

Prepare Input

Pass a markdown request file with YAML frontmatter.

Supported fields:

  • topic
  • question
  • model: mini / pro / auto
  • source_file: optional path to a prior news-report.md
  • seed_urls: optional list or comma-separated URLs

Example:

---
topic: AI coding agents
question: 这些产品近一周的产品化方向和商业化信号是什么？
model: pro
source_file: content-production/inbox/20260405-ai-news-report.md
seed_urls:
  - https://example.com/a
  - https://example.com/b
---

补充说明：优先输出能转成中文公众号选题判断的结论。

Follow Research Workflow

  1. Validate that tvly is installed and available on PATH.
  2. Combine the request fields into a single research query.
  3. Call tvly research ... --json.
  4. Save the raw JSON and rewrite the result into a normalized markdown research report.
  5. Add a writing-decision section covering whether the topic is worth writing, recommended structure, opening hooks, title directions, and evidence risks.

Write Output

Write the report to:

content-production/inbox/YYYYMMDD-<slug>-research.md

Write the raw JSON to:

content-production/inbox/raw/research/YYYY-MM-DD/<slug>.json

Respect Constraints

  • Only use the repo-local dependency marker skills/tavily-research/ for this integration
  • Do not silently fall back if tvly is missing or not logged in
  • Keep the output contract stable even if Tavily CLI changes its JSON schema

Read Related Files

  • Runtime entry: skill_runtime/engine.py
  • Wrapper runtime: skills/topic-research/runtime.py
  • Vendor dependency marker: skills/tavily-research/
  • Data contract: docs/data-contracts.md