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Skills topic-research

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/`.

install
source · Clone the upstream repo
git clone https://github.com/openclaw/skills
Claude Code · Install into ~/.claude/skills/
T=$(mktemp -d) && git clone --depth=1 https://github.com/openclaw/skills "$T" && mkdir -p ~/.claude/skills && cp -r "$T/skills/abigale-cyber/topic-research" ~/.claude/skills/clawdbot-skills-topic-research && rm -rf "$T"
manifest: skills/abigale-cyber/topic-research/SKILL.md
source content

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