Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add JeanDiable/obsidian-claude --skill news-researchgit clone --depth 1 https://github.com/JeanDiable/obsidian-claudeWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/jeandiable/obsidian-claude/news-research)<a href="https://agentmods.dev/skills/jeandiable/obsidian-claude/news-research"><img src="https://agentmods.dev/badge/skills/jeandiable/obsidian-claude/news-research/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/jeandiable/obsidian-claude/news-research"><img src="https://agentmods.dev/badge/skills/jeandiable/obsidian-claude/news-research.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00017 | $0.00810 |
| Opus 5 | $0.00009 | $0.00405 |
| Sonnet 5 | $0.00003 | $0.00162 |
| Haiku 4.5 | $0.00002 | $0.00081 |
Grade A, and why
news-research scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 12d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 132 lines — stays where its author put it; the contents beside it link to each section on GitHub.
News Research
Given news headlines, research across domains (politics, economics, finance, tech, AI), find connections, and analyze investment implications.
Vault Path
/Library/Mobile Documents/iCloudmd~obsidian/Documents/My_note
Input
User provides one or more headlines: /news-research <headline1>; <headline2>
Workflow
Step 1: Research Each Headline
For each provided headline:
-
Search for related coverage using DuckDuckGo MCP:
- Direct search for the headline
- Search in specific domains: politics, economics, finance, tech, AI
- Search for analysis and opinion pieces
-
Summarize findings per domain:
- Core facts and developments
- Key highlights and non-obvious insights
- Expert opinions if found
Step 2: Cross-Domain Analysis
-
Identify connections between the news items across domains:
- How does a political event affect technology?
- How does a tech development affect financial markets?
- What second-order effects exist?
-
Search for related developments in adjacent domains that the user may not have considered
Step 3: Investment Analysis
Analyze implications for:
-
Short-term (1-7 days):
- Immediate market reactions
- Sentiment shifts
- Specific sectors/stocks affected
-
Mid-term (1-3 months):
- Industry trend implications
- Regulatory impacts
- Supply chain effects
-
Long-term (6-12+ months):
- Structural changes
- New market opportunities
- Technology adoption curves
Focus on: US stock market (specific sectors/companies) and Bitcoin/crypto.
Step 4: Generate Report
Create 50_Clippings/News_Research_YYYY-MM-DD_<brief-topic>.md:
---
title: "News Research: <Brief Topic>"
created: YYYY-MM-DD
modified: YYYY-MM-DD
tags: [news, research, investment]
description: "Multi-domain analysis of <headlines>"
---
# News Research — YYYY-MM-DD
## Headlines Analyzed
1. Headline 1
2. Headline 2
## Domain Analysis
### 政治 (Politics)
[Relevant findings, impacts]
### 经济 (Economics)
[Relevant findings, impacts]
### 金融 (Finance)
[Relevant findings, impacts]
### 科技 (Technology)
[Relevant findings, impacts]
### AI
[Relevant findings, impacts]
## Cross-Domain Connections
- Connection 1: How X in domain A affects Y in domain B
- Connection 2: ...
## Investment Implications
### 短期影响 (Short-term: 1-7 days)
**US Stocks**: [Analysis with specific sectors/companies]
**BTC/Crypto**: [Analysis]
### 中期影响 (Mid-term: 1-3 months)
**US Stocks**: [Analysis]
**BTC/Crypto**: [Analysis]
### 长期影响 (Long-term: 6-12+ months)
**US Stocks**: [Analysis]
**BTC/Crypto**: [Analysis]
## Sources
- [Source 1](URL)
- [Source 2](URL)
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 12d ago First seen · 132 lines · 17 tokens per session scan A 773688a823bf
news-research is a skill published in the GitHub repository JeanDiable/obsidian-claude (2 stars, last pushed 6mo ago), licensed MIT. It adds 17 tokens to every session and 810 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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