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 ai-productgit 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/ai-product)<a href="https://agentmods.dev/skills/jeandiable/obsidian-claude/ai-product"><img src="https://agentmods.dev/badge/skills/jeandiable/obsidian-claude/ai-product/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/ai-product"><img src="https://agentmods.dev/badge/skills/jeandiable/obsidian-claude/ai-product.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 | $0.00031 | $0.01359 |
| Opus 5.5 | $0.00012 | $0.00544 |
| Sonnet 5.5 | $0.00006 | $0.00272 |
| Haiku 4.5 | $0.00003 | $0.00136 |
Grade A, and why
ai-product 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 2mo 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 — 152 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AI Product Discovery
Fetch, deduplicate, and rank AI product launches from multiple sources.
Vault Path
/Library/Mobile Documents/iCloudmd~obsidian/Documents/My_note
Sources
| Source | Method | Notes |
|---|---|---|
| Product Hunt | WebFetch https://www.producthunt.com/feed + DuckDuckGo search "site:producthunt.com AI product launch today" |
Filter for AI-related |
| Hacker News | WebFetch https://hn.algolia.com/api/v1/search?tags=show_hn&numericFilters=created_at_i>TIMESTAMP |
Show HN posts, 24h window. Replace TIMESTAMP with Unix timestamp for 24h ago |
| GitHub Trending | WebFetch https://mshibanami.github.io/GitHubTrendingRSS/daily/python.xml + DuckDuckGo search "github trending AI" |
Python repos |
| Techmeme | WebFetch https://techmeme.com/river |
Product announcements |
| DuckDuckGo search "site:reddit.com r/artificial AI product new" | Supplementary |
Workflow
-
Check cache: Look for
50_Clippings/AI/产品发布/YYYY-MM/YYYY-MM-DD-摘要.md. If exists with today's date, return cached. -
Fetch sources: Use WebFetch on each URL. For sources without RSS, use DuckDuckGo MCP search + fetch_content. Extract product name, URL, description, and engagement metrics (votes/points/stars).
-
Filter: Keep only AI-related products (keywords: AI, ML, LLM, GPT, Claude, automation, agent, model, neural, transformer, diffusion).
-
Deduplicate: Same product across sources = merge. Keep best description, combine metrics, track all sources.
-
Rank by:
- AI relevance
- Engagement (normalize: PH votes/500, HN points/100, GH stars/1000)
- Content potential (tutorial-friendly, review-worthy, open source bonus)
- Recency and novelty
-
Generate digest: Use the template below. Sections:
- 精选推荐 (3-5) with content angles
- LLM与AI模型
- 开发者工具
- 生产力与自动化
- 开源亮点
-
Save files using Obsidian CLI (
obsidian create):50_Clippings/AI/产品发布/YYYY-MM/YYYY-MM-DD-摘要.md50_Clippings/AI/产品发布/YYYY-MM/原始数据/YYYY-MM-DD_ProductHunt-Raw.md50_Clippings/AI/产品发布/YYYY-MM/原始数据/YYYY-MM-DD_HackerNews-Raw.md50_Clippings/AI/产品发布/YYYY-MM/原始数据/YYYY-MM-DD_GitHub-Raw.md
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.
- 2mo ago First seen · 152 lines · 31 tokens per session scan A 2a9eaf4c1c65
ai-product is a skill published in the GitHub repository JeanDiable/obsidian-claude (2 stars, last pushed 8mo ago), licensed MIT. It adds 31 tokens to every session and 1,359 once invoked, about $0.0001 per session on Opus 5.5. 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.
ai-product compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| ai-productJeanDiable/obsidian-claude | Skill | 2 | 8mo ago | MIT | A | 31 | Claude Code |
| imagegenopenai/codex | Skill | 134k | today | Apache-2.0 | A | 113 | Codex |
| playwright-climicrosoft/playwright | Skill | 99k | today | Apache-2.0 | A | 19 | Claude Code |
| local-ai-agentsmicrosoft/ai-agents-for-beginners | Skill | 79k | today | MIT | A | 200 | Claude Code, Codex |
| systematic-debuggingobra/superpowers | Skill | 314k | 3d ago | MIT | A | 21 | Claude Code |
| next-cache-components-adoptionvercel/next.js | Skill | 143k | yesterday | MIT | A | 95 | Claude Code |
| next-partial-prefetching-adoptionvercel/next.js | Skill | 143k | yesterday | MIT | A | 103 | Claude Code |