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 agentmods add skills/ibigqiang/feedgrab/feedgrab-batchnpx skills add iBigQiang/feedgrab --skill feedgrab-batchgit clone --depth 1 https://github.com/iBigQiang/feedgrabWrote 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/ibigqiang/feedgrab/feedgrab-batch)<a href="https://agentmods.dev/skills/ibigqiang/feedgrab/feedgrab-batch"><img src="https://agentmods.dev/badge/skills/ibigqiang/feedgrab/feedgrab-batch.svg" alt="Measured on agentmods" 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 | $0.00076 | $0.01918 |
| Opus 5 | $0.00038 | $0.00959 |
| Sonnet 5 | $0.00015 | $0.00384 |
| Haiku 4.5 | $0.00008 | $0.00192 |
Grade A, and why
feedgrab-batch 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 yesterday.
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 — 204 lines — stays where its author put it; the contents beside it link to each section on GitHub.
feedgrab-batch — Batch Content Grabber
Bulk fetch content from any platform — bookmarks, user timelines, keyword search, album pages, wiki trees.
Trigger
Activate when user mentions batch/bulk operations:
/feedgrab-batch <command> <args>- "Grab all my bookmarks"
- "批量抓取这个用户的推文"
- "搜索关键词 AI Agent"
- "抓取这个公众号的所有文章"
- "下载这个飞书知识库"
Prerequisites
- feedgrab installed (
which feedgrab) - Platform-specific cookies/API keys configured (see each command below)
If not ready, suggest /feedgrab-setup.
Command Reference
X/Twitter
Bookmarks
# Requires: X_BOOKMARKS_ENABLED=true + feedgrab login twitter (primary session only)
feedgrab https://x.com/i/history # All bookmarks (current X URL)
feedgrab https://x.com/i/history/bookmarks/2015311287715340624 # Specific folder
feedgrab https://x.com/i/bookmarks # Legacy URL, still accepted
User Tweets
# Requires: X_USER_TWEETS_ENABLED=true + feedgrab login twitter
feedgrab https://x.com/username # All tweets
X_USER_TWEETS_SINCE=2026-01-01 feedgrab https://x.com/username # Since date
# Auto browser search supplement when >800 tweets
List Tweets
# Requires: X_LIST_TWEETS_ENABLED=true + feedgrab login twitter
feedgrab https://x.com/i/lists/LIST_ID # Last 1 day
X_LIST_TWEETS_DAYS=7 feedgrab https://x.com/i/lists/LIST_ID # Last 7 days
X_LIST_TWEETS_SUMMARY=true feedgrab https://x.com/i/lists/LIST_ID # + summary table
Keyword Search (x-so)
feedgrab x-so "AI Agent" # Search tweets
feedgrab x-so "AI Agent" --days 7 # Last 7 days
feedgrab x-so "AI Agent" --min-faves 100 # Min 100 likes
feedgrab x-so WorkBuddy --lang zh+zxx --sort all # Chinese tweets + Article cards, merged Latest/Top
feedgrab x-so "claude,cursor,copilot" --merge # Multi-keyword merged table
feedgrab x-so "AI Agent" --raw # Raw query syntax
Output: Markdown table (sorted by views) + CSV at output/X/search/
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.
- yesterday Changed · +1 lines 6023f9a12eb5
- 5d ago First seen · 203 lines · 76 tokens per session scan A a897d1f9dbe5
feedgrab-batch is a skill published in the GitHub repository iBigQiang/feedgrab (606 stars, last pushed 4d ago), licensed MIT. It adds 76 tokens to every session and 1,918 once invoked, about $0.0004 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 2026-08-30.
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