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 kangarooking/x-skills --skill x-collectgit clone --depth 1 https://github.com/kangarooking/x-skillsWrote 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/kangarooking/x-skills/x-collect)<a href="https://agentmods.dev/skills/kangarooking/x-skills/x-collect"><img src="https://agentmods.dev/badge/skills/kangarooking/x-skills/x-collect/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/kangarooking/x-skills/x-collect"><img src="https://agentmods.dev/badge/skills/kangarooking/x-skills/x-collect.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 | $0.00070 | $0.01376 |
| Opus 5 | $0.00035 | $0.00688 |
| Sonnet 5 | $0.00014 | $0.00275 |
| Haiku 4.5 | $0.00007 | $0.00138 |
Grade A, and why
x-collect 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 10d 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 — 197 lines — stays where its author put it; the contents beside it link to each section on GitHub.
X Collect
Collect trending topics and research materials for X content creation using a systematic 4-round web search strategy.
Prerequisites
- WebSearch tool available
- Internet connection
Optional State (ContextStore)
If available, leverage user preference state to improve search quality:
- State dir:
~/.claude/skills/x-create/state/ - Positive samples:
liked_topics.json(preferred topics/entities/sources) - Negative samples:
rejected_topics.json(avoid low-value/repetitive topics)
If state files don't exist, proceed normally.
Workflow
Input
User provides:
- Topic (required): The subject to research (e.g., "AI Agent最新进展", "Claude 4 发布")
- Language (optional): Output language, defaults to Chinese (zh-CN)
4-Round Search Strategy
Simulate human research thinking process with progressive depth.
Query expansion rules (lightweight):
- Start with user
topic - Add 2-5 query variants based on:
- User profile (domains/persona if known)
- liked_topics.json high-frequency keywords/entities (if available)
- Keep ~20% queries as exploration (cross-domain / adjacent keywords) to avoid information bubble
Dedup & clustering (at the end of each round):
- Merge near-duplicate URLs/titles
- Group materials into topic clusters (rough tags are fine)
Round 1: Official Sources (权威信息)
Search: "{topic} 官方文档"
Search: "{topic} GitHub"
Search: "{topic} official announcement"
Goal: Get authoritative first-hand information
Round 2: Technical Analysis (技术解析)
Search: "{topic} 详细介绍"
Search: "{topic} 教程 tutorial"
Search: "{topic} how it works"
Goal: Understand technical details and mechanisms
Round 3: Comparison & Reviews (对比评测)
Search: "{topic} vs {competitor}"
Search: "{topic} 评测 review"
Search: "{topic} pros cons"
Goal: Get different perspectives and comparisons
Round 4: Supplementary Verification (补充验证)
# Analyze gaps from previous rounds
missing_info = analyze_gaps(previous_results)
Search: "{missing_info}"
Search: "{topic} 最新 latest 2024 2025"
Goal: Fill information gaps and get latest updates
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.
- 10d ago First seen · 197 lines · 70 tokens per session scan A 3f83c893a797
x-collect is a skill published in the GitHub repository kangarooking/x-skills (325 stars, last pushed 6mo ago), licensed Apache-2.0. It adds 70 tokens to every session and 1,376 once invoked, about $0.0003 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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