hotspot-article

hotspot-article is a skill for Claude Code from ChanningLua/prax-agent. It costs 39 tokens per session (5,548 once invoked), scanned A, original, MIT.

A research and writing workflow for in-depth technology articles. It selects topics, gathers evidence from multiple sources, tests claims, connects technology to business needs, and checks the finished article.

In plain words
What is it for?
Use it to investigate a current event, business problem, or lasting technical decision and turn it into a researched article. It can produce topic briefs, source records, outlines, drafts, and fact checks.
Why use it?
It replaces an unstructured request to write a long article with defined research, fact-checking, and review steps. It also sets different standards for news analysis, decision frameworks, and hands-on reports.

Skill for Claude Code

Written for Claude Code: allowed-tools in frontmatter.

Good fit Use it to investigate a current event, business problem, or lasting technical decision and turn it into a researched article. It can produce topic briefs, source records, outlines, drafts, and fact checks.

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Install with agentmods
npx agentmods add skills/channinglua/prax-agent/hotspot-article
Install

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.

Any agent
npx skills add ChanningLua/prax-agent --skill hotspot-article
Clone the repo
git clone --depth 1 https://github.com/ChanningLua/prax-agent

Made for: Claude Code.

Wrote 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.

agentmods badge for hotspot-article

README.md
[![agentmods](https://agentmods.dev/badge/skills/channinglua/prax-agent/hotspot-article/github.svg)](https://agentmods.dev/skills/channinglua/prax-agent/hotspot-article)
Your own site
<a href="https://agentmods.dev/skills/channinglua/prax-agent/hotspot-article"><img src="https://agentmods.dev/badge/skills/channinglua/prax-agent/hotspot-article/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.

agentmods 80×15 button for hotspot-article

Your own site · 80×15
<a href="https://agentmods.dev/skills/channinglua/prax-agent/hotspot-article"><img src="https://agentmods.dev/badge/skills/channinglua/prax-agent/hotspot-article.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 39 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 5,548 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00039 $0.05548
Opus 5 $0.00019 $0.02774
Sonnet 5 $0.00008 $0.01110
Haiku 4.5 $0.00004 $0.00555

Measured 2d ago against content hash b074c3759947, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-14, from the pricing page.

Security

Grade A, and why

hotspot-article 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 2d 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.

src/prax/skills/hotspot-article/SKILL.md · 422 lines

How it starts

The opening of the file, as written. The whole thing — 422 lines — stays where its author put it; the contents beside it link to each section on GitHub.

热点深度文章 Pipeline

这不是“一次提示词写长文”,而是一条有证据链和退出门槛的编辑流水线:

三轨机会池 → 需求优先评分 → 技术到业务桥接 → 多源研究 → 多视角提纲 → 实测 → 成稿 → 事实/技术/文风审校 → 质量门

对标腾讯云“内容精选”时,先读 docs/recipes/tencent-selected-benchmark.md,再按内容类型选质量档,不能用一个固定篇幅处理所有文章:

  • selected-analysis:重大事件或行业变化,6,000–12,000 有效字符;
  • selected-framework:架构、组织或决策框架,5,500–11,000 有效字符;
  • selected-hands-on:产品实测或项目实战,4,500–9,000 有效字符。

三类都控制在 5–9 个 H2。重量来自攻击链、分类框架、真实输入输出、失败修复、架构图和明确取舍,不来自拆出更多章节。selected-sharp 只用于技术短稿,不计入腾讯云精选批次;selected 保留为兼容旧稿。

机器分只衡量可审计的下限,不能把 8.6/10 直接解释为审美或洞察得分。最终发布仍需人工主编确认。

触发条件

  • “追一下今天的 AI 热点,写成深度文章”
  • “从客户项目和业务难题里找一个值得写的选题”
  • “对标精选文章,做一篇 8–9 分的长文”
  • “运行 hotspot-article”

如果用户没有给主题,同时扫描近期大事件、真实需求和常青决策三条线。默认周内容组合为:时事 30%、需求/解决方案 50%、常青框架 20%。选题先补齐业务场景,再按当前组合缺口选择;热度很高但说不清“谁在什么情况下要做什么决定”的内容,只进简报,不写精选文章。

把选题与评分写入 brief.md,不中断执行等待确认;如果涉及政治、医疗、金融、法律或未成年人等高风险主题,则停在选题报告,等待用户确认。

文件约定

ROOT=.prax/vault/hotspot-articles/<YYYY-MM-DD>/<topic-slug>

$ROOT/
├── brief.md
├── topic-candidates.json
├── opportunity-report.json
├── business-bridge.json
├── demand-brief.md
├── research-notes.md
├── source-index.json
├── outline.md
├── evidence.json
├── evidence/
├── draft.md
├── fact-check.json
├── fact-check.md
├── editorial-review.md
├── quality-report.json
└── publish-ready.md       # 只有全部门槛通过后才创建

新文件使用 Write;修改已有文件使用 Edit。保留中间稿和失败报告,不覆盖研究证据。

Step 0:读取项目配置

可选配置 .prax/article.yaml

audience: 中文开发者与技术决策者
topics: [AI Agent, LLM, RAG, 开源工具]
exclude: [纯融资传闻, 无原始出处的爆料]
lookback_hours: 48
candidate_limit: 20
tone: 克制、清晰、证据优先
target_mix:
  event: 0.30
  demand: 0.50
  evergreen: 0.20

没有配置就使用以上默认值。当前日期和时区必须写入 brief.md

Step 1:构建三轨机会池

每个候选标注一个 track

A. 时事线 event

  • 当天 .prax/vault/ai-news-hub/<DATE>/
  • 先运行 python3 -m prax.article_integrations probe,把可用和缺失的适配器写入 brief.md
  • TRENDRADAR_OUTPUT 存在时,用 python3 -m prax.article_integrations ingest-trendradar 归一化其 Markdown、JSON 或 SQLite 输出;
  • AutoCLI 可用时,通过 collect-autocli 抓登录态平台;扩展或登录态失败只跳过该源;
  • 官方博客、GitHub Trending、Hacker News、行业媒体;
  • 正文优先使用 Crawl4AI;未安装时适配器会遵守 robots.txt 并退回公开 HTTP 抓取。

Read the full file on GitHub · 422 lines

Changes

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.

  1. 2d ago First seen · 422 lines · 39 tokens per session scan A b074c3759947

Subscribe to this mod's changes

hotspot-article is a skill published in the GitHub repository ChanningLua/prax-agent (273 stars, last pushed 2d ago), licensed MIT. It adds 39 tokens to every session and 5,548 once invoked, about $0.0002 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 2026-09-12.

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