refresh

A skill for checking a knowledge base against current online information and updating or flagging pages that may be out of date. It scans wiki pages, records refresh status, and tracks sources and conflicts.

In plain words
What is it for?
Use it to refresh the whole wiki, a named page, or pages with a selected tag, using commands such as /refresh and recording when each page was checked.
Why use it?
It addresses the problem that technical, business, policy, and other facts can become outdated. It helps distinguish pages that are current, updated, stale, conflicting, or failed to refresh.

Skill for Claude CodeCodex

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.

agentmods
npx agentmods add skills/lululu811/init-knowledge-base/refresh
Any agent
npx skills add lululu811/init-knowledge-base --skill refresh
Clone the repo
git clone --depth 1 https://github.com/lululu811/init-knowledge-base

Made for: Claude Code, Codex.

Per session 107 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,219 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
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 $0.00107 $0.02219
Opus 5 $0.00053 $0.01110
Sonnet 5 $0.00021 $0.00444
Haiku 4.5 $0.00011 $0.00222

Measured 3d ago against content hash 1d8e93510b3f, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

refresh 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 3d 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.

_templates/.claude/skills/refresh/SKILL.md · 228 lines

How it starts

The opening of the file, as written. The whole thing — 228 lines — stays where its author put it; the contents beside it link to each section on GitHub.

refresh 技能:联网时效性更新

核心目标

知识库会随时间推移而过时。本技能通过联网搜索,主动验证和更新 wiki/ 中的陈旧内容,确保知识的时效性和准确性。

触发场景

  • 用户输入 /refresh — 全局扫描陈旧页面并联网更新
  • 用户输入 /refresh <页面名> — 更新指定页面
  • 用户输入 /refresh --tag=<标签> — 按标签批量更新
  • 用户说"知识库该更新了"、"检查一下过时内容"、"联网刷新知识库"

状态追踪机制

通过 frontmatter 中的 last_refreshed 字段和 .claude/refresh-state.json 追踪刷新状态:

{
  "version": 1,
  "last_full_scan": "2026-08-15T10:00:00",
  "pages": {
    "wiki/concepts/Transformer.md": {
      "last_refreshed": "2026-08-15T10:30:00",
      "status": "current",
      "changes": ["更新了参数规模数据", "补充了 GPT-5 相关引用"],
      "sources_added": ["https://example.com/new-info"]
    }
  }
}

状态规则

状态 含义
current 联网验证过,内容仍然准确
updated 联网后发现新信息,已更新页面
conflict 联网后发现矛盾信息,已标记冲突
stale 超过刷新周期,待处理
failed 上次刷新失败(网络错误等),需重试

刷新流水线

步骤 1:识别刷新候选

全局扫描模式(/refresh):

  1. 读取 wiki/ 下所有带 frontmatter 的 .md 文件(排除 index.md、log.md)
  2. 检查 last_refreshed 字段(若无此字段,使用 last_updated
  3. 按优先级排序候选页面:
    • 高优先:超过 90 天未刷新 + 主题属于快变领域(AI/技术/商业/政策)
    • 中优先:超过 90 天未刷新 + 主题属于慢变领域(科学/历史/哲学)
    • 低优先:超过 180 天未刷新 + 主题属于稳定领域
    • 跳过:30 天内已刷新且状态为 current
  4. 状态为 draft 的页面也纳入候选(可能有信息缺口可补充)

指定页面模式(/refresh <页面名>): 直接定位目标页面,跳过扫描步骤。

按标签模式(/refresh --tag=<标签>): 扫描带有指定标签的所有页面。

步骤 2:提取搜索关键词

对每个候选页面:

  1. 读取完整内容
  2. 提取页面标题作为核心搜索词
  3. 从 frontmatter 的 tags 提取辅助关键词
  4. 从"一句话定义"或"核心摘要"提取关键概念
  5. 构造搜索查询:
    • 基础查询:{标题} {关键概念} 最新 2025 2026
    • 补充查询:{标题} 更新 变化 新进展
    • 实体查询:{实体名} 最新动态 新闻

步骤 3:联网搜索

  1. 使用搜索工具执行步骤 2 构造的查询
  2. 读取排名前 3-5 的搜索结果
  3. 提取关键事实:
    • 新数据/新数字(市值、参数量、版本号等)
    • 新事件(融资、发布、人事变动等)
    • 新观点/新论文
    • 对已有信息的验证或推翻

步骤 4:对比分析

将搜索结果与现有 wiki 内容逐项对比:

情况 处理方式
新信息补充现有内容 标记为"待追加"
新信息与现有内容矛盾 标记为"待冲突处理"
现有内容被验证仍准确 标记为"已验证"
搜索结果与主题无关或无新信息 标记为"无更新"
发现新实体/概念需创建页面 标记为"待创建"

步骤 5:更新页面

更新类型 A — 追加新信息:

在页面的相应区块追加新内容,并在末尾添加时效性更新标记:

## 时效性更新

> [!info] 联网刷新 — YYYY-MM-DD
> 已通过联网搜索验证并更新本页面内容。

- **追加**:[新信息摘要] — 来源:[URL]
- **更新**:[旧数据] → [新数据] — 来源:[URL]

Read the full file on GitHub · 228 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. 3d ago First seen · 228 lines · 107 tokens per session scan A 1d8e93510b3f

Subscribe to this mod's changes

refresh is a skill published in the GitHub repository lululu811/init-knowledge-base (23 stars, last pushed 18d ago), licensed MIT. It adds 107 tokens to every session and 2,219 once invoked, about $0.0005 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.

Related

Other skills, from other repositories

systematic-debugging

Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.

obra/superpowers · 21 tokens

brainstorming

You MUST use this before any creative work - creating features, building components, adding functionality, or modifying behavior. Explores user intent, requirements and design before implementation.

obra/superpowers · 37 tokens

auto-perf-optimize

Run agent-driven VS Code performance or memory investigations. Use when asked to launch Code OSS, automate a VS Code scenario, run the Chat memory smoke runner, capture renderer heap snapshots, take workflow screenshots, compare run summaries, or drive a repeatable scenario before heap-snapshot analysis.

microsoft/vscode · 62 tokens

chat-perf

Run chat perf benchmarks and memory leak checks against the local dev build or any published VS Code version. Use when investigating chat rendering regressions, validating perf-sensitive changes to chat UI, or checking for memory leaks in the chat response pipeline.

microsoft/vscode · 51 tokens

chat-pet-sprite-creation

Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.

microsoft/vscode · 53 tokens

cpu-profile-analysis

Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…

microsoft/vscode · 71 tokens