Token导航 LogoToken导航

Agent Skill · 待分类

temporal-awareness(时间意识)

temporal-awareness 用于处理 GitHub 仓库、Issue、Pull Request 和代码协作信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要围绕仓库状态、代码变更或协作事项进行整理时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

temporal-awareness 是待分类类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为只读;许可证信息还不明确,第三方扫描有提醒项,按安装量在待分类类的 11,209 个 Skill 里排第 5,119。

总安装 612周安装 26GitHub Stars 13下载 214核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
unknown

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:temporal-awareness(时间意识)
来源仓库:https://github.com/jpcaparas/skills
仓库路径:skills/temporal-awareness
安装命令:
npx skills add https://github.com/jpcaparas/skills --skill temporal-awareness
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/jpcaparas/skills --skill temporal-awareness

这个 Skill 是做什么的

这个 Skill 的分类还没最终确定,用法以来源仓库的说明为准。

temporal-awareness 用于处理 GitHub 仓库、Issue、Pull Request 和代码协作信息,适合在 Codex、Claude、Cursor、Gemini CLI 中围绕仓库状态、代码变更或协作事项进行整理时使用。适用于时间敏感型任务、事件驱动开发和实时系统监控场景。

可识别时间相关逻辑、调度策略和异步操作流程。安装命令:npx skills add https://github.com/jpcaparas/skills --skill temporal-awareness。使用前需确认权限范围、维护状态及是否触发联网或文件读写操作。

来源仓库内路径:skills/temporal-awareness

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 Codex、Claude、Cursor、Gemini CLI;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 npx skills add https://github.com/jpcaparas/skills --skill temporal-awareness;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它标注为只读,先用只读任务试一次,确认行为符合预期再扩大使用范围。

常见问题

6 条

temporal-awareness 怎么安装?

在终端执行 npx skills add https://github.com/jpcaparas/skills --skill temporal-awareness。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

temporal-awareness 支持哪些 AI 工具?

公开资料标注支持 Codex、Claude、Cursor、Gemini CLI。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

temporal-awareness 需要什么权限?

权限级别是只读。该 Skill 主要提供规则、说明或参考内容,本身偏只读;真正读写文件、联网或执行命令仍取决于宿主 Agent 的任务。

temporal-awareness 是免费的吗?

公开资料没有标注明确许可证,收费和商用限制都无法确认。正式使用前请到来源仓库核对授权说明。

temporal-awareness 用的人多吗?

公开数据是累计安装 612 次,近一周安装 26 次,下载 214 次,GitHub 13 星。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

temporal-awareness 安全吗?

第三方扫描有提醒项,说明存在需要人工确认的行为。安装前请打开源码看清它读了什么、联网到哪里。

值得选的地方和要先想清楚的地方

值得选的地方

  • 同时适配 4 种工具,换客户端不用重新找替代品。
  • 标注为只读权限,试用阶段不容易误改本地文件。

先想清楚的地方

  • 许可证没有明确标注,能不能商用、能不能再分发都不确定。
  • 第三方扫描存在提醒项或未通过项,需要人工逐条确认。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 Codex,想直接扩展它能力的人。
  • 需要处理待分类类任务、又不想每次都手写提示词的人。
  • 只想先试试效果、不希望它改动本地文件的人。

不太适合

  • 需要明确授权才能用到公司项目里的场景。
  • 需要厂商级技术支持和 SLA 的生产系统。

待分类类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
infsh-cli

infsh CLI · Codex、Claude

4,374,576382权限未标注未明确未收录
ai-video-generation

AI 视频生成 · Codex、Claude

4,313,376382调用外部服务未明确有提醒
lark-openapi-explorer

云雀 OpenAPI 浏览器 · Codex、Claude

2,064,1209,011需要联网未明确有提醒
lark-workflow-standup-report

Lark 工作流程站立报告 · Codex、Claude

2,041,6328,978需要联网未明确通过
use-my-browser

使用我的浏览器 · Codex、Claude

1,848,49140操作浏览器未明确未通过
temporal-awareness

时间意识 · 本页

61213只读未明确有提醒

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

temporal-awareness

Ground the session in the real clock before answering anything that could have changed.

Verified locally on April 9, 2026 in Pacific/Auckland (NZST, UTC+12). The motivating failure mode is real: OpenAI's official Help Center now documents GPT-5.3 and GPT-5.4 in ChatGPT, while stale assistants still default to GPT-4o-era wording from older memory.

Decision Tree

What is the time-sensitive failure mode?

  • Need a clean session anchor before answering

- Run python3 scripts/capture_temporal_context.py --format markdown - Read references/bootstrap.md

  • Need to decide whether a prompt can be answered from stable knowledge or needs live verification

- Run python3 scripts/recency_guard.py --prompt "..." --format markdown - Read references/recency-triage.md

  • Need patterns for latest, today, yesterday, tomorrow, timezone math, or source selection

- Read references/verification-patterns.md

  • Need refresh rules for long-running sessions, day rollovers, or recurring work

- Read references/long-horizon.md

  • Need to debug stale assumptions, outdated model names, or relative-date mistakes

- Read references/gotchas.md

Quick Reference

TaskCommand or fileWhy
Capture local and UTC time contextpython3 scripts/capture_temporal_context.py --format markdownLoad the real clock into the session before answering
Compare the current moment across zonespython3 scripts/capture_temporal_context.py --format markdown --extra-zone America/New_York --extra-zone Europe/LondonAvoid silent timezone drift
Classify whether a prompt needs live verificationpython3 scripts/recency_guard.py --prompt "What is the latest OpenAI model for coding?" --format markdownSeparate stable questions from volatile ones
Run the deterministic probe suitepython3 scripts/probe_temporal_awareness.py --format prettyVerify the skill still behaves as designed
Learn the startup workflowreferences/bootstrap.mdSession-load order and exact commands
Handle relative dates and volatile factsreferences/verification-patterns.mdAbsolute-date conversion and source selection

Reading Guide

If the user says...Read
"Before you answer, what date is it here and what timezone are we using?"references/bootstrap.md
"Do I need to browse for this or is it stable?"references/recency-triage.md
"What does latest mean here?"references/verification-patterns.md
"This session has been running for hours, should we refresh the date context?"references/long-horizon.md
"Why are agents still mentioning GPT-4o / old CEOs / stale prices?"references/gotchas.md

Operational Rules

  1. Run scripts/capture_temporal_context.py before answering any prompt that uses relative time language or depends on the current date, time, or timezone.
  2. Run scripts/recency_guard.py on prompts containing latest, current, today, yesterday, tomorrow, recent, as of, or volatile domains such as models, prices, laws, schedules, weather, executives, or live events.
  3. Treat the system clock as authoritative for local date and time, but treat external current facts as untrusted until verified against live sources.
  4. Convert relative dates into absolute dates before answering whenever there is even a small chance the user is thinking in a different timezone.
  5. Refresh the temporal anchor when the session crosses midnight, spans multiple hours, changes timezone context, or revisits rolling external data.

Verified Behaviors

  1. scripts/capture_temporal_context.py emits local and UTC timestamps, timezone name candidates, UTC offset, locale, platform, and optional extra-zone snapshots.
  2. scripts/recency_guard.py detects relative-date language and volatile domains, and distinguishes stable historical prompts from current-state prompts.
  3. scripts/probe_temporal_awareness.py runs deterministic checks across smoke, edge, negative, and disclosure-style scenarios.
  4. The skill explicitly treats model families and product versions as volatile; this prevents stale answers like defaulting to GPT-4o when the official docs have moved on.
  5. Long-running sessions get explicit refresh rules instead of assuming the first temporal anchor stays valid forever.

Gotchas

  1. Do not confuse clock grounding with live verification: the system clock can tell you what day it is locally, but it cannot tell you today's stock price or the current CEO.
  2. Relative dates are timezone-dependent: today, yesterday, and tomorrow are wrong if you silently assume UTC while the user is thinking locally.
  3. Historical facts are not the same as current-state facts: Who won the 2024 election? is usually stable; Who is president now? is not.
  4. Model names drift faster than agents admit: treat model families, versions, limits, and availability as volatile unless you just verified them.
  5. Long sessions go stale: if work spans a day boundary or a DST change, rerun the capture step and restate the new absolute date.

Helper Scripts

  • scripts/capture_temporal_context.py prints a session-ready time anchor in JSON, text, or Markdown.
  • scripts/recency_guard.py classifies a prompt as stable, system-clock-sensitive, or live-verification-required.
  • scripts/probe_temporal_awareness.py runs deterministic regression checks across the core heuristics.
  • scripts/validate.py validates structure, references, eval coverage, and Python syntax.
  • scripts/test_skill.py validates the packaging and runs the temporal probe suite.

平台分布

Codex

36.07%
按下载量换算77

Claude

30.11%
按下载量换算64

Cursor

16.68%
按下载量换算36

Gemini CLI

10.04%
按下载量换算21

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

可疑

权限和风险

只读

该 Skill 主要提供规则、说明或参考内容,本身偏只读;真正读写文件、联网或执行命令仍取决于宿主 Agent 的任务。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。来源安全扫描存在提醒或未通过项,安装前请自行复核。目前只有一个公开来源,建议同时核对源仓库。

继续浏览同类 Skills