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Agent Skill · 研究检索

help(帮助指南)

help 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。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。

help 是研究检索类 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,第三方扫描已通过,按安装量在研究检索类的 73,675 个 Skill 里排第 51,876。

总安装 570周安装 24GitHub Stars 3,270下载 462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:help(帮助指南)
来源仓库:https://github.com/agenticnotetaking/arscontexta
仓库路径:skills/help
安装命令:
npx skills add https://github.com/agenticnotetaking/arscontexta --skill help
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/agenticnotetaking/arscontexta --skill help

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

动态生成帮助指南,根据 vault 状态决定 compact 或 full 模式展示可用命令。支持按技能名查询详细用法(如 help reduce)或空参数下智能判断模式类型。执行五步流程:收集 vault 状态、解析域词汇、确定模式、动态发现命令、渲染输出。

使用前需确保 notes 文件夹存在且 ops/config.yaml 配置有效。help 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

来源仓库内路径:skills/help

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/agenticnotetaking/arscontexta --skill help;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

help 怎么安装?

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

help 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。

help 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。

help 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。

help 用的人多吗?

公开数据是累计安装 570 次,近一周安装 24 次,下载 462 次,GitHub 3,270 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。

help 安全吗?

第三方扫描结果为通过,但这只覆盖已知的静态检查项,不能替代自己读一遍源码和安装命令。

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。
  • 第三方扫描已通过,常见的高风险行为没有命中。
  • 来源仓库有 3,270 星,维护活跃度相对可查。
  • 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。
  • 需要处理研究检索类任务、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。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
help

帮助指南 · 本页

5703,270只读未明确通过

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

EXECUTE NOW

Target: $ARGUMENTS

Parse immediately:

  • If target contains --compact: force compact mode regardless of vault state
  • If target contains a skill name (e.g., "help reduce" or "help reflect"): show detailed help for that specific skill
  • If target is empty: determine mode from vault state

Execute these steps:

  1. Gather vault state (Step 1)
  2. Resolve domain vocabulary (Step 2)
  3. Determine mode (Step 3)
  4. Discover commands dynamically (Step 4)
  5. Render the appropriate mode (Step 5)

START NOW. Reference below defines each step.


Step 1: Gather Vault State

Determine the notes folder by checking which domain-named directory exists (notes/, reflections/, concepts/, ideas/, decisions/, memories/, or any custom name from derivation-manifest.md). Then gather counts:

  • Note count: .md files in the notes folder, excluding MOCs (files with type: moc in frontmatter)
  • Inbox count: .md files in the inbox folder (inbox/, journal/, encounters/, etc.)
  • Observation count: .md files in ops/observations/ or ops/methodology/
  • Tension count: .md files in ops/tensions/
  • Connection density: count wiki links ([[) across notes folder; sparse if fewer than 2x note count
  • Queue state: pending tasks in ops/queue/queue.yaml or ops/queue/queue.json
  • Health warnings: check latest report in ops/health/ if it exists
  • Tutorial state: check ops/tutorial-state.yaml for incomplete tutorial
  • Session count: estimate from ops/sessions/ file count (indicates usage maturity)
# Quick state gathering
note_count=$(ls -1 {vocabulary.notes}/*.md 2>/dev/null | wc -l | tr -d ' ')
inbox_count=$(ls -1 {vocabulary.inbox}/*.md 2>/dev/null | wc -l | tr -d ' ')
obs_count=$(ls -1 ops/observations/*.md ops/methodology/*.md 2>/dev/null | wc -l | tr -d ' ')
tension_count=$(ls -1 ops/tensions/*.md 2>/dev/null | wc -l | tr -d ' ')

Step 2: Resolve Domain Vocabulary

Read ops/derivation-manifest.md (or fall back to ops/derivation.md Vocabulary Mapping section). Extract domain-native names for: reduce, reflect, reweave, verify, rethink, note, MOC, inbox. If neither file exists, use universal names.

For display, show domain name with universal in parentheses when they differ:

  /{domain:reduce} (reduce)   Extract patterns from journal entries

If domain name equals universal name, show just the name:

  /reduce   Extract insights from source material

Step 3: Determine Mode

ConditionMode
--compact in argumentsCompact
Specific skill name in argumentsSkill detail
Note count < 5Narrative
Note count >= 5Contextual

Step 4: Discover Commands

Scan ${CLAUDE_PLUGIN_ROOT}/skills/ dynamically:

  • Subdirectories containing SKILL.md (e.g., reduce/SKILL.md)

Extract name: and description: from each frontmatter. Do NOT hardcode the command list.

Command categories:

CategoryCommandsWhen to Show
Core/ask, /learn, /next, /helpAlways
Processing/reduce, /reflect, /reweave, /verifyAlways (all skills from day one)
Maintenance/health, /rethink, /rememberAlways
Evolution/architect, /reseed, /add-domain, /upgradeAlways
Meta/tutorial, /graph, /statsAlways

Step 5: Render

NARRATIVE MODE (note count < 5)

This is the first impression. The user is new or nearly new. Explain what the system IS before listing what it DOES.

What narrative mode communicates:

  1. What Ars Contexta is (one sentence)
  2. What THEIR system was built to do (read from ops/derivation.md if available)
  3. What they can do RIGHT NOW (concrete actions, not abstract possibilities)
  4. How the system grows with them
--=={ ars contexta : help }==--

Your knowledge system is ready. It turns thoughts
into a connected graph where every note compounds
the value of every other note.

[If ops/derivation.md exists:]
Your system: [domain description from derivation]

Getting started:

  Tell me a thought, observation, or question.
  I will turn it into a note and show you what
  the system does with it.

  Or try one of these:

  /ask [question]    Ask about [domain] -- I will
                     answer from your graph
  /learn [topic]     Research [topic] and grow
                     your graph with findings
  /tutorial          Walk through the system
                     step by step (5 minutes)

As your graph grows, you will use:
  /reduce [source]   Extract insights from articles,
                     notes, or any raw material
  /reflect           Find connections between notes
  /health            Check your system's health

Your system also learns from experience:
  /remember             Capture when something goes wrong
                        (your system remembers corrections)
  /ask [question]       Ask about [domain] -- answers draw
                        from 249 methodology notes AND your
                        system's own methodology notes

Type /help anytime for guidance.

Manual reference (if manual/ exists): If the vault contains a manual/ directory, add to the narrative output:

  For a deeper guide, read manual/getting-started.md
  or explore the full manual in manual/manual.md.

Key principles for narrative mode:

  • Conversational, not list-like
  • Show the easiest entry point first ("tell me a thought")
  • Group commands by when the user would need them, not alphabetically
  • Reference the user's actual domain when possible
  • If tutorial is incomplete, mention: "You have an unfinished tutorial (step N of 5). Resume with /tutorial"

CONTEXTUAL MODE (note count >= 5)

The user has been working. Show them what is happening NOW and what would be most valuable NEXT.

What contextual mode communicates:

  1. Current system state (brief metrics)
  2. What needs attention right now (state-aware)
  3. Suggested next action (the single most valuable thing)
  4. Commands they might not know yet
  5. Full command reference
--=={ ars contexta : help }==--

Your system: [domain] knowledge graph
  [N] notes, [M] connections, [P] pending tasks

Right now:
  [State-aware observations — pick up to 3 most relevant:]
  Your inbox has [N] items (oldest: [age])
  [N] pending observations -- approaching /rethink threshold
  Pipeline: [N] tasks at [phase] phase
  [N] notes have sparse connections (< 2 links)

Suggested:
  [Single most valuable next action with rationale]

[If user hasn't tried certain commands:]
Commands you might not know:
  /remember    Capture when something goes wrong
               (teaches your system from friction)
  /graph       Explore your knowledge graph visually
  /stats       See vault metrics in shareable format

All commands:
  /ask [question]        Query your knowledge system
  /learn [topic]         Research and grow your graph
  /next                  Next recommended action
  /{reduce} [source]     Extract insights from material
  /{reflect}             Find connections between notes
  /{reweave}             Update older notes
  /verify [note]         Combined quality verification
  /health                Run vault diagnostics
  /{rethink}             Challenge assumptions
  /remember              Capture methodology learning
  /architect             Research-backed evolution advice
  /reseed                Principled restructuring
  /add-domain            Extend with a new domain
  /upgrade               Check for skill improvements
  /tutorial              Interactive walkthrough
  /graph                 Graph exploration
  /stats                 Vault metrics

State-aware suggestion logic:

Pick the FIRST matching condition:

ConditionSuggestion
Inbox has itemsProcess your inbox: /{reduce} [oldest-inbox-item-filename]
Pipeline has pending tasksResume processing: /next
10+ observations or 5+ tensionsReview accumulated evidence: /{rethink}
Health warnings existCheck health: /health
Notes exist, sparse connectionsBuild connections: /{reflect}
User hasn't tried /learnGrow your graph: /learn [topic related to their domain]
Methodology folder has friction notesYour system is learning from friction -- review with /{rethink}
Methodology folder has notes beyond derivation-rationaleYour system has [N] operational learnings -- query them with /ask or browse ops/methodology/
Sessions accumulating without miningMine session learnings: /remember
Healthy vault, no pressureWhat is next: /next

Reference a specific file when possible (e.g., the actual oldest inbox filename, the actual pending task description).

Manual page suggestion (if manual/ exists): Based on the first matching state-aware condition, suggest the relevant manual page:

ConditionManual Page
Inbox has items[[workflows]] (processing pipeline)
Pipeline has pending tasks[[workflows]] (batch processing)
Observations/tensions accumulated[[meta-skills]] (/rethink guide)
Health warnings exist[[troubleshooting]]
Sparse connections[[workflows]] (connection finding)
General orientation needed[[getting-started]]

Add: For details, see manual/{page}.md

"Commands you might not know" logic:

Track which commands the user has likely used by checking for their artifacts:

  • /learn used if ops/sessions/ has learn-related transcripts or inbox has research files
  • /remember used if ops/methodology/ or ops/observations/ has files
  • /graph used if... (no artifact, always suggest if note count > 20)
  • /stats used if... (no artifact, always suggest if note count > 10)

Show up to 3 commands the user probably has not tried. Skip commands they clearly have used.

COMPACT MODE (--compact flag)

Quick reference. No state analysis. No suggestions. Just the commands.

--=={ ars contexta : help --compact }==--

  /ask [question]        Query knowledge system
  /learn [topic]         Research and grow graph
  /next                  Next recommended action
  /{reduce} [source]     Extract insights
  /{reflect}             Find connections
  /{reweave}             Update older notes
  /verify [note]         Quality verification
  /health                Vault diagnostics
  /{rethink}             Challenge assumptions
  /remember              Capture methodology learning
  /architect             Evolution advice
  /reseed                Restructure system
  /add-domain            Add new domain
  /upgrade               Check for improvements
  /tutorial              Interactive walkthrough
  /graph                 Graph exploration
  /stats                 Vault metrics
  /help                  This guide

SKILL DETAIL MODE (help [skill-name])

When the user asks for help with a specific skill (e.g., /help reduce or /help reflect):

  1. Find the skill's SKILL.md file
  2. Read its frontmatter (name, description) and first section
  3. Display a focused guide:
--=={ ars contexta : help /{skill-name} }==--

{Description from frontmatter}

Usage:
  /{skill-name} [arguments]

Examples:
  /{skill-name} inbox/article.md
  /{skill-name} --since 7d

What it does:
  {2-3 sentence summary extracted from the skill's
   philosophy or first methodology section}

Related:
  /{related-skill}    {one-line description}

Special case for /help ask: Expand the "What it does" section to mention both knowledge layers:

What it does:
  Queries the bundled methodology knowledge base (249
  research claims) AND your local methodology notes
  in ops/methodology/. Answers are grounded in
  specific claims and applied to your system's
  configuration.

Extract the pipeline position (what comes before and after this skill) to show workflow context.

Manual cross-reference: If manual/skills.md exists, also check it for additional context about the requested skill. The manual may contain domain-specific examples and workflow context that the SKILL.md frontmatter does not include.


Rendering Rules

  • Max width: 76 characters
  • No ANSI color codes
  • No emoji
  • Monospaced alignment assumed
  • Display short command forms (/reduce), not plugin-qualified forms (/arscontexta:reduce)
  • Domain-native names in curly braces (e.g., /{reduce}) are resolved from derivation-manifest.md
  • When domain name equals universal name, drop the braces

Edge Cases

No ops/derivation-manifest.md: Use universal vocabulary for all command names.

Pre-init invocation: If no vault structure exists at all (no notes folder, no ops/), show a minimal message:

Ars Contexta is not initialized in this directory.
Run /setup to create your knowledge system.

Multiple domains: If ops/derivation-manifest.md lists multiple domains, show commands grouped by domain in contextual mode.

平台分布

Codex

39.09%
按下载量换算181

Claude

27.95%
按下载量换算129

Cursor

18.65%
按下载量换算86

Gemini CLI

8.42%
按下载量换算39

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

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。目前只有一个公开来源,建议同时核对源仓库。

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