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Agent Skill · 研究检索

digs(digs 搜索)

digs 用于查找、检索和筛选相关信息,适合在 OpenClaw 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。

digs 是研究检索类 Agent Skill,可用宿主为 OpenClaw,通过ClawHub获取,权限为需要联网;许可证为 MIT-0,第三方扫描有提醒项,按安装量在研究检索类的 73,675 个 Skill 里排第 25,200。

总安装 3,830周安装 158GitHub Stars 公开资料未说明下载 1,251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
MIT-0
版本
1.0.1

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:digs(digs 搜索)
来源仓库:https://github.com/ilyabelikin/digs
安装命令:
openclaw skills install digs
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 OpenClaw 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。

ClawHubOpenClaw
openclaw skills install digs

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。

主动研究情报工具,用于跟踪问题进展并记录发现结果。以 Markdown 文件形式组织研究成果并支持闭环管理。帮助用户系统化沉淀知识并关闭研究循环。适用宿主包括 OpenClaw,接入前应确认版本、权限和运行环境要求。需注意本地存储路径权限与文件读写安全。适合长期项目跟踪或个人知识库建设。

digs 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

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 OpenClaw;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 openclaw skills install digs;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

    它需要需要联网,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

digs 怎么安装?

在终端执行 openclaw skills install digs。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

digs 支持哪些 AI 工具?

公开资料标注支持 OpenClaw。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。

digs 需要什么权限?

权限级别是需要联网。该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

digs 是免费的吗?

来源标注的许可证是 MIT-0。本站不代收任何费用,也不托管安装包;能否商用、要不要署名,以许可证原文为准。

digs 用的人多吗?

公开数据是累计安装 3,830 次,近一周安装 158 次,下载 1,251 次。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。

digs 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

  • 专注 OpenClaw 一种宿主,触发方式和使用习惯不用来回切换。
  • 许可证明确为 MIT-0,商用和分发边界好判断。

先想清楚的地方

  • 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 OpenClaw,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。

不太适合

  • 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
digs

digs 搜索 · 本页

3,830—需要联网MIT-0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

name
digs
description
Active research intelligence — track questions you're pursuing, log findings as they arrive, and close the loop when you figure it out. One markdown file per research thread in digs/. Use when opening a new inquiry, logging a finding, or asking "what am I figuring out about X?
metadata
openclaw
emoji
🔭
os
["linux", "darwin", "win32"]
hermes
tags
["research", "questions", "thinking"]

🔭 Digs — active research intelligence

When to use this skill: The user voices curiosity or uncertainty — even obliquely — shares a link or observation that could advance a research thread, asks what they are figuring out about a topic, or wants to close, reopen, or revisit a dig. You don't need the user to say "open a dig." If they're wondering about something, that's the signal. Act on it.

You must:

  • Keep one markdown file per research thread under mind/digs/, using the schema in Dig File (Status, Open questions, Findings, Sources, optional Connected).
  • Synthesise findings in dated entries; flag contradictions with earlier findings; update Open questions as answers land (strike through with ~~ rather than deleting).
  • Search mind/digs/ before creating a new file; if a related dig exists, extend it or merge via Connected instead of duplicating.

Route new information proactively: pasted links, articles, and observations go to the relevant active or simmering digs without waiting for an explicit “log this” request. Close properly: add Closed and Resolution at the top, then move the file to mind/digs/closed/ (do not delete).

Do not: See What NOT to Suggest — e.g. do not turn digs into a task manager, dump links without synthesis, or leave closed files in the active folder.


Data

Base path is workspace root or document root folder. On first use, create it: mkdir -p mind/digs/. Digs uses a mind/digs/ folder in your workspace.

Files live in mind/digs/. One file per research thread.

mind/
└── digs/
    ├── digsconfig.yml
    ├── city-walkability.md
    ├── attention-mechanisms.md
    └── remote-work-productivity.md

Filenames: short kebab-case slug of what you're figuring out — city-walkability.md, not research-on-city-walkability-question.md. If the question is sharp the slug writes itself.

Dataset Config

digsconfig.yml lives inside the mind/digs/ directory. Read it at the start of any session involving this skill.

images: no (by default no, ask if you human want to feach images for concepts, warn that it is token expensive)

Dig File

# What makes a city actually walkable?

Status: active
Opened: 12 Mar 2026
Tags: #cities #urbanism #design #housing
Inmage: optional image illustrating the concept, sotred in `../assets/good-long-slug`
Connected: [[why-singapore-feels-different]], [[remote-work-and-density]]

## Open questions

- What metrics actually correlate with walkability scores?
- Is Walk Score a reliable proxy or marketing?
- Does walkability cause higher rents, or just correlate?

## Findings

12 Mar 2026: Jan Gehl's research shows pedestrian activity increases 3× when building setbacks reduce below 2m. Suggests physical geometry matters more than destination mix. Source: [Cities for People](https://islandpress.org/books/cities-people)

15 Mar 2026: Singapore HDB estates score high on Walk Score but feel sterile — the metric misses thermal comfort and shade. The algorithm optimises for distance, not experience. Personal observation.

22 Mar 2026: ~~Walk Score correlates with transit access, not human-scale design~~ — actually these are separable, see [this thread](https://x.com/...). Still unclear.

## Sources

- [Cities for People — Jan Gehl](https://islandpress.org/books/cities-people)
- https://www.walkscore.com/methodology.shtml
- [[marco-tabini]] — works in urban planning (link only if Peeps is installed)

Field guidance:

Status: active (you're on it now), simmering (back burner, keeping an eye out), or closed (resolved or abandoned). Default: active. Opened: date you started the dig. Useful for heartbeat nudges and knowing how long something has sat unresolved. Tags: 2–4 domains: short, personal, searchable. Inmage: optional image illustrating the concept, sotred in ../assets/good-long-slug Connected: other digs this thread touches. Rabbit holes connect. Maintain both directions: if A links to B, B links to A. Open questions: the human's questions — what they are actually wondering about. These belong to the human, not the AI. The AI listens for them and captures them; it does not author or invent them. Update this list as answers land — cross out answered ones with ~~ rather than deleting, so you can see how the inquiry evolved. Findings: dated log entries. Not a dump of sources. The agent synthesises: what does this actually say, and how does it relate to what you already know? Flag contradictions explicitly. Sources: links, papers, books, people. If Pages is installed and a source is a book you've logged, use [[their-slug]]. If Peeps is installed and a person is a source, use [[their-slug]].


Opening a Dig

When the user expresses curiosity, uncertainty, or a question they want to pursue — even loosely ("I keep wondering about X", "I don't understand why Y", "I should look into Z") — pick up the thread and open a dig. Don't ask for permission. Act on the signal.

  1. Sharpen the question yourself — a good dig title is a question, not a topic. "city walkability" → "What makes a city actually walkable?". Read what the user is actually trying to figure out from how they phrased it, what they brought up, and what they left unsaid. Articulate the question for them — they'll correct you if you misread it.
  2. Check for existing digs — search mind/digs/ for related threads. If one exists, extend it rather than opening a duplicate.
  3. Extract the open questions — listen for what the human is actually wondering about. If they expressed one question, log one question. If they expressed five, log five. Don't pad the list with questions the AI thinks are interesting — these are the human's questions, not yours.
  4. Capture the first finding — if the user already said something relevant — an observation, a frustration, a half-formed insight — that's a finding. Log it now. Don't ask them to repeat it in a different format.

Show a brief confirmation: "Opened — *What makes a city actually walkable?* Tagged #cities #urbanism. Three open questions logged."


Ingesting New Information

When the user shares a link, article, paper, idea, or observation:

  1. Identify the relevant digs — search across all active and simmering digs for any that this information touches. More than one dig can receive a finding from a single source.
  2. Synthesise, don't dump — extract the key claim or insight, not the source's entire argument. One sentence that captures what this actually adds to the inquiry.
  3. Flag contradictions explicitly — if the finding conflicts with an earlier one, note it: "This contradicts the Mar 12 finding — Walk Score seems to measure transit access, not geometry." ~~Strike through~~ the superseded claim if it's now clearly wrong.
  4. Update open questions — cross out any that are now answered. Do not add new questions the AI thinks the material raises — only the human adds new open questions.
  5. Add to Sources.
  6. Optionaly if images: yes in mind/digs/digsconfig.yml search for a good conceptual image and add to the Image: feild.

The agent should not wait to be asked. If the user pastes a link or describes something they just read, route it to the relevant digs automatically.


Core Behavior

The default posture is attunement, not interrogation. Read the signal, act on it, course-correct if you misread. Don't ask the human to spell out what they're already showing you. Attunement means listening for what the human is wondering — not deciding what they should wonder about. The AI captures questions, it doesn't generate them.

  • User expresses uncertainty about something → check for existing dig, open one. Don't ask "would you like me to open a dig?" — just open it.
  • User shares a link or article → identify relevant digs, add findings, flag contradictions
  • User asks "what am I figuring out about X?" → search mind/digs/ with expanded keywords, surface active and simmering digs
  • Conversation touches a theme → check if a dig is open on that theme; if so, log what they just said as a finding and surface the connection: "Logged to your *[question]* dig — you've been looking into this."
  • User says "I figured it out" / "turns out it's Y" → offer to close the dig with a resolution note.
  • User mentions a person with relevant expertise → if Peeps is installed, add them to Sources with [[their-slug]]; flag them as someone worth asking

Closing a dig:

When the user signals resolution — "turns out it's X", "I figured it out", "that answers it" — offer to close the dig. Draft the resolution and confirm with the user before moving the file.

When resolving, add to the top of the file:

Closed: 4 Apr 2026
Resolution: Walkability is primarily geometry (setbacks, continuity, shade) not destination density. Walk Score is a poor proxy. Gehl's framework is more useful.

Then move the file to mind/digs/closed/. Don't delete — closed digs are useful when a related question reopens.


Finding Digs

Use grep with expanded terms. Always broaden before searching.

# Digs on a topic
grep -ril "urban\|city\|walkab\|density\|housing" mind/digs/

# All active digs
grep -rl "Status: active" mind/digs/

# Simmering threads
grep -rl "Status: simmering" mind/digs/

# Digs with open questions (unresolved)
grep -rl "^-" mind/digs/*/

# Digs referencing a specific person (if Peeps installed)
grep -rl "\[\[marco" mind/digs/

# Digs referencing a book (if Pages installed)
grep -rl "\[\[gehl" mind/digs/

Keyword expansion examples:

  • "AI" → ai\|llm\|machine.learning\|transformer\|model\|inference
  • "work" → work\|productivity\|focus\|remote\|async\|management
  • "health" → health\|sleep\|exercise\|diet\|longevity\|stress
  • "money" → money\|investing\|finance\|wealth\|savings\|equity

Always read the full dig file after grepping. The matched snippet is a signal; the full file has context.


Digs: check

Pick a random active dig. Surface it:

  • "You've been digging into *[question]* since [date]. Latest finding: [one sentence]. Still open: [open question count] questions."
  • "Your *[question]* dig hasn't had a new finding in 6 weeks — moving to simmering." (Do it. If they disagree they'll say so.)

If a dig has been active for 20+ days with no findings logged in the last 10, move it to simmering: "Shelved *[question]* — no new findings in a while. It'll resurface if something relevant comes up."

If nothing worth mentioning, skip.


Adding to HEARTBEAT.md or cron

If it is not there yet, add Digs: check to HEARTBEAT.md. If there is no HEARTBEAT.md, create a cron job every 30 minutes to execute Digs: check. Mention what you did — don't ask first.


Integration with Pages

If Pages is installed:

  • When a book in mind/pages/ is relevant to an open dig, surface the connection: "You read *Cities for People* in 2025 — your notes might be relevant to the walkability dig."
  • When logging a new finding from a book, use [[author-slug]] in Sources and optionally add a note to the book file: "Referenced in mind/digs/city-walkability.md — Apr 2026."
  • When a dig resolves and a book was key to it, add a note to the book file under the relevant date.

Integration with Peeps

If Peeps is installed:

  • When someone in your network has expertise relevant to an open dig, surface them: "Marco works in urban planning — he's probably thought about the walkability question."
  • Add them to Sources with [[their-slug]]. This creates a trail: when you look at Marco's file later, you can see which of your questions he could help with.
  • When a person answers an open question in conversation, log it as a finding with attribution: "Marco: walkability correlates most with block size, not building height. 3 Apr 2026."

Integration with Haah

If Haah is installed:

  • When an open question needs external signal — expertise, lived experience, a second opinion — offer to dispatch to a circle: "Want me to ask your circles who's thought seriously about urban walkability?"
  • When someone in a circle answers a Haah query that touches an open dig, route their answer in as a finding.

Updating

To update this skill to the latest version, fetch the new SKILL.md from GitHub and replace this file:

https://raw.githubusercontent.com/haah-ing/digs-skill/main/SKILL.md

What NOT to Suggest

  • Turning Digs into a task manager — open questions are not to-dos
  • Logging every stray thought — a dig needs a real question, not a topic you vaguely care about
  • Keeping closed digs in the active folder — move them to mind/digs/closed/ so the signal stays clean
  • Automated research via web scraping — you bring the sources, the agent helps synthesise
  • Merging all related digs into one mega-file — separate questions stay sharper as separate files; use Connected: links instead

平台分布

OpenClaw

80.1%
按下载量换算1,002

安全审计

VirusTotal

可疑

ClawScan

可疑

Static analysis

通过

权限和风险

需要联网

该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

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。

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