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Agent Skill · 研究检索

confidant(confidant 搜索)

confidant 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。

confidant 是研究检索类 Agent Skill,可用宿主为 OpenClaw,通过ClawHub获取,权限为接触敏感数据;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 1,794。

总安装 76,863周安装 3,268GitHub Stars 1下载 26,928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
1.5.3

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:confidant(confidant 搜索)
来源仓库:https://github.com/ericsantos/confidant
安装命令:
openclaw skills install confidant
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 confidant

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。

AI 代理的安全秘密移交和凭证设置向导,保护敏感信息如 API 密钥。适合在 OpenClaw 中需要根据关键词或任务场景快速定位候选结果时使用。可结合来源仓库和原始 README 核验具体用法,通过 clawhub 安装。安装前建议确认权限范围、维护状态及是否会触发联网或文件读写。

confidant 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 confidant;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

    它需要接触敏感数据,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

confidant 怎么安装?

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

confidant 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。

confidant 需要什么权限?

权限级别是接触敏感数据。该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

confidant 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。

confidant 用的人多吗?

公开数据是累计安装 76,863 次,近一周安装 3,268 次,下载 26,928 次,GitHub 1 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。

confidant 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

  • 需要接触敏感数据,装到常用环境前要先评估影响面。
  • 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

  • 环境里有大量密钥、凭证,不方便给第三方 Skill 读取的人。
  • 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
confidant

confidant 搜索 · 本页

76,8631接触敏感数据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
confidant
description
Secure secret handoff and credential setup wizard for AI agents. Use when you need sensitive information from the user (API keys, passwords, tokens) or need to save credentials to config files. Never ask for secrets via chat — use Confidant instead.
homepage
https://github.com/aiconnect-cloud/confidant
user-invocable
true
disable-model-invocation
false
metadata

Confidant

Receive secrets from humans securely — no chat exposure, no copy-paste, no history leaks.

🚨 CRITICAL FLOW — Read This First

This is a human-in-the-loop process. You CANNOT retrieve the secret yourself.

  1. Run the script → you get a secure URL
  2. SEND the URL to the user in chat ← THIS IS MANDATORY
  3. WAIT for the user to open the URL in their browser and submit the secret
  4. The script handles the rest (receives, saves to disk, confirms)
❌ DO NOT curl/fetch the secret URL yourself — it's a web form for humans
❌ DO NOT skip sharing the URL — the user MUST receive it in chat
❌ DO NOT poll the API to check if the secret arrived — the script does this
❌ DO NOT proceed without confirming the secret was received
✅ Share URL → Wait → Confirm success → Use the secret silently

🔧 Setup (once per environment)

Run this once to install the CLI globally (avoids slow npx calls):

bash {skill}/scripts/setup.sh
{skill} is the absolute path to the directory containing this SKILL.md file. Agents can resolve it at runtime: ``bash SKILL_DIR=$(find "$HOME" -name "SKILL.md" -path "*/confidant/skill*" -exec dirname {} \; 2>/dev/null | head -1) # Then use: bash "$SKILL_DIR/scripts/setup.sh" ``

⚡ Quick Start

You need an API key from the user? One command:

bash {skill}/scripts/request-secret.sh --label "OpenAI API Key" --service openai

The script handles everything:

  • ✅ Starts server if not running (or reuses existing one)
  • ✅ Creates a secure request with web form
  • ✅ Detects existing tunnels (ngrok or localtunnel)
  • ✅ Returns the URL to share with the user
  • ✅ Polls until the secret is submitted
  • ✅ Saves to ~/.config/openai/api_key (chmod 600) and exits

If the user is remote (not on the same network), add --tunnel:

bash {skill}/scripts/request-secret.sh --label "OpenAI API Key" --service openai --tunnel

This starts a localtunnel automatically (no account needed) and returns a public URL.

Output example:

🔐 Secure link created!

URL: https://gentle-pig-42.loca.lt/requests/abc123
  (tunnel: localtunnel | local: http://localhost:3000/requests/abc123)
Save to: ~/.config/openai/api_key

Share the URL above with the user. Secret expires after submission or 24h.

Share the URL → user opens it → submits the secret → script saves to disk → done.

Without --service or --save, the script still polls and prints the secret to stdout (useful for piping or manual inspection).

Scripts

request-secret.sh — Request, receive, and save a secret (recommended)

# Save to ~/.config/<service>/api_key (convention)
bash {skill}/scripts/request-secret.sh --label "SerpAPI Key" --service serpapi

# Save to explicit path
bash {skill}/scripts/request-secret.sh --label "Token" --save ~/.credentials/token.txt

# Save + set env var
bash {skill}/scripts/request-secret.sh --label "API Key" --service openai --env OPENAI_API_KEY

# Just receive (no auto-save)
bash {skill}/scripts/request-secret.sh --label "Password"

# Remote user — start tunnel automatically
bash {skill}/scripts/request-secret.sh --label "Key" --service myapp --tunnel

# JSON output (for automation)
bash {skill}/scripts/request-secret.sh --label "Key" --service myapp --json
FlagDescription
--label <text>Description shown on the web form (required)
--service <name>Auto-save to ~/.config/<name>/api_key
--save <path>Auto-save to explicit file path
--env <varname>Set env var (requires --service or --save)
--tunnelStart localtunnel if no tunnel detected (for remote users)
--port <number>Server port (default: 3000)
--timeout <secs>Max wait for startup (default: 30)
--jsonOutput JSON instead of human-readable text

check-server.sh — Server diagnostics (no side effects)

bash {skill}/scripts/check-server.sh
bash {skill}/scripts/check-server.sh --json

Reports server status, port, PID, and tunnel state (ngrok or localtunnel).

⏱ Long-Running Process — Use tmux

The request-secret.sh script blocks until the secret is submitted (it polls continuously). Most agent runtimes (including OpenClaw's exec tool) impose execution timeouts that will kill the process before the user has time to submit.

Always run Confidant inside a tmux session:

# 1. Start server in tmux
tmux new-session -d -s confidant
tmux send-keys -t confidant "confidant serve --port 3000" Enter

# 2. Create request in a second tmux window
tmux new-window -t confidant -n request
tmux send-keys -t confidant:request "confidant request --label 'API Key' --service openai" Enter

# 3. Share the URL with the user (read from tmux output)
tmux capture-pane -p -t confidant:request -S -30

# 4. After user submits, check the result
tmux capture-pane -p -t confidant:request -S -10
Why not exec? Agent runtimes typically kill processes after 30-60s. Since the script waits for human input (which can take minutes), it gets SIGKILL before completion. tmux keeps the process alive independently.

If your agent platform supports long-running background processes without timeouts, exec with request-secret.sh works fine. But when in doubt, use tmux.

Rules for Agents

  1. NEVER ask users to paste secrets in chat — always use this skill
  2. NEVER reveal received secrets in chat — not even partially
  3. NEVER curl the Confidant API directly — use the scripts
  4. NEVER kill an existing server to start a new one
  5. NEVER try to expose the port directly (public IP, firewall rules, etc.) — use --tunnel instead
  6. ALWAYS share the URL with the user in chat — this is the entire point of the tool
  7. ALWAYS wait for the script to finish — it polls automatically and saves/outputs the secret; do not try to retrieve it yourself
  8. Use --tunnel when the user is remote (not on the same machine/network)
  9. Prefer --service for API keys — cleanest convention
  10. After receiving: confirm success, use the secret silently

Exit Codes (Scripts)

Agents can branch on exit codes for programmatic error handling:

CodeConstantMeaning
0—Success — secret received (saved to disk or printed to stdout)
1MISSING_LABEL--label flag not provided
2MISSING_DEPENDENCYcurl, jq, npm, or confidant not installed
3SERVER_TIMEOUT / SERVER_CRASHServer failed to start or died during startup
4REQUEST_FAILEDAPI returned empty URL — request not created
≠0(from CLI)confidant request --poll failed (expired, not found, etc.)

With --json, all errors include a "code" field for programmatic branching:

{ "error": "...", "code": "MISSING_DEPENDENCY", "hint": "..." }

Example Agent Conversation

This is what the interaction should look like:

User: Can you set up my OpenAI key?
Agent: I'll create a secure link for you to submit your API key safely.
       [runs: request-secret.sh --label "OpenAI API Key" --service openai --tunnel]
Agent: Here's your secure link — open it in your browser and paste your key:
       🔐 https://gentle-pig-42.loca.lt/requests/abc123
       The link expires after you submit or after 24h.
User: Done, I submitted it.
Agent: ✅ Received and saved to ~/.config/openai/api_key. You're all set!

⚠️ Notice: the agent SENDS the URL and WAITS. It does NOT try to access the URL itself.

How It Works

  1. Script starts a Confidant server (or reuses existing one on port 3000)
  2. Creates a request via the API with a unique ID and secure web form
  3. Optionally starts a localtunnel for public access (or detects existing ngrok/localtunnel)
  4. Prints the URL — agent shares it with the user in chat
  5. Delegates polling to confidant request --poll which blocks until the secret is submitted
  6. With --service or --save: secret is saved to disk (chmod 600), then destroyed on server
  7. Without --service/--save: secret is printed to stdout, then destroyed on server

Tunnel Options

ProviderAccount neededHow
localtunnel (default)No--tunnel flag or npx localtunnel --port 3000
ngrokYes (free tier)Auto-detected if running on same port

The script auto-detects both. If neither is running and --tunnel is passed, it starts localtunnel.

Advanced: Direct CLI Usage

For edge cases not covered by the scripts:

# Start server only
confidant serve --port 3000 &

# Start server + create request + poll (single command)
confidant serve-request --label "Key" --service myapp

# Create request on running server
confidant request --label "Key" --service myapp

# Submit a secret (agent-to-agent)
confidant fill "<url>" --secret "<value>"

# Check status of a specific request
confidant get-request <id>

# Retrieve a delivered secret (by secret ID, not request ID)
confidant get <secret-id>
If confidant is not installed globally, run bash {skill}/scripts/setup.sh first, or prefix with npx @aiconnect/confidant.

⚠️ Only use direct CLI if the scripts don't cover your case.

平台分布

OpenClaw

73.58%
按下载量换算19,814

安全审计

VirusTotal

可疑

ClawScan

可疑

Static analysis

未展示

权限和风险

接触敏感数据

该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

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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