Token导航 LogoToken导航TokenDH.com
研究检索敏感数据clawhub未标认证来源可访问clear审计提醒

moltsheetmoltsheet 命令行

Agent Skill

moltsheet 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。

总安装

71,411

周安装

2,861

GitHub Stars

1

下载量

23,117
OpenClaw

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

MIT-0

最后核验

2026-05-01

来源状态

来源可访问

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:moltsheet(moltsheet 命令行)
来源仓库:https://github.com/youssefbm2008/moltsheet
安装命令:
openclaw skills install moltsheet
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 moltsheet

简介

moltsheet 用于查找、检索和筛选相关信息。

  • 适合在 OpenClaw 中根据关键词、任务场景或来源线索快速定位候选结果时使用。
  • 通过 clawhub 安装,提供电子表格样式数据管理 CLI 工具。
  • 安装前需确认权限范围、维护状态及是否触发文件读写或 JSON 输出。
  • 注意该技能优先使用 CLI 而非 HTTP,需验证数据格式兼容性。

SKILL.md

name
moltsheet
description
Use the Moltsheet CLI to manage spreadsheet-style data for AI workflows. Prefer the CLI over raw HTTP. Authenticate once, prefer --json, and use files or stdin for structured payloads.
allowed-tools
Bash(moltsheet *), Bash(npx moltsheet@latest *), Bash(npm run cli -- *), Bash(curl *)

Moltsheet

Moltsheet is a spreadsheet API for AI agents with a CLI designed to be easier and safer for agents than handwritten HTTP requests.

If you need to create sheets, inspect data, import rows, update cells, or share sheets with another agent, use the CLI first.

Default Agent Procedure

When handling Moltsheet as an agent, follow this order:

  1. Confirm the CLI is available: moltsheet --version
  2. If it is not installed, use npx moltsheet@latest ... or install it globally
  3. Authenticate once with moltsheet auth login
  4. Prefer --json whenever another tool, script, or agent will read the output
  5. Use sheet list and sheet get before writing, so you understand the target schema
  6. Use stdin or JSON files for structured inputs instead of hand-escaped inline JSON
  7. Use raw HTTP only if the CLI cannot be run

Install

Preferred global install:

npm install -g moltsheet

One-off usage without installing:

npx moltsheet@latest auth status

If you are working inside the Moltsheet repository itself, you can also run the local build:

npm --prefix cli install
npm run build:cli
npm run cli -- auth status

Authentication

Authenticate once:

moltsheet auth login

Or pass the API key directly:

moltsheet auth login --api-key YOUR_API_KEY

Check current auth state:

moltsheet auth status --json

Clear stored auth:

moltsheet auth logout

Credential resolution order:

  1. --api-key
  2. MOLTSHEET_API_KEY
  3. Stored local credential from auth login

Storage behavior:

  • Preferred: OS credential storage through keytar
  • Windows: Credential Manager
  • macOS: Keychain
  • Linux: Secret Service or libsecret
  • Fallback: local config file if secure storage is unavailable

Base URL defaults to production:

https://www.moltsheet.com

Override it when working against another environment:

moltsheet sheet list --base-url http://localhost:3000 --json

Commands Agents Should Reach For First

Register an agent:

moltsheet agent register --display-name "Research Bot" --slug research.bot --json

List sheets:

moltsheet sheet list --json

Inspect one sheet:

moltsheet sheet get SHEET_ID --json

Read a filtered subset of a sheet:

moltsheet sheet get SHEET_ID --columns "Company,Qualified" --filter "Qualified:eq:true" --json

Update a sheet:

moltsheet sheet update SHEET_ID --name "Leads v2" --json

Update a schema and allow destructive changes:

cat schema.json | moltsheet sheet update SHEET_ID --schema-stdin --confirm-data-loss --json

Delete a sheet:

moltsheet sheet delete SHEET_ID --json

Create a sheet from schema stdin:

cat schema.json | moltsheet sheet create "Leads" --schema-stdin --json

Create empty rows:

moltsheet row add SHEET_ID --count 10 --json

Add one row from stdin:

cat row.json | moltsheet row add SHEET_ID --data-stdin --json

Import multiple rows:

cat rows.json | moltsheet row import SHEET_ID --stdin --json

Import multiple rows through the dedicated sheet import route:

cat rows.json | moltsheet sheet import SHEET_ID --stdin --json

List rows:

moltsheet row list SHEET_ID --json

Delete rows by ID:

cat row-ids.json | moltsheet row delete SHEET_ID --stdin --json

Delete one row by index:

moltsheet row delete-index SHEET_ID 0 --json

Update cells:

cat updates.json | moltsheet cell update SHEET_ID --stdin --json

Add columns:

cat columns.json | moltsheet column add SHEET_ID --stdin --json

Delete columns by index list:

cat indices.json | moltsheet column delete SHEET_ID --stdin --json

Delete one column by index:

moltsheet column delete-index SHEET_ID 1 --json

Rename a column:

moltsheet column rename SHEET_ID 0 --name "Company Name" --json

Share a sheet:

moltsheet share add SHEET_ID --slug analyst.bot --access write --json

List collaborators:

moltsheet share list SHEET_ID --json

Remove a collaborator:

moltsheet share remove SHEET_ID --slug analyst.bot --json

Structured Input Patterns

Prefer files or stdin for anything shaped like JSON.

Sheet schema example:

[
  { "name": "Company", "type": "string" },
  { "name": "Website", "type": "url" },
  { "name": "Qualified", "type": "boolean" }
]

Single row example:

{
  "Company": "Moltsheet",
  "Website": "https://www.moltsheet.com",
  "Qualified": true
}

Multiple rows example:

[
  {
    "Company": "Moltsheet",
    "Website": "https://www.moltsheet.com",
    "Qualified": true
  },
  {
    "Company": "Example",
    "Website": "https://example.com",
    "Qualified": false
  }
]

Column definitions example:

[
  { "name": "Company", "type": "string" },
  { "name": "Website", "type": "url" }
]

Row ID list example:

[
  "123e4567-e89b-12d3-a456-426614174000",
  "123e4567-e89b-12d3-a456-426614174001"
]

Column index list example:

[
  0,
  2
]

Cell updates example:

[
  {
    "rowId": "123e4567-e89b-12d3-a456-426614174000",
    "column": "Qualified",
    "value": true
  }
]

How Agents Should Handle the CLI

Use this operating style:

  • Prefer --json for machine-readable output
  • Read before writing: use sheet list or sheet get before mutating data
  • Trust schema types and let the CLI or API validation guide corrections
  • Prefer stdin or files over complex shell escaping
  • Reuse stored auth rather than passing secrets repeatedly
  • Use collaborator slugs for sharing, never API keys
  • Use sheet import for the dedicated sheet import route and row import for rows-endpoint bulk insert behavior
  • If a command fails, inspect the error payload before retrying

Recommended write workflow:

  1. Run moltsheet auth status --json
  2. Run moltsheet sheet list --json
  3. Run moltsheet sheet get SHEET_ID --json
  4. Confirm column names and expected types
  5. Prepare JSON input
  6. Run the write command with --json
  7. Re-run sheet get or sheet list to verify the result

Output and Validation

Supported schema types:

  • string
  • number
  • boolean
  • date
  • url

Validation behavior:

  • Empty values are allowed
  • Invalid types return an error
  • Bulk row imports reject the full request if any row is invalid
  • Cell updates require valid rowId values and valid column names

Important note:

  • Returned row values are stored and returned as strings, even when validated against number, boolean, date, or url schema types

Collaboration Model

  • Sheets are shared by agent slug
  • Access levels are read and write
  • API keys are never exposed through collaboration commands
  • Collaboration responses expose only slug and displayName

Troubleshooting

If moltsheet is not installed:

npx moltsheet@latest sheet list --json

If you suspect auth problems:

moltsheet auth status --json

If you need to bypass stored auth for one call:

moltsheet sheet list --api-key YOUR_API_KEY --json

If you are working inside the repo and the published CLI is unavailable:

npm run cli -- sheet list --json

HTTP Fallback

Use raw HTTP only if you cannot run the CLI.

Base URL:

https://www.moltsheet.com/api/v1

Example list sheets request:

curl https://www.moltsheet.com/api/v1/sheets \
  -H "Authorization: Bearer YOUR_API_KEY"

Example create sheet request:

curl -X POST https://www.moltsheet.com/api/v1/sheets \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "name": "Leads",
    "description": "Outbound leads",
    "schema": [
      { "name": "Company", "type": "string" },
      { "name": "Website", "type": "url" }
    ]
  }'

Short Rules For Agents

  • Prefer the CLI over curl
  • Prefer --json
  • Prefer files or stdin for structured payloads
  • Read the sheet schema before writing
  • Verify writes by reading the sheet again
  • Use npx moltsheet@latest when the binary is not installed

适合场景

01

OpenClaw 用户查找和安装 Skill 时

02

用户想查找某类 Agent Skill 时

03

需要根据任务场景推荐可安装能力包时

04

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

补充不同宿主或平台的使用分布数据

能力 5

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

OpenClaw

89.06%
按下载量换算20,588

安全审计

VirusTotal

可疑

ClawScan

通过

Static analysis

通过

权限和风险

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 warning/failed 结果,不能写成本站确认安全。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

继续浏览同类 Skills