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convex-logs凸原木

Agent Skill

convex-logs 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。

总安装

539

周安装

22

GitHub Stars

405

下载量

172
CodexClaudeCursorGemini CLI

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

unknown

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:convex-logs(凸原木)
来源仓库:https://github.com/openagentsinc/openagents
仓库路径:skills/convex-logs
安装命令:
npx skills add https://github.com/openagentsinc/openagents --skill convex-logs
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/openagentsinc/openagents --skill convex-logs

简介

用于检查 Convex 部署中的函数执行日志和错误信息。

  • 适用于调试 unauthorized 错误、验证失败或超时等问题排查。
  • 可查看查询、突变和动作的执行详情及耗时统计。
  • 使用前应确认目标部署环境和所需权限级别。
  • convex-logs 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

SKILL.md

Check Convex logs

Use this skill when you need to inspect what is happening in a Convex deployment: failed actions, validation errors, 401 unauthorized from external APIs, or which functions ran and how long they took.

When to use this skill

  • User reports an error from Convex (e.g. "unauthorized", "ArgumentValidationError", action timeout).
  • You need to confirm which Convex deployment (dev vs prod) is being used.
  • You need to see recent function executions (queries, mutations, actions) and their success/failure.
  • You are debugging Convex env vars (e.g. OA_INTERNAL_KEY, PUBLIC_API_URL) and want to correlate with API responses in logs.

Prerequisites

  • The project must use Convex and have npx convex (or convex CLI) available.
  • Run Convex commands from the app directory that contains the convex/ folder (e.g. apps/web in a monorepo).
  • You must be logged in and have the correct Convex project linked (npx convex dashboard to verify).

Default deployment: dev vs prod

Important: By default, convex logs and convex env target the dev deployment. For production issues (e.g. openagents.com), you must pass --prod.

  • Dev (default): npx convex logs streams from the project's dev deployment.
  • Prod: npx convex logs --prod streams from the project's production deployment.

Same for env vars: npx convex env list shows dev; npx convex env list --prod shows production.

Commands

Stream or fetch logs

# From the app that has convex/ (e.g. apps/web)
cd apps/web

# Stream logs (default: dev). Use Ctrl+C to stop.
npx convex logs

# Stream production logs
npx convex logs --prod

# Show last N log entries then exit (no streaming). Good for quick checks.
npx convex logs --prod --history 30

# Include successful executions (default is failures only in some contexts)
npx convex logs --prod --history 25 --success

Log command options

OptionMeaning
--prodUse the production deployment (required for prod debugging).
--history [n]Show the last n log entries; then exit instead of streaming.
--successInclude successful function runs in the output.
--jsonlOutput raw log events as JSONL.
--deployment-name <name>Target a specific deployment (e.g. dev:effervescent-anteater-82).
--env-file <path>Use env file for CONVEX_DEPLOYMENT or similar.

Inspect environment variables

Convex actions do not read .env.local. They only see variables set in the Convex deployment (Dashboard or CLI). To see what the deployment has:

# List env vars on dev (default)
npx convex env list

# List env vars on production
npx convex env list --prod

# Get a single variable (e.g. confirm OA_INTERNAL_KEY is set; value is hidden in output)
npx convex env get OA_INTERNAL_KEY --prod

Use this to confirm that keys and URLs (e.g. OA_INTERNAL_KEY, PUBLIC_API_URL) are set on the deployment that's actually serving the app.

Typical workflow

  1. Reproduce the issue (e.g. open Hatchery, trigger an action that returns 401).
  2. Fetch recent prod logs (if the app is production): cd apps/web npx convex logs --prod --history 30 --success
  3. Find the failing function in the output (e.g. [CONVEX A(openclawApi:getRuntimeStatus)] [ERROR]... 401 'unauthorized').
  4. Confirm which deployment is used: logs show the deployment name (e.g. successful-mongoose-647 for prod).
  5. Check env vars for that deployment: npx convex env list --prod (or without --prod for dev).
  6. Fix env in Convex (Dashboard or npx convex env set...) or fix the calling code; redeploy if needed.

Example log output

Watching logs for production deployment successful-mongoose-647...
2/4/2026, 12:39:06 PM [CONVEX A(openclawApi:getInstance)] Function executed in 434 ms
2/4/2026, 12:39:06 PM [CONVEX A(openclawApi:getRuntimeStatus)] [ERROR] '[openclawApi getRuntimeStatus] API error response:' 401 'unauthorized'
2/4/2026, 12:39:06 PM [CONVEX A(openclawApi:getRuntimeStatus)] Uncaught Error: unauthorized ...

Here, getInstance succeeded but getRuntimeStatus got 401 from the external API—often a mismatch of OA_INTERNAL_KEY between Convex and the API worker.

Troubleshooting

  • "No logs" or wrong deployment: Use --prod when the live app uses the production Convex deployment.
  • 401 from Convex actions calling an API: Set OA_INTERNAL_KEY (and PUBLIC_API_URL if needed) in the same Convex deployment that runs the action (npx convex env set OA_INTERNAL_KEY "..." --prod), and ensure the API worker has the same key (e.g. npx wrangler secret put OA_INTERNAL_KEY in the API app).
  • Timeout when streaming: Use --history N to fetch a finite number of entries and exit instead of streaming.
  • Need a specific deployment: Use --deployment-name <name> (e.g. dev:effervescent-anteater-82) for that deployment's logs.

适合场景

01

用户想查找某类 Agent Skill 时

02

需要根据任务场景推荐可安装能力包时

03

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

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

Codex

35.34%
按下载量换算61

Claude

32.68%
按下载量换算56

Cursor

20.12%
按下载量换算35

Gemini CLI

8.94%
按下载量换算15

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

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。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

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