AIGCLIST
基准评分
OpenCode 在 Agent 就绪度与 AI 可见性上的得分 AI 就绪度和 GEO Score 是 VibeLaunch 在提交后生成的平台评估。
决策摘要
Terminal-native developers and engineering teams using CLI workflows who want provider-flexible AI coding assistance without IDE lock-in.
AI-assisted coding in terminal environments with provider flexibility, Plan-mode-driven code reviews, and enterprise data privacy guarantees.
适合
- Terminal-native developers using tmux or CLI workflows
- Teams needing provider-flexible AI coding without vendor lock-in
- Enterprises with strict data residency requirements for local-only processing
注意
- Windows support is still in progress; Unix-like environments are the primary target
- Share feature sends conversation data externally when enabled; review privacy guidance before use
- Windows installation support is still in progress, limiting adoption for Windows-native development teams.
概述
OpenCode 是一款功能强大的开源 AI 编程助手，旨在简化软件开发生命周期。它直接在开发者的终端、IDE 中运行，或作为独立的桌面应用程序使用，解决了在编程环境和 AI 聊天界面之间频繁切换的困扰。该工具作为一个自主或半自主的合作伙伴，能够理解项目上下文、提供改进建议并实时生成代码片段。\n\nOpenCode 的核心亮点之一是其“自带模型”理念。虽然它内置了免费模型供用户入门，但它也无缝集成了超过 75 家 LLM 提供商。这包括 OpenAI (GPT-4)、Anthropic (Claude) 和 Google (Gemini) 等行业领先者，以及为需要极高隐私或离线功能的用户提供的本地模型。它甚至允许用户利用现有的 GitHub Copilot 或 ChatGPT Plus 订阅，确保开发者无需为 AI 智能重复付费。\n\n除了简单的代码生成，OpenCode 专为专业工作流而设计。它具备 LSP（语言服务器协议）集成功能，这意味着它能为正在使用的模型自动加载正确的语言智能……
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评分构成
编辑评分由哪些维度构成，每项附判断依据。 AI 就绪度和 GEO Score 是 VibeLaunch 在提交后生成的平台评估。
Information quality
Documentation covers installation, providers, Plan mode, themes, keybinds, sharing, and enterprise features with clear configuration examples. Missing areas include performance benchmarks, model comparison guidance, and troubleshooting documentation.
Comprehensive docs across multiple sections including providers, Zen, themes, keybinds, share, and enterprise with JSON configuration examples and step-by-step setup instructions.
Ease of use
Terminal-based TUI with JSON configuration is familiar to CLI-native developers but excludes GUI-oriented users. Plan mode adds a deliberate friction step that improves code quality at the cost of speed. Windows support is in progress, creating a barrier for Windows-native teams.
JSON-based config for themes and keybinds; platform-specific defaults for Windows terminals; Plan mode intentionally adds a review step before changes.
Feature depth
Plan mode, multi-provider support, Zen AI provider, conversation sharing, theming, and keybindings are each documented in dedicated sections. Provider support is broad but Snowflake Cortex is limited to Claude and OpenAI families for tool-calling. Enterprise features are outlined but lack implementation depth.
Dedicated docs pages for providers (40+ entries), Zen with per-token pricing table, share with three modes, theme JSON schema, and keybind configuration with platform defaults.
Workflow fit
Fits naturally into terminal-native CLI and tmux workflows. Plan mode introduces a review-before-execute pattern well-suited to teams with code review practices. Excludes developers who prefer IDE integration, and Windows support gap limits cross-platform team adoption.
Terminal TUI architecture; Plan mode recommendation to plan before changes; /connect and /share commands accessible directly from the terminal interface.
Reliability
Data privacy commitment is strong: no code storage, local processing, opt-in sharing only. No uptime SLA, performance benchmarks, error recovery documentation, or production deployment track record is available in the source packet. Community support channels are not documented beyond the share feature's collaboration use case.
Enterprise documentation states no code or context data storage with local-only processing; share feature privacy guidance warns against sharing proprietary code.
Value
Free and open-source core with optional Zen pay-as-you-go pricing listed per million tokens offers transparency for the first-party provider. Enterprise pricing is contact-sales only with no public tiers, making cost evaluation difficult for business teams. Provider flexibility allows cost optimization by choosing cheaper LLM backends.
Zen pricing table with per-1M-token rates; enterprise contact-sales model requiring internal trial first; any-provider architecture allowing cost-conscious provider selection.
评分反映可查证的产品资料，不代表实际使用效果保证。
Agent 就绪度
评估 Agent 能否通过产品的官方信息理解产品，并重建一条有文档依据的工作流程。
Automated agent-readiness assessment of https://opencode.ai/: 12 of 22 checks verified across 6 fetched pages. Machine interfaces are documented (api_reference, cli, sdk, mcp). Absent: llms_txt, quickstart, request_examples, response_examples, version_information, cli_non_interactive.
就绪度维度
| 评估维度 | 得分 |
|---|---|
| 文档质量 | 80 |
| 执行结果可验证性 | 20 |
| 机器接口 | 60 |
| 项目定位清晰度 | 50 |
| 资源可发现性 | 75 |
| 工作流完整度 | 70 |
对 Agent 有帮助的部分
- docs: verified during this run
- sitemap: verified during this run
- agent tooling artifacts: verified during this run
- api reference: verified during this run
- authentication: verified during this run
- error documentation: verified during this run
Agent 受阻的部分
- llms.txt is absent (HTTP probe during this run).
- No quickstart signal matched across 6 fetched pages.
- No request examples signal matched across 6 fetched pages.
- No response examples signal matched across 6 fetched pages.
- No version information signal matched across 6 fetched pages.
- No cli non interactive signal matched across 6 fetched pages (a CLI is documented, but not this property).
| 检查项 | 状态 | 详情 |
|---|---|---|
| 理解产品2/5 已核验 | ||
| 产品文档 | 已核验 | Developer/documentation pages reachable from the entry page (e.g. https://opencode.ai/docs). |
| 快速开始 | 未在本次官方来源链中找到 | |
| API 参考 | 已核验 | Probe matched on https://opencode.ai/changelog: /api (reference|documentation|endpoints?)/. |
| 请求示例 | 未在本次官方来源链中找到 | |
| 响应示例 | 未在本次官方来源链中找到 | |
| 连接接口3/4 已核验 | ||
| SDK | 已核验 | Probe matched on https://opencode.ai/docs: /\bsdk\b|client library|npm package|pip i/. |
| MCP 接口 | 已核验 | Probe matched on https://opencode.ai/docs: /model context protocol|\bmcp\b(?!-)/. |
| Webhooks | 未在本次官方来源链中找到 | |
| 认证文档 | 已核验 | Probe matched on https://opencode.ai/docs: /api key|bearer|oauth|access token|authen/. |
| 执行工作流2/6 已核验 | ||
| 命令行工具 | 已核验 | Probe matched on https://opencode.ai/docs: /\bcli\b|command[- ]line interface|npm (i/. |
| 非交互式命令 | 未在本次官方来源链中找到 | |
| 命令行结构化输出 | 未在本次官方来源链中找到 | |
| 结构化导入与导出 | 未在本次官方来源链中找到 | |
| 成功状态验证 | 未在本次官方来源链中找到 | |
| 智能体工具产物 | 已核验 | Multiple agent tooling artifacts documented: agent instruction files (AGENTS.md / CLAUDE.md / skills) referenced on https://opencode.ai/docs; named slash-command skills (≥2 distinct) documented on https://opencode.ai/docs. |
| 维护与排错3/4 已核验 | ||
| 错误文档 | 已核验 | Probe matched on https://opencode.ai/changelog: /error (codes?|handling|responses?)|4xx|5/. |
| 速率限制 | 已核验 | Probe matched on https://opencode.ai/changelog: /rate limit|429|throttl|requests per (sec/. |
| 版本信息 | 未在本次官方来源链中找到 | |
| 更新日志 | 已核验 | Probe matched on https://opencode.ai/changelog: /changelog|release notes|what'?s new/. |
| 发现与验证2/3 已核验 | ||
| llms.txt | 未在本次官方来源链中找到 | |
| 站点地图 | 已核验 | sitemap.xml reachable and lists site pages. |
| 智能体原生定位 | 已核验 | Agent-native positioning with a concrete operational path: "The docs provide a concrete operational path for agents by instructing to run /init to create an AGENTS.md file, which is a standard agent-native convention.". |
官方证据
审计信息
- 评测时间
- 2026年8月30日
- 评测基准
- agent-readiness-v1
- 读取页面
- 6
- 来源深度
- 1
本审计从一个入口 URL 及其经过验证的官方来源链评估文档所支持的可操作性。AIGCLIST 未注册、登录、购买、执行或测试该产品的运行可靠性。
证据核查
关于该工具的公开声明，每条均标注核验状态与引用来源。
docs已验证7opencode.ai已验证核验于 2026年8月30日
OpenCode supports any LLM provider by configuring their API keys, giving developers freedom to choose models without vendor lock-in.
OpenCode has a Plan mode that disables file modifications and instead suggests how it would implement a feature, with documentation recommending users ask for a plan before code changes.
Windows installation support for OpenCode using Bun is currently in progress.
OpenCode operates as a terminal-based TUI application accessed through the command line rather than as an IDE plugin.
A documentation surface is reachable at https://opencode.ai/docs.
Agent tooling artifacts observed: agent instruction files (AGENTS.md / CLAUDE.md / skills) referenced on https://opencode.ai/docs; named slash-command skills (≥2 distinct) documented on https://opencode.ai/docs.
Agent-native positioning with a concrete operational path: "The docs provide a concrete operational path for agents by instructing to run /init to create an AGENTS.md file, which is a standard agent-native convention.".
https://opencode.ai/docsdocs/enterprise已验证3opencode.ai已验证核验于 2026年7月16日
OpenCode Enterprise does not store user code or context data; all processing happens locally or through direct API calls to the chosen AI provider.
Enterprise pricing follows a contact-sales model after internal team trials.
The optional share feature sends conversation data to the project's hosting infrastructure when users explicitly create public share links.
https://opencode.ai/docs/enterprise/OpenCode | The open source AI coding agent已验证1opencode.ai已验证核验于 2026年8月30日
The entry page was fetched and analyzed for machine-interface signals (title, headings, developer links, keyword probes).
https://opencode.ai/https://opencode.ai/sitemap.xml已验证1opencode.ai已验证核验于 2026年8月30日
sitemap.xml is reachable and lists site pages.
https://opencode.ai/sitemap.xmlOpenCode | Changelog已验证1opencode.ai已验证核验于 2026年8月30日
A documentation surface is reachable at https://opencode.ai/changelog.
https://opencode.ai/changeloghttps://opencode.ai/_build/assets/entry-client-VF7ouASi.css已验证1opencode.ai已验证核验于 2026年8月30日
A quick-start / agent-skills documentation page is reachable at https://opencode.ai/_build/assets/entry-client-VF7ouASi.css.
https://opencode.ai/_build/assets/entry-client-VF7ouASi.csshttps://opencode.ai/_build/assets/entry-client-dCNGfboU.js已验证1opencode.ai已验证核验于 2026年8月30日
A quick-start / agent-skills documentation page is reachable at https://opencode.ai/_build/assets/entry-client-dCNGfboU.js.
https://opencode.ai/_build/assets/entry-client-dCNGfboU.jsCLI | OpenCode已验证1opencode.ai已验证核验于 2026年8月30日
A quick-start / agent-skills documentation page is reachable at https://opencode.ai/docs/cli.
https://opencode.ai/docs/clihttps://opencode.ai/openapi.json已验证1opencode.ai已验证核验于 2026年8月30日
A machine-readable OpenAPI/Swagger specification is published at https://opencode.ai/openapi.json.
https://opencode.ai/openapi.jsondocs/zen已验证1opencode.ai已验证核验于 2026年7月16日
OpenCode Zen is an optional first-party AI provider offering a pay-as-you-go model charged per million tokens, with users able to add credits to their account.
https://opencode.ai/docs/zendocs/share已验证1opencode.ai已验证核验于 2026年7月16日
OpenCode supports conversation sharing via public links with three configurable modes: manual, auto-share for every new conversation, and disabled.
https://opencode.ai/docs/sharedocs/themes已验证1opencode.ai已验证核验于 2026年7月16日
OpenCode supports a flexible JSON-based theme system requiring truecolor (24-bit) terminal support, with fallback to 256-color approximation when truecolor is unavailable.
https://opencode.ai/docs/themesdocs/keybinds已验证1opencode.ai已验证核验于 2026年7月16日
OpenCode provides configurable keybindings with platform-specific defaults, including Windows terminals that do not support POSIX suspend.
https://opencode.ai/docs/keybindsdocs/providers已验证1opencode.ai已验证核验于 2026年7月16日
OpenCode supports a wide range of LLM providers including 302.AI, Baseten, Cerebras, Snowflake Cortex, and Helicone, with Snowflake limited to Claude and OpenAI families due to tool-calling requirements.
https://opencode.ai/docs/providers决策核对台
在依赖该产品或访问官网前，最值得先确认的问题。
Plan mode disables OpenCode's ability to modify files and instead suggests how it would implement a feature. The documentation recommends asking OpenCode to create a plan before making changes, providing a reviewable strategy before any code is written.
OpenCode supports any LLM provider by configuring their API keys. Documented providers include 302.AI, Baseten, Cerebras, Snowflake Cortex, and Helicone. Snowflake Cortex is limited to Claude and OpenAI families due to tool-calling requirements.
No. OpenCode does not store code or context data. All processing happens locally or through direct API calls to your chosen AI provider. The only exception is the optional /share feature, which sends conversation data to the project's hosting infrastructure only when you explicitly create a public share link.
OpenCode Zen is an optional first-party AI provider with pay-as-you-go pricing charged per million tokens. You sign in, add billing details, and connect via the /connect command. It is completely optional — you can use your own API keys from other providers instead.
Windows installation support using Bun is currently in progress and not yet complete. The primary development target is Unix-like environments for now.
请在官网核验
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