通过实际操作产品验证交付内容,记录用户可查看的证据,并发布验收报告。可检查已有验证计划或创建检查项,选择合适的操作界面,并使用 `lh` CLI 发布结果。
- 实际检查更改后的产品行为
- 收集截图或其他验证证据
- 编写验证计划和报告
手动获准后,针对受支持的命令行代理和服务器提供的模型运行实时兼容性矩阵。检查请求是否经 LobeHub Desktop 和官方提供方路径完成,并生成逐项证据与结构化报告。
Manually runs the live LobeHub official-provider compatibility matrix across Claude Code, Codex, Grok Build, Kimi Code, Pi, and TRAE when explicitly invoked by the user.
实测评分 未实测
查看安装方法通过 LobeHub Desktop,对 Claude Code、Codex、Grok Build、Kimi Code、Pi、TRAE 及服务器提供的模型进行实时兼容性检查。请求从各代理的命令行工具发出,经由官方提供方路径处理。检查会记录请求和响应是否完成,以及中继、提供方和模型信息。先列出可用组合,再按顺序运行选定的测试项。结果包含每项测试的证据文件和汇总报告,可据此沿着命令行工具启动、身份验证、请求路由等边界排查失败原因。
在变更前后检查外部命令行代理与官方提供方之间的兼容性,并将验证范围限制在指定代理或模型时,可以使用此技能。
实时运行只能手动启动,并需要批准范围和费用。需要已登录的 Electron 环境及目标命令行工具。此技能不会安装或更新命令行工具,也不会执行 OAuth 登录。运行时必须提供 --confirm-live,测试项会依次处理。
本介绍由 AI(OpenAI Codex)根据公开的 SKILL.md 撰写。准确的规格请查看下方原文。
AI 根据 SKILL.md 的内容检查了需要注意的操作和使用前提。评分只依据实际运行的结果(实测对比)。
不计入评分。 由 AI(OpenAI Codex)于 2026年10月26日 评估。仅供参考,安装前请同时查看原文。
安装前可以查看交给 AI 代理的指令内容。
This project skill extends acceptance with one scenario: proving that every
server-advertised official model completes through each supported external CLI
agent and LobeHub's server-default provider binding.
It does not replace Acceptance. Use Acceptance for the plan, approval gate,
evidence contract, immutable rounds, publishing, and teardown. Use
.agents/acceptance/PROJECT.md for LobeHub's Electron launch, auth, CDP, and
multi-instance commands. This skill owns only the compatibility-matrix semantics
and its executable harness.
The user invokes this skill with /testing-heterogeneous-agents in Claude Code
or $testing-heterogeneous-agents in Codex. Do not automatically load or execute
it as part of development, debugging, acceptance, or release tasks, and do not
schedule it. A reference from another skill is not permission to invoke it.
Manual invocation still requires scope and cost approval before live requests.
The matrix covers:
getServerDefaultHeterogeneousCapability response;anthropic-messages or
openai-responses);It does not cover user-defined providers, user-managed API keys, general model quality, tool-use quality, or ordinary chat-agent execution. Add a separate scenario instead of silently widening this matrix.
HARNESS=.agents/skills/testing-heterogeneous-agents/scripts/official-smoke.mjs
# Discover the live matrix and installed CLI versions. Makes no model calls.
node "$HARNESS" list --json
# Narrow discovery when validating one change.
node "$HARNESS" list --agent claude-code,codex --model MODEL_ID --json
# Execute selected or all cells through the real official provider.
node "$HARNESS" run --confirm-live --topic-id TOPIC_ID --cdp 9222
Filters, topic id, and non-default CDP port are optional when the attached Electron window already supplies the intended scope.
Exit codes:
| Code | Meaning |
|---|---|
0 | Every selected cell passed |
1 | At least one selected cell failed |
2 | No failures, but at least one cell was blocked |
3 | Electron, authentication, topic, or capability preflight failed |
Read the acceptance skill, .agents/acceptance/PROCESS.md, and
.agents/acceptance/PROJECT.md. Follow their approval and teardown rules. This
scenario makes billable requests and creates server operation records, so never
infer permission to run it from a request to inspect or list the matrix.
Run list --json first. It reads the live capability response and probes only
already-installed CLI binaries with version/help flags. Use its exact cells as
the plan; do not maintain a second hard-coded model list.
Report missing CLIs as blocked. Do not install, update, or sign in to an external CLI during this workflow. To suppress Claude Code's background update paths even during detection, start or restart the Electron instance with:
DISABLE_AUTOUPDATER=1 DISABLE_UPDATES=1 \
.agents/acceptance/scripts/electron-dev.sh start
Use the Electron section of .agents/acceptance/PROJECT.md to attach to an
already-running signed-in instance or start one for this run. Confirm an active
personal topic or pass --topic-id. Never trigger an interactive OAuth flow.
For each live run, present the discovered agents/models and obtain the
Acceptance plan approval before passing --confirm-live. Run sequentially; do
not parallelize cells because the CLIs share profiles and provider quota.
For repeated manual runs of the same compatibility scope, reuse one stable Acceptance subject so every execution becomes another immutable round in the same history. Previous runs do not authorize another live run.
Run the selected matrix with --confirm-live. By default each CLI receives an
isolated workspace inside the report directory. Pass --cwd only when a real
project workspace is part of the compatibility claim.
The harness starts each cell idempotently in the renderer and polls it with short
host-side evaluations. Do not replace this with one long agent-browser eval:
long evaluations can be retried by the driver and duplicate live requests.
The harness writes an Acceptance-compatible result.json, one text evidence
artifact per cell, and a structured matrix table under:
.records/reports/<timestamp>-heterogeneous-official-provider-smoke/
Unless --report-dir selects another location. Inspect the report and evidence;
do not infer success from the process exit code alone. Publish it with the clean
production lh acceptance run ingest environment required by
.agents/acceptance/PROCESS.md. Confirm that every matrix cell has its required
text evidence and return only the stable Acceptance URL.
Use each failed cell's evidence to identify the first broken boundary:
Load the heterogeneous-agent skill for raw trace, adapter, IPC, persistence, or
terminal-event diagnosis. A model refusing one ingress but passing another is a
request-compatibility signal, not proof of an adapter bug.
run requires --confirm-live; never bypass this gate.The self-test uses a fully stubbed agent-browser; it launches no browser,
external CLI, or model request:
bash .agents/skills/testing-heterogeneous-agents/scripts/official-smoke.test.sh
还没有评价。欢迎分享你的使用感受。
无需登录即可发表。欢迎分享使用感受、提问,或说明在哪些环境下无法运行。
还没有评论。来写第一条吧。
通过实际操作产品验证交付内容,记录用户可查看的证据,并发布验收报告。可检查已有验证计划或创建检查项,选择合适的操作界面,并使用 `lh` CLI 发布结果。
本技能指导在 LobeHub 中接入 AI 模型提供商,涵盖运行时、模型信息、设置、品牌展示、文档和验收,并帮助判断新增模型是否需要新的提供商集成。
本技能指导如何用服务器端环境变量设置用户偏好默认值,涵盖变量校验、服务器配置、写入用户状态,以及更新 `.env.example` 和自托管文档。
说明如何在智能体执行步骤、工具调用、人工审批、上下文压缩和子智能体调用时注册钩子。钩子可观察事件、模拟本地工具结果,也可通过 Webhook 按配置策略允许或拒绝工具调用。
此技能用于为智能体设计事件驱动的后台工作流,划分来源、信号、动作和策略的职责,并处理异步交接、去重、执行范围、完成记录与运行观测。
本技能在 macOS 桌面聊天应用中测试机器人频道:打开应用、进入频道或联系人、发送消息、等待回复并截图。支持 Discord、Slack、Telegram、微信、飞书和 QQ;iMessage 使用 BlueBubbles 桥接。