cheat-on-content
给所有想把"感觉"变成可校准预测的内容创作者。**方法论通用**——打分 → 盲预测 → T+3d 复盘 → 进化 rubric 的循环适用任何能被量化(播放 / 阅读 / 收听 / 点击)的内容。**rubric…
Automate Make (Integromat) tasks via Rube MCP (Composio): operations, enums, language and timezone lookups. Always search tools first for current schemas.
Claude Code
$ npx -y skills add LiHongwei-cn/lihongwei-cn --skill make-automation --agent claude-code
Codex
$ npx skills add LiHongwei-cn/lihongwei-cn --skill make-automation -a codex -y
Cursor
$ npx skills add LiHongwei-cn/lihongwei-cn --skill make-automation -a cursor -y
Gemini CLI
$ npx skills add LiHongwei-cn/lihongwei-cn --skill make-automation -a gemini-cli -y
GitHub Copilot
$ npx skills add LiHongwei-cn/lihongwei-cn --skill make-automation -a github-copilot -y
OpenCode
$ npx skills add LiHongwei-cn/lihongwei-cn --skill make-automation -a opencode -y
Windsurf
$ npx skills add LiHongwei-cn/lihongwei-cn --skill make-automation -a windsurf -y
name: make-automation description: "Automate Make (Integromat) tasks via Rube MCP (Composio): operations, enums, language and timezone lookups. Always search tools first for current schemas." risk: critical source: community date_added: "2026-02-27"
Automate Make (formerly Integromat) operations through Composio's Make toolkit via Rube MCP.
**Get Rube MCP**: Add `https://rube.app/mcp` as an MCP server in your client configuration. No API keys needed — just add the endpoint and it works.
1. Verify Rube MCP is available by confirming `RUBE_SEARCH_TOOLS` responds 2. Call `RUBE_MANAGE_CONNECTIONS` with toolkit `make` 3. If connection is not ACTIVE, follow the returned auth link to complete Make authentication 4. Confirm connection status shows ACTIVE before running any workflows
**When to use**: User wants to retrieve operation logs or usage data from Make scenarios
**Tool sequence**: 1. `MAKE_GET_OPERATIONS` - Retrieve operation records [Required]
**Key parameters**:
**Pitfalls**:
**When to use**: User wants to see supported languages for Make scenarios or interfaces
**Tool sequence**: 1. `MAKE_LIST_ENUMS_LANGUAGES` - Get all supported language codes [Required]
**Key parameters**:
**Pitfalls**:
**When to use**: User wants to see supported timezones for scheduling Make scenarios
**Tool sequence**: 1. `MAKE_LIST_ENUMS_TIMEZONES` - Get all supported timezone identifiers [Required]
**Key parameters**:
**Pitfalls**:
**When to use**: User needs to configure scenarios with correct language and timezone values
**Tool sequence**: 1. `MAKE_LIST_ENUMS_LANGUAGES` - Get valid language codes [Required] 2. `MAKE_LIST_ENUMS_TIMEZONES` - Get valid timezone identifiers [Required]
**Key parameters**:
**Pitfalls**:
Before configuring any Make scenario properties that accept language or timezone:
1. Call MAKE_LIST_ENUMS_LANGUAGES or MAKE_LIST_ENUMS_TIMEZONES 2. Verify the desired value exists in the returned list 3. Use the exact string value from the enum list
1. Call MAKE_GET_OPERATIONS with date range filters 2. Analyze operation counts, statuses, and error rates 3. Identify failed operations for troubleshooting
Since language and timezone lists are static:
1. Call MAKE_LIST_ENUMS_LANGUAGES once at workflow start 2. Store results in memory or local cache 3. Validate user inputs against cached values 4. Refresh cache only when starting a new session
For scenario health monitoring:
1. Call MAKE_GET_OPERATIONS with recent date range 2. Group operations by scenario ID 3. Calculate success/failure ratios per scenario 4. Identify scenarios with high error rates 5. Report findings to user or notification channel
Make workflows often connect to other apps. Compose multi-tool workflows:
1. Call RUBE_SEARCH_TOOLS to find tools for the target app 2. Connect required toolkits via RUBE_MANAGE_CONNECTIONS 3. Use Make operations data to understand workflow execution patterns 4. Execute equivalent workflows directly via individual app toolkits
**Limited Toolkit**:
**Operations Data**:
**Response Parsing**:
**Rate Limits**:
**Authentication**:
MUNDO - THE EMPEROR. Complete AI orchestration system with 1208 skills, 25 capability modules, self-evolving, collective consciousness. GitHub Actions 24/7 automation.
给所有想把"感觉"变成可校准预测的内容创作者。**方法论通用**——打分 → 盲预测 → T+3d 复盘 → 进化 rubric 的循环适用任何能被量化(播放 / 阅读 / 收听 / 点击)的内容。**rubric…
提议并执行 rubric 或 bucket 升级。两种模式:**完整 rubric bump**(最高风险动作,5 步强制 + 跨模型审核)和 **--bucket-only 轻量重校**(只换 bucket 边界,不动 rubric 公式)。**Phase…
cheat-on-content 的首次 onboarding 与脚手架创建器。统一流程——所有用户都走相同 5 阶段闭环,唯一区别是"发过视频的人"会在 init 时多一步:抓取已有视频建立历史 context(用于后续 cheat-seed…
从对标账号导入 script + 数据 → 拆 pattern + 派生 base rubric 信号 → 写到 benchmark.md / script_patterns.md /…
把老用户的 .cheat-state.json 升级到当前 schema_version。读 migrations/registry.md 算迁移链,按顺序应用每一步迁移文件。幂等:跑两次结果一样。失败停在中间版本不前进。触发词:"迁移"/"升级…
从复盘评论数据派生 / 刷新账号的受众画像,写入 audience.md。这是和 rubric 平行的第二个派生物——rubric 答"怎么打分",persona 答"谁在看"。cheat-seed 选题 / 写稿时读它。**audience.md…
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