“first run”的搜索结果

Generate ScriptableObject-based systems including data containers, event channels, and runtime sets. Use when creating game data (weapons, enemies, items, abilities), cross-system events, or live object tracking. Triggers on requests like "create weapon data", "add an event system", "make a runtime set", "decouple these systems", "create item database", "add a damage event", "track active enemies", "create a config SO", "add game settings data", or any task involving ScriptableObject data containers, event-driven communication, or runtime object tracking. Reads ProjectConfig.yaml -> architecture_pattern to determine SO-first vs DI-first context.

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Run work as an explicit event-driven state machine executed by subagents. The orchestrator is the runtime from the canonical loop — `state, effects = init(machine); execute(effects); while state is active: event = nextEvent(); state, effects = transition(machine, state, event); execute(effects); return state.output`. All routing judgment is authored ONCE, at plan time, into a machine file (states, event alphabet, transition table, budgets, final states); at runtime the orchestrator does pure table lookups and dispatches effects — it never decides, never authors, never ingests artifacts. Subagent/sync protocol is the timeboxed-iterating one: role prompts scaffolded once to disk and dispatched BY PATH, an initialiser preamble every subagent reads first, a self-populating cheatsheet, per-unit files, tiny structured returns, independent measurement gate. Use when the user says "workmachine", "run this as a state machine", "state-machine this", or when a goal has a small number of clearly named phases with explicit outcomes (built / passed / failed / blocked) and you want the routing to be auditable rather than judged on the fly. For clock-driven loops use timeboxed-iterating; for wide graphs with judged edge criteria use workgraph.

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When the user wants to optimize post-signup onboarding, user activation, first-run experience, or time-to-value. Also use when the user mentions "onboarding flow," "activation rate," "user activation," "first-run experience," "empty states," "onboarding checklist," "aha moment," "new user experience," "users aren't activating," "nobody completes setup," "low activation rate," "users sign up but don't use the product," "time to value," or "first session experience." Use this whenever users are signing up but not sticking around. For signup/registration optimization, see signup. For ongoing email sequences, see emails.

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When the user wants to optimize post-signup onboarding, user activation, first-run experience, or time-to-value. Also use when the user mentions "onboarding flow," "activation rate," "user activation," "first-run experience," "empty states," "onboarding checklist," "aha moment," "new user experience," "users aren't activating," "nobody completes setup," "low activation rate," "users sign up but don't use the product," "time to value," or "first session experience." Use this whenever users are signing up but not sticking around. For signup/registration optimization, see signup-flow-cro. For ongoing email sequences, see email-sequence.

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Critically audit agent skills and remove content that is outdated, disproven, model-specific, or based on poorly cited sources. Load when improve-skills runs its per-skill cycle, when the user asks to prune skills, remove outdated techniques, check if skills are still valid, verify citations in skills, audit skill sources, or update skills for a new model release. Also triggers on "are these skills still valid", "check for obsolete techniques", "verify skill citations", or "update skills for GPT-5/Claude 4/Gemini 2". Runs before split-skill and compress-skill — removing bad content first means the remaining content is worth preserving.

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Find the earliest decisive failure in an agent run trace and propose an evidence-backed targeted repair. Load when a run failed, results are wrong, or the user asks what went wrong in an agent session. Also triggers on "localize the fault", "first incorrect step", "debug this run", "trace attribution", "why did the agent fail", or after run-trace captures errors. Pairs with debug-and-fix for code defects and dynamic-routing for plan faults.

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Guides an agent through reproducing, root-causing, fixing, and validating flaky tests in the PostHog monorepo. Use when a test fails intermittently in CI but passes on rerun or locally, when `hogli ci:insights` or the debugging-ci-failures skill classifies a failure as a flaky test, when given a GitHub Actions URL for a flaky job, when asked to check Trunk Flaky Tests for a test, PR, or master, or when asked to deflake, stabilize, or fix a flaky Jest, pytest, or Playwright test. Core discipline: reproduce locally before changing anything, fix the root cause (never mask it with sleeps, retries, or bigger timeouts), and prove the fix with an N-run validation loop sized to the observed failure rate. Stabilizing is not the only valid outcome — the skill also gates whether the test should exist, so deleting a test that catches nothing real, or re-leveling one that flakes because of the level it runs at, are first-class endings.

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按测试驱动开发流程新增功能或修复缺陷：先确认测试按预期失败，再以最少代码使其通过，随后整理代码，并检查至少80%的测试覆盖率、记录验证结果。

• 从测试开始实现新功能
• 先复现缺陷再修复
• 保持测试通过并整理代码

从目标读者的角度试读发布前的文稿，检查是否愿意打开、在哪里失去兴趣，以及读后记住什么。它报告模拟读者的反应，不改写文章。

• 检查帖子是否会被读完
• 找出读者停止阅读的位置
• 比较修改前后的读者反应

通过Rube MCP自动化Doppler Secretops操作，先查询支持的工具及所需输入，检查连接状态，再按获取的定义执行任务。

• 查询Doppler Secretops支持的操作
• 开始工作前检查连接状态
• 批量执行多个支持的操作

通过Rube MCP将Dreamstudio操作交给AI智能体。查询可用工具和输入格式，确认连接后执行，并支持批量操作及获取分页结果。

• 查询Dreamstudio可用操作
• 执行前检查连接状态
• 批量执行Dreamstudio操作

通过Rube MCP自动执行Dialmycalls支持的操作。从Composio中查找工具，检查连接状态和最新输入要求，并按对应工具执行任务。

• 查找支持所需任务的工具
• 执行前检查连接状态
• 批量执行多个受支持的操作

Automate Digicert operations through Rube MCP, a connection to external tools. The skill guides an agent through finding available actions, checking the connection, and running tasks with the input fields those tools currently require.

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• Find available Digicert actions
• Check the connection before running tasks
• Run a series of Digicert operations

Automate Dadata Ru tasks through Rube MCP, a connection between an AI agent and external tools. The skill finds suitable operations, verifies the service connection, and runs the requested work with current input requirements.

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• Finding available Dadata Ru operations
• Checking the connection before running tasks
• Running multiple Dadata Ru operations together

通过Rube MCP将Corrently操作交给AI智能体。查找合适工具，确认输入字段和连接状态后执行，并按流程复用会话及获取分页结果。

• 查询Corrently可用操作
• 执行前确认连接状态
• 依次执行Corrently操作

通过Rube MCP将Callpage操作交给AI代理，查询可用工具及最新输入规范，按流程检查连接并执行任务，也支持批量处理。

• 查询Callpage支持的操作
• 执行前检查连接状态
• 批量执行多个操作

通过Rube MCP将Campayn操作交给AI代理，查询可用工具及最新输入规范，按流程检查连接并执行任务，也支持批量处理。

• 查询Campayn支持的操作
• 执行前检查连接状态
• 批量执行多个操作

Automate Bugsnag operations through Rube MCP and Composio. The skill identifies available tools, reads their current input requirements, checks the service connection, and follows the discovered specifications to run supported tasks.

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• Find tools for a Bugsnag task
• Check the service connection before running tasks
• Run supported operations in bulk

Automate Byteforms operations through Rube MCP and Composio. The skill discovers available tools, checks their current input requirements, verifies the connection, and runs supported tasks using the tools it finds.

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• Discover available Byteforms operations
• Check the Byteforms connection before running tasks
• Run multiple supported operations together

Automate Browseai operations through Rube MCP, a connection to external tools. The skill guides an agent through finding available actions, checking the connection, and running tasks with the input fields those tools currently require.

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• Find available Browseai actions
• Check the connection before running tasks
• Run a series of Browseai operations

通过连接智能体与外部服务的Rube MCP自动执行Borneo操作。先查找可用工具及其输入格式，再检查连接状态并执行受支持的任务。

• 查找支持Borneo任务的工具
• 检查Borneo连接状态
• 集中执行多个受支持的操作

Automate Bitwarden operations through Rube MCP, a connection to external tools. The skill guides an agent through finding available actions, checking the connection, and running tasks with the input fields those tools currently require.

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• Find available Bitwarden actions
• Check the connection before running tasks
• Run a series of Bitwarden operations

Automate Bookingmood operations through Rube MCP, a connection to external tools. The skill guides an agent through finding available actions, checking the connection, and running tasks with the input fields those tools currently require.

中文简介正在准备中。当前显示英语简介。

• Find available Bookingmood actions
• Check the connection before running tasks
• Run a series of Bookingmood operations

Automate Ambee operations through Rube MCP, a connection for agent tools. The skill finds available actions, verifies the service connection, and runs tasks using the current input requirements supplied by Composio.

中文简介正在准备中。当前显示英语简介。

• Finding available Ambee actions
• Checking the connection before running tasks
• Running multiple supported operations together