邮件、日历、任务管理、自动化（7838 个）
Prepare Apple Notes exports and Markdown conversions by handling note HTML, checklist states, and attachment metadata. Scope exports to selected folders, check conversion limitations, and produce records that support backup or migration reviews.
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Collect diagnostic evidence for Apple Notes automation failures involving AppleScript or JXA, JavaScript for Automation. Package platform details, authorization outcomes, and redacted errors into a scoped archive with a manifest, while excluding note content and sensitive records.
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Manage AI work in one Notion task database, from capturing ideas and discussing proposals to approving and running tasks. Dispatch approved work to parallel agents using task-specific model choices while respecting dependencies and tracking progress.
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Find and load AGENTS.md instruction files across a project's directory hierarchy. Combine shared and module-specific rules, report conflicting instructions and source paths, and reuse discovery results during the current agent session.
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Work with the `wacli` repository and local stores for WhatsApp linked devices. Inspect accounts, chats, messages, and database health with read-only commands, or handle authentication, syncing, sending, repository changes, and releases when requested.
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Use the Skillshare CLI to install, sync, inspect, and recover skills and other agent resources across configured targets. It also guides shared memory notes, MCP settings, plugins, hooks, audits, backups, and troubleshooting in global or project configurations.
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Finds installable agent skills for a task or area of interest, then explains what relevant options do and how to install them. It helps users explore available tools, templates, and workflows when they want to extend an agent’s capabilities.
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Keep project context across Claude Code sessions with a two-layer memory system: a quick-access MEMORY.md file and a linked knowledge wiki. It supports separate project backlogs, safety hooks against context loss, and an end-of-day `/close-day` summary, with no external dependencies.
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Manage AI agent skills and instruction files across 11 tools. Learn where each tool stores them and how to list, create, edit, enable or disable, copy, move, and remove files while adapting formats when needed.
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Search local WeChat chats in read-only mode, review recent history with a contact, and draft a short reply without sending it. The skill can guide first-time access setup when explicitly requested, with separate confirmation for acquiring local access material.
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Summarize work since the user’s last message as a short silent landscape video made from slides, with waiting calls listed as text beneath it. The slides use captured work artifacts, show what is done or still pending, and keep each frame focused on one point.
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Restate the user’s goals and the problem they are trying to solve in your own words. Use it to make the understood request explicit before moving ahead, so the user can check whether the interpretation matches their intent.
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Get guidance on setting up pstack, starting work with /poteto-mode, choosing a skill or playbook for a task, and troubleshooting a run. The skill answers how-to questions with a prompt you can send and a link to the relevant source.
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Apply a detailed working style that favors concise explanations, simple code, deliberate delegation, and checking results against the real artifact. It also routes different kinds of work to relevant principles and playbooks when available.
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Rewrite the agent’s previous message in concise, plain language. It removes jargon and awkward phrasing while keeping the explanation coherent and direct, so the same point is easier to understand.
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Summarizes what changed in a chat since the user's last message and explains why it matters. It also lists every decision or action waiting on the user, with enough context to decide from the summary alone.
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Turn a user's recurring work preferences into a personal “-mode” skill that agents can follow. The guided workflow can create a new skill or revise an existing one, using recent conversation history as optional evidence.
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Keep a reviewable record of decisions during long-running or unattended work. The skill uses a single TSV log to capture what was decided, why, supporting evidence, and the result, so a reviewer can follow the work later.
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Rebuild recent work context from chat history, current project state, and shared records such as reports, fixes, and incidents. Get a concise brief of active threads, recurring problems, and the most useful next action before resuming work.
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Coordinate multiple agents to cover separate parts of a task or compare results from the same brief, then combine their findings into one report. Useful for parallel exploration, reviews, and other work that benefits from broader coverage.
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When asked to reflect, this skill reviews the active conversation for reusable lessons and maps accepted findings to edits in existing skills. It gathers reviewer input, checks whether a structural rule should enforce a lesson instead, and waits for approval before applying skill changes.
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Manage an agent's limited conversation context when large outputs, long files, repeated reads, or broad planning start to fill it. The skill recommends limiting each phase and sending bulk work to subagents while keeping summaries in the main conversation.
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Keep reversible work moving by making reasonable execution decisions, completing the task, and showing the result for later feedback. It distinguishes routine edits from irreversible actions that still need confirmation.
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Turn a repeated workflow into a reusable OpenChatCut skill. The process captures intent, clarifies when the skill should activate and what it should produce, then drafts or updates a SKILL.md and checks it with realistic prompts.
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