527 件 ・ 関連度順
概要と使いどころ
Direct substantial repository work across Claude Code, Codex CLI, or Grok Build with a concise brief, parallel agents, evidence-based completion, and optional cross-CLI continuation. Use for project onboarding, multi-step implementation, agent coordination, verification planning, low-interruption setup, or deciding how another CLI should take over. Do not use it as a permission gate or mandatory workflow.
日本語の概要は準備中です。原文の説明を表示しています。
Verification before completion claims. Use when about to say "done", "fixed", or "complete". Runs checklist by workflow type with evidence requirements.
日本語の概要は準備中です。原文の説明を表示しています。
Customer success reconnaissance — audit current onboarding completion, health signals, NRR, churn patterns, and CS motion. Use when asked to "audit our customer success", "why are customers churning", "what's our NRR", or before designing any CS playbook.
日本語の概要は準備中です。原文の説明を表示しています。
Creates GitHub Pull Requests with automated validation and task tracking. Use when user wants to create PR, open pull request, submit for review, or check if ready for PR. Analyzes commits, validates task completion, generates Conventional Commits title and description, suggests labels. NOTE - for merging existing PRs, use github-pr-merge instead.
日本語の概要は準備中です。原文の説明を表示しています。
Parallel agent fleet dispatch with progress tracking and result aggregation. Launch N agents, monitor completion, merge results. Proven at 7-agent scale.
日本語の概要は準備中です。原文の説明を表示しています。
Build a weekly TikTok posting plan from a niche, audience, and content pillars. Produces per-day picks (hook formula, angle, sound, video length, goal, posting time), a hook-batching schedule so you film several openers in one session, a sound shortlist with the trend window, and a completion-rate goal check. Use for a repeatable posting rhythm instead of ad-hoc videos. Not for scripting one hook (use tt-hook-scripter) or one caption (use tt-caption-writer).
日本語の概要は準備中です。原文の説明を表示しています。
Plan, script, caption, and publish short-form video for TikTok. Use when the user wants to write the first 1-3 second hook (spoken line plus on-screen text), draft a caption under 2,200 chars with TikTok settings and hashtags, ride a trending sound without being cringe, strip AI tells from a spoken script to sound human on camera, or plan a week around completion rate. TikTok is video-only: the user supplies the video, the skills produce the script, caption, and settings, then publish via Publora.
日本語の概要は準備中です。原文の説明を表示しています。
Remove the AI-script tells viewers hear in a TikTok spoken script and caption: 2026 vocabulary by density, reveal bridges, staccato stacks, stacked triads, performed sincerity, written-not-spoken phrasing, "hey guys" filler; caps em dashes. Includes --mode audit pre-film check (hook, completion design, caption fit) and --mode profile. Not for beating AI detectors (no edit reliably does). Not for writing from scratch (use tt-hook-scripter). Keywords: humanize script, de-AI, audit before filming.
日本語の概要は準備中です。原文の説明を表示しています。
Script the first 1-3 second TikTok hook: the spoken line, the on-screen text, and the opening visual firing at once so the viewer cannot swipe. Picks a 2026 hook formula (cold-open result, pattern interrupt, number reveal, open-loop question, relatable call-out, story) by goal of completion, saves, comments, or shares. The single biggest retention lever on TikTok. Use to script a hook from a video idea. Not for the caption (use tt-caption-writer) or scrubbing a script (use tt-humanizer).
日本語の概要は準備中です。原文の説明を表示しています。
Use when the primary outcome is refining an existing AI-facing artifact without dropping behavior, including SKILL.md, AGENTS.md, CLAUDE.md, rules, prompts, and agent definitions that need sharper invocation, structure, or completion criteria.
日本語の概要は準備中です。原文の説明を表示しています。
Use when building CLI applications with Typer — creating commands, defining arguments and options with enum restrictions, path validation, date and UUID types, composing subcommands, testing with CliRunner, or using advanced features like colored output, progress bars, shell autocompletion, and version callbacks.
日本語の概要は準備中です。原文の説明を表示しています。
Discover and run configured quality gates for requested or changed work, preserve diagnostics as evidence, route failures to the appropriate causal/domain capability, and verify corrections. Use for linting, formatting, type-checking, configured hook checks, or pre-completion quality verification.
日本語の概要は準備中です。原文の説明を表示しています。
When calling LLM APIs from Python code. When connecting to llamafile or local LLM servers. When switching between OpenAI/Anthropic/local providers. When implementing retry/fallback logic for LLM calls. When code imports litellm or uses completion() patterns.
日本語の概要は準備中です。原文の説明を表示しています。
Use when creating, grooming, planning, or closing a backlog item. Bridges backlog items to SAM planning with issue, project, and milestone tracking against the configured backend. Activates on interactive browsing with no arguments, loading an item by issue reference or title match to run grooming and SAM planning, autonomous unattended runs that substitute evidence-derived decisions for clarifying questions, a quick path for one-file fixes where full grooming is disproportionate, dismissing an item without completion under a required reason (duplicate, out of scope, superseded, wontfix, blocked), marking an item done with an evidence trail and required summary, or initializing GitHub tracking infrastructure for a project. Stops when the item already has a plan or is blocked on missing information.
日本語の概要は準備中です。原文の説明を表示しています。
Use when executing a task the orchestrator dispatched — reads the task and its orchestrator response from the work ledger, loads task-level skills, implements against acceptance criteria, records divergences and the completion report as task sections, and closes the attempt. Triggers on task execution within the implement-feature loop or when an agent picks up a specific task from a plan.
日本語の概要は準備中です。原文の説明を表示しています。
Close a completed GitHub milestone. Args: {milestone-number}. Audits open and closed issues, offers to carry forward open items to a new or existing milestone, closes the GitHub milestone, updates Project V2 Status to Done for closed issues, and generates a completion summary. Use when a sprint or release is finished and needs to be officially closed.
日本語の概要は準備中です。原文の説明を表示しています。
When the user wants to optimize any form that is NOT signup/registration — including lead capture forms, contact forms, demo request forms, application forms, survey forms, or checkout forms. Also use when the user mentions "form optimization," "lead form conversions," "form friction," "form fields," "form completion rate," or "contact form." For signup/registration forms, see signup-flow-cro. For popups containing forms, see popup-cro.
日本語の概要は準備中です。原文の説明を表示しています。
Design and optimize AI agent action spaces, tool definitions, and observation formatting for higher completion rates.
日本語の概要は準備中です。原文の説明を表示しています。
Live real-time dashboard for monitoring AI agent swarms with smart completion detection, clickable agent detail views, idle time tracking, and activity streaming. Auto-launches a beautiful web UI with capybara-inspired colors.
日本語の概要は準備中です。原文の説明を表示しています。
Track and report agent invocation metrics including usage counts, success/failure rates, and completion times. Use for understanding which agents are utilized, identifying underused agents, and optimizing agent delegation patterns.
日本語の概要は準備中です。原文の説明を表示しています。
Generate markdown reports from issues. Filter by type, priority, epic, date range. Supports summary, detailed, progress, completion, velocity, and backlog analysis views.
日本語の概要は準備中です。原文の説明を表示しています。
Check and process messages from autonomous AILANG agents. Use when starting a session, after agent handoffs, or when checking for completion notifications.
日本語の概要は準備中です。原文の説明を表示しています。
Master orchestration for the VNX multi-terminal system. Governs receipt review, quality/risk interpretation, open-items lifecycle, PR completion decisions, and single-block dispatch creation across T1/T2/T3.
日本語の概要は準備中です。原文の説明を表示しています。
Run a high-thoroughness end-to-end implementation loop using clean worker worktrees, per-slice planning, implementation, explicit review/fix iteration, orchestrator integration, and final commit/PR drafting. Use when the user explicitly wants a Ralph/Wiggum-style loop, autonomous multi-agent execution, a delegated feature/bugfix carried from confirmed scope through review-ready completion, or RFC-driven implementation that should be reviewed, bumped to In Progress, decomposed into phases, and executed through nested sub-loops. Supports Codex subagents by default and external CLI workers such as OpenCode when explicitly requested and available.
日本語の概要は準備中です。原文の説明を表示しています。