「workspace」の検索結果

Drive a whole tdmcp feature BACKLOG to completion as resumable, wave-by-wave releases — the campaign layer ABOVE tdmcp-pipeline/tdmcp-feature-lead. Use whenever the user wants to implement an ENTIRE backlog or discovery file (e.g. _workspace/discovery*/FEATURE_BACKLOG*.md), 'all the features', many features across multiple releases, or a long autonomous build campaign, AND for every follow-up: continue/resume the campaign, run the next wave, re-run a failed wave, fold in QA results, or check campaign status. Backed by a ledger.json so re-running is idempotent (skips shipped work, resumes interrupted work) and resilient (retry-once then quarantine-and-continue). For a SINGLE feature or one small batch, use tdmcp-pipeline instead; this skill is for the whole ledger.

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。

Survey one surface of tdmcp (artist controls, library/packaging, CLI/DX, AI/LLM, or TouchDesigner depth) for candidate NEW features — inventory what exists, cross-check the roadmap, apply the gap-finding lenses, vet each idea, and emit a structured, novelty- and confidence-labelled candidate list to _workspace/discovery/. Use when a td-surveyor agent is scouting a surface during the feature-discovery harness.

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 acting as the orchestrator agent that drives Syntropic137 - running the dogfood loop, deciding what to dispatch next, landing agent PRs, deploying a beta, triaging failed executions, or keeping the scratchpad, paper cuts and retrospectives current. Trigger phrases include "orchestrator tick", "keep the loop running", "what should we dispatch next", "land these PRs", "why are PRs stacking up", "deploy the next beta", "pit stop", "the run failed, what now", "write the retro", "is the system helping", "scale quality", "learning loop for the orchestrator". Do NOT use for deciding whether one task belongs in a workspace or locally (see `dogfooding`), for turning one incident into an eval case (see `learning-loop`), for designing a workflow A/B experiment (see `workflow-experimentation`), or for release-branch and version-bump mechanics (see `devops`).

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。

Control Herdr, a terminal multiplexer for coding agents. Use only when the user explicitly mentions Herdr or asks to use Herdr to inspect or control panes, tabs, workspaces, commands, or another agent. Do not use merely because a task could benefit from a background terminal, delegation, or parallel work. Requires HERDR_ENV=1.

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 starting feature work that needs isolation from current workspace or before executing implementation plans - creates isolated git worktrees with smart directory selection and safety 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。

Automate Bitbucket repositories, pull requests, branches, issues, and workspace management via Rube MCP (Composio). Always search tools first for current schemas.

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。

Azure Monitor Query SDK for Python. Use for querying Log Analytics workspaces and Azure Monitor metrics.

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。

Azure Monitor Ingestion SDK for Python. Use for sending custom logs to Log Analytics workspace via Logs Ingestion API.

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。

Azure Monitor Query SDK for Java. Execute Kusto queries against Log Analytics workspaces and query metrics from Azure resources.

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。

Azure Machine Learning SDK v2 for Python. Use for ML workspaces, jobs, models, datasets, compute, and pipelines.

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。

Automate Asana tasks via Rube MCP (Composio): tasks, projects, sections, teams, workspaces. Always search tools first for current schemas.

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。

Gmail, Calendar, Drive, Docs, Sheets via gws CLI or Python.

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。

Invoke connected Unique spaces/subagents through the unique-cli subagent command. Use when the workspace exposes connected-space tools and you need to delegate a question or task to one of those configured assistants.

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。

Microsoft Learn の公式ドキュメントを調査し、正確で最新の情報を構造的にまとめるスキル。Azure サービスの仕様確認、機能比較、ベストプラクティスの調査に使用する。

顧客企業の情報、業界動向、導入事例を調査し、提案・プリセールス活動に役立つインサイトを構造的にまとめるスキル。

SVG でスライドを設計し、Python スクリプト (svg2pptx.py) で編集可能な PPTX に変換するスキル。デザイントークン・カラーパレット・レイアウト原則を統一し、高品質なプレゼンスライドを生成する。

Markdown で提案書・報告書・議事録などのビジネスドキュメントを構造的に作成するスキル。対象読者に応じた表現で、そのまま使える品質を目指す。

Busabase-backed App-in-Skill control-panel/workspace for a deal analyst to model revenue-based-financing (RBF) deals for SME businesses (retail/F&B chain stores). Use when the user invokes $kelly-revshare-simulator or /kelly-revshare-simulator, wants to model a revenue-share or merchant-cash-advance deal, project cash flow and repayment, compute a Cash-Flow Payout Multiple, effective annualized merchant cost, or compare/underwrite multiple financing scenarios. Pure deterministic math, no external calls, no real trading/payment side effects. Scenario create/edit/delete and the underwriting decision are direct writes made by the analyst, not a review/approval queue.

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 create Busabase-backed App-in-Skill packages with a canonical app project, Busabase-native setup and product onboarding, review/execution workflows, a standardized responsive UI, and AirApp-first delivery. Use when a user wants a Busabase research desk, review queue, planner, action console, operating dashboard, control panel, collaboration workspace, onboarding/readiness flow, or an existing Kelly App-based skill updated. Every generated skill contains a complete app/ project, deploys that source to Busabase AirApp by default, runs pnpm dev only when local preview is explicitly requested, follows the Kelly desktop and phone UI contract, delegates AirApp runtime, SDK, security, scaffolding, and deployment constraints to busabase-app-creator, and delegates repository-level conformance testing to kelly-app-skill-creator-tests.

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。

Drive the AgentWiki knowledge platform via its CLI (`@aiagentwiki/cli`, command `agentwiki`) and MCP server (`https://api.agentwiki.cc/mcp`). Use this skill whenever the user mentions AgentWiki, agentwiki.cc, app.agentwiki.cc, the `agentwiki` CLI, the `@aiagentwiki/cli` npm package, the AgentWiki MCP server, or asks to create/list/search/share/publish documents, manage folders or tags, upload files or images, deploy static sites, traverse a knowledge graph, or query their AgentWiki workspace from the terminal or as an AI agent. Triggers include phrases like "agentwiki login", "aw_… API key", "create a doc on agentwiki", "search my wiki", "publish to agentwiki", "agentwiki MCP", or any task that would otherwise require opening app.agentwiki.cc manually.

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。

Detect compromised O365 and Google Workspace email accounts by analyzing inbox rule creation, suspicious sign-in locations, mail forwarding rules, and unusual API access patterns via Microsoft Graph and audit logs.

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。

Intelligently organizes your files and folders across your computer by understanding context, finding duplicates, suggesting better structures, and automating cleanup tasks. Reduces cognitive load and keeps your digital workspace tidy without manual effort.

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。

Searches across your Notion workspace, synthesizes findings from multiple pages, and creates comprehensive research documentation saved as new Notion pages. Turns scattered information into structured reports with proper citations and actionable insights.

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。

Teach the user a new skill or concept, within this workspace.

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。