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Weekdays, light browser lane. The one routine in this kit with an outward surface. Takes the slots that are due today, whose drafts were written yesterday and passed the copy check, whose hold box is not ticked, and whose destination the member wrote into the publish allow list themselves, and hands each one to the channel the member configured. It records a receipt the instant each slot lands. It never drives a browser control to publish, never replies, sends only where you released the channel a message, spends only where you released it, and never touches a credential.

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。

Runs once by hand on the first day and once a month after that. On the first run it researches the business from its own public presence, writes the charter with a source and a date beside every conclusion, discovers the AI Employees actually installed on this machine within a bounded search, writes the map every other routine in this kit reads, seeds the priorities and the watchlist once, builds the fleet dashboard, and registers this Employee's own seven jobs. On every monthly run it re-runs discovery and reconciles the map against what is really there. It never writes into another Employee's folder, never registers a job it does not own, sends only where you released the channel, spends only where you released it, and never touches a credential.

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。

Weekdays, file work only, no browser at all. Reads every run record, folds the metrics, change, and creative ledgers, turns yesterday's ticks into facts a machine can count, folds the card inbox, rewrites the board, and writes the short morning brief the member opens first. It holds every outbound action unless you released the channel, and it never touches a credential.

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。

Weekly, file work only, no browser at all. Reads everything the week produced, picks exactly three moves, and argues both sides of each one before the member reads a word of it, with every clause carrying a number or an observation from a file it names. It argues against its own top recommendation last, records a predicted effect and the metric that would show it so the monthly review can score it, and files each move onto the register. It sends only where you released the channel, spends only where you released it, never deploys, and never touches a credential.

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。

Runs once by hand on the first day and once a month after that. On the first run it researches the business from its own public surfaces before asking anything, reads the account structure once, writes the plan folder, seeds the board, creates the creative doctrine, builds the dashboard, and registers the recurring jobs. It asks about exactly two things, the monthly ceiling and the daily cap, because those are the two numbers that decide how much money can leave. On every monthly run it re reads the evidence, corrects what the ledgers prove wrong, and reconciles drift.

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。

Runs once by hand on the first day and once a month after that. On the first run it researches the business from its own public surfaces before asking anything, writes the strategy folder, seeds the launch board, builds the tailored command center, reconciles the schedule table, and registers the recurring jobs. On every monthly run it re-reads the evidence the kit produced, applies what changed, reconciles drift, and rebuilds. It holds every outbound action unless you released the channel, and it never enters a credential.

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 user needs to define, document, or enforce how the brand SOUNDS in writing — three personality traits, a five-dimension tone table, vocabulary to use, avoid, and ban, sentence rules, before and after rewrites, platform adaptation, and a copy approval checklist. Every content skill reads it before writing. Trigger on 'brand voice', 'tone of voice', 'voice guidelines', 'banned words list', 'this copy does not sound like us', 'every writer sounds different'. Also use when the user cannot say why a draft feels wrong. Not for — the visual side of brand, see `46-brand-guideline-global`; positioning and the message, see `58-positioning-global`; approving one specific piece, see `62-marketing-review-global`.

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。

Slack CLI for agents: read URLs/threads/history/unreads/later/canvases/workflows, create/edit canvases from Markdown, search messages/files, download attachments, lookup users, list/create/invite channels, open DMs, compose messages, manage Slack-native drafts, schedule sends, and explicit sends/edits/deletes/reactions/mark-read/uploads.

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。

Canonical patterns for writing custom MSBuild targets. USE FOR: diagnosing and fixing custom target authoring anti-patterns; broken SDK target chains across files (e.g., Directory.Build.targets silently redefining SDK targets); targets that replace CompileDependsOn instead of extending it with $(CompileDependsOn); query targets returning stale results from Outputs vs Returns misuse; missing Inputs/Outputs causing unnecessary rebuilds; missing FileWrites registration. Covers DependsOnTargets vs BeforeTargets vs AfterTargets, the Build→CoreBuild three-level pattern, and the $(XxxDependsOn) chain-extension pattern. DO NOT USE FOR: incremental build tuning (use incremental-build), parallelization (use build-parallelism), general anti-patterns (use msbuild-antipatterns), non-MSBuild build systems.

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。

Guide for optimizing MSBuild incremental builds. USE FOR: builds slower than expected on subsequent runs, 'nothing changed but it rebuilds anyway', diagnosing why targets re-execute unnecessarily, fixing broken no-op builds. Covers 8 common causes: missing Inputs/Outputs on custom targets, volatile properties in output paths (timestamps/GUIDs), file writes outside tracked Outputs, missing FileWrites registration, glob changes, Visual Studio Fast Up-to-Date Check (FUTDC) issues. Key diagnostic: look for 'Building target completely' vs 'Skipping target' in binlog. DO NOT USE FOR: first-time build slowness (use build-perf-baseline), parallelism issues (use build-parallelism), evaluation-phase slowness (use eval-performance), non-MSBuild build systems.

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 free built-in .NET maintainability analyzers and code metrics configuration to find overly complex methods and coupled code. USE FOR: the team wants to find overly complex methods; cyclomatic complexity thresholds are needed in CI; maintainability metrics or coupling thresholds need to be configured. DO NOT USE FOR: formatting-only work; generic analyzer setup with no complexity policy change. INVOKES: inspect the repository context, edit targeted files, and run relevant build, test, lint, or validation commands when changes are made.

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。

Query and answer questions about Volcengine API specifications. Trigger this skill whenever a user asks about Volcengine API parameters, error codes, request methods, enum values, required fields, response structures, pagination, parameter dependencies, or API comparisons — even if they don't explicitly say "API". Typical triggers include questions like "What parameters does DescribeInstances have?", "What values does Status support?", "What does InvalidInstanceId.NotFound mean?", "Does Volcengine have a batch tag deletion API?", "Which APIs does ECS support?", "How do I pass parameters to CreateDatabase?", "Is ChargeType required?", "What fields does DescribeInstances return?", "How do I paginate instance lists?", "What's the difference between these two APIs?", "RunInstances returns InvalidParameterValue". When the user needs runnable SDK code, hand off to the volcengine-sdk-generator skill. When the user needs CLI-based operations, hand off to the volcengine-cli skill. Supports both Chinese and English prompts.

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。

ENHANCE overlay on [[dspy]] — the upfront rubric for choosing a reasoning SHAPE (Predict / ChainOfThought / ReAct / ProgramOfThought) BEFORE you write a prompt or pick an optimizer. The local `dspy` skill lists the modules but never surfaces the *selection criterion*: reasoning shape is chosen by task structure, not by reflexively defaulting to CoT. Activate every time a new LM-calling node/step is added to a pipeline. Do NOT activate for one-shot prompts, optimizer/teleprompter choice (that is the dspy SOP's job), or non-LM control flow. Search keywords: chain of thought vs ReAct, when to use CoT, reasoning type, ReAct vs CoT vs PoT, which dspy module, predict vs chain of thought.

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。

Read and write Google Sheets spreadsheets - get content, update cells, append rows, fetch specific ranges, search for spreadsheets, and view metadata. Use when user asks to: read a spreadsheet, update cells, add data to Google Sheets, find a spreadsheet, check sheet contents, export spreadsheet data, or get cell values. Lightweight integration with standalone OAuth authentication supporting full read/write access.

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。

Read from a UModel object-graph semantic layer with the `umctl` CLI (MCP alternative noted). Three kinds of read: (1) entities & relationships / topology (`.entity`, `.topo`) and (2) the model itself (`.umodel`, and `.entity_set` methods, including entity-linked `list_skills`) return real rows; (3) metrics & logs (`get_metrics` / `get_logs`) return an executable *plan* — PromQL / Elasticsearch DSL with the entity id pre-substituted — that you run against the backend. Against a PaaS endpoint the same calls return data rows instead of a plan. Use to query or read UModel entities, relations, topology, or model metadata; to read a service's metrics or logs; to look up services and dependencies; or to discover what objects, datasets, and methods exist. For root-cause analysis on top of these reads, see the `umodel-rca` skill. Triggers: UModel, object graph, .entity / .topo / .umodel / .entity_set, query entities, read topology, read metrics / logs, get_metrics / get_logs, list services / dependencies / datasets / skills, 实体查询, 关系/拓扑查询, 读模型, 读指标, 读日志, 查指标, 查日志, 查服务依赖.

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。

Cleans up CRM data from HubSpot, Salesforce, Pipedrive, Zoho, Close, Attio, or any CRM CSV export. Finds duplicate contacts and companies with fuzzy matching (not just exact email), normalizes emails, phones to E.164, names, domains, states, and countries, flags stale, invalid, role, and test records, finds broken contact-company associations, and produces a reviewable merge plan plus import-ready files without touching the live CRM. Use this skill whenever the user wants to dedupe, find or merge duplicate contacts, merge companies or accounts, clean up a CRM, prep a CRM migration or re-import, or says the CRM export is a mess. Also use it when they mention only one symptom, like "the same person is in here three times", "half our leads are junk", or "our company records don't match".

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。

Implements financial records retention requirements across EU directives (5-7 years), SOX Section 802 (7 years), MiFID II (5-7 years), tax records, payment data, and AML obligations under AMLD. Maps financial data categories to statutory retention periods with cross-jurisdictional reconciliation. Activate for financial retention, SOX records, MiFID retention, AML retention, tax record keeping queries.

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。

Builds a multi-channel DSAR intake system supporting web form, email, phone, and in-person requests with identity verification tiers, automated routing logic, SLA tracking, and response generation. Activate for DSAR intake, rights request portal, multi-channel intake, SLA tracking, request management queries.

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 GDPR Article 30(1) Records of Processing Activities (RoPA) for data controllers with all seven mandatory fields: controller identity and contact details, processing purposes, data subject categories, personal data categories, recipient categories, third country transfers, and retention periods. Includes Python generator for automated RoPA creation. Activate for controller RoPA, Art. 30(1), processing records, data mapping.

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 user explicitly asks for $threads, Codex-native subagents, 开几个子 agent, or a GitHub issue/PR queue needing parallel lanes, worktrees, review/merge gates, and closure audit. Do not use for OS/language threads, chat/email/forum threads, or Assistants product threads unless Codex workflow orchestration is explicit.

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 and updates coding standards, conventions, rules, and guidelines for the current project. Use when creating new standards from scratch, converting existing documents into coding standards, or updating existing standards. Does not create architectural decision records — use architectural-decision-record for ADRs. Does not write feature or system documentation — use project-documentation for that. Does not research open-ended options — use research. Does not produce runbooks for operational scenarios — use runbook for that.

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。

Optimize DSPy programs with dspy.GEPA — a reflective/evolutionary optimizer to consider against task-specific baselines within an authorized evaluation budget. Use when the user says optimize, compile, GEPA, reflective optimization, or "make this program better" and a DSPy program + metric + trainset exist.

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 dspy.RLM (Recursive Language Model) for reasoning over contexts too large to fit in an LLM's working window — entire codebases, long logs, massive documents, or multi-step data exploration that needs a sandboxed Python REPL. Use when the input is >100k tokens, needs recursive chunking, or benefits from the LLM writing and running code to probe data.

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 DSPy evaluation harnesses with rich-feedback metrics that are essential for GEPA optimization. Use when writing a metric function, calling dspy.Evaluate, splitting dev/val sets, debugging "why is my optimizer not improving?", or designing CI-ready DSPy eval suites.

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。