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概要と使いどころ
Ultra-compressed code review comments. Cuts noise from PR feedback while preserving the actionable signal. Each comment is one line: location, problem, fix. Use when user says "review this PR", "code review", "review the diff", "/review", or invokes /caveman-review. Auto-triggers when reviewing pull requests.
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。
Configure platform-level global search in a Salesforce org — per-object Search Layouts (Search Results, Lookup Dialogs, Lookup Phone Dialogs, Tab columns), the Setup → Search Settings page (Sidebar Search, Lookup Auto-Completion, Drop-Down List size), and Synonym Groups (Setup → User Interface → Synonyms). NOT for Einstein Search personalization signals or Natural Language Search (use agentforce/einstein-search-personalization), NOT for Experience Cloud site Search Manager (use lwc/experience-cloud-search-customization), NOT for SOSL query authoring (use data/sosl-search-patterns), NOT for Commerce storefront search tuning.
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 admins are reducing Chatter signal-to-noise across an org — covers org-level Chatter Email Settings, per-user Email Settings preferences, group-level email digest frequency (Daily / Weekly / Every post / Never), bell-icon Custom Notifications vs Chatter feed-post tradeoffs, automated-feed suppression on record types via Feed Tracking config, and the Chatter Settings org defaults that control whether new users start with everything-on. Triggers: 'chatter feed full of automated posts nobody reads', 'users complain about chatter email volume', 'turn off chatter notifications for a specific group', 'change default chatter digest frequency', 'stop process builder posts from filling the feed', 'NotificationFrequency invalid value', 'ChatterEmailsMD.settings will not deploy', 'custom notification recipient limit'. NOT for Custom Notifications API design (use apex/apex-custom-notifications-from-apex), NOT for Connect API / Chatter REST API integration patterns (use apex/apex-connect-api-chatter), NOT for Chatter group lifecycle, archiving, ownership and unlisted-group governance (use admin/chatter-group-governance).
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。
Detects placeholder content, stub UI, hardcoded test credentials, and non-production endpoints that signal an incomplete app to reviewers under Guideline 2.1.
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。
Design, mock up, build and review terminal UIs — full-screen TUIs, interactive CLIs and pickers, and plugin panels or popups inside a host (herdr, tmux, Neovim, k9s, lazygit). Use when designing, reviewing (from code, a live capture or a screenshot) or redesigning a TUI's layout, keybindings, states or colors, including requests that name a known TUI (lazygit, k9s, btop, yazi, helix, fzf); writing terminal mockups; building or fixing one in Ink, Textual, Bubble Tea, Ratatui or gum; mapping a color scheme (Catppuccin, Dracula, Nord, Gruvbox, Tokyo Night, Rosé Pine…) onto a TUI's theme; fixing misaligned glyphs, flicker, NO_COLOR, exit codes, signals, pipes or a broken terminal after exit; suspend or $EDITOR handoff; or profiling a slow TUI. Not for web or native GUIs, terminal-emulator, editor or shell-prompt themes.
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。
Neuroscience expert covering brain structure, neural signaling, cognition, and neurological disorders
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。
Fourier analysis specialist covering series, transforms, signal processing, and harmonic analysis
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。
Aggregate friction log files across a time period to identify recurring patterns, classify each cluster by intervention type, produce a prioritized action plan with success criteria, and calculate convergence metrics. Complements `skmtc-retro` (which captures per-session signal) by acting as the system's actuator: turning accumulated observations into decisions. The primary output is a review document that makes the "is it getting better?" question answerable. Use this skill when the user asks to "review retros", "review friction", "run a retro review", "what's the pattern across sessions", "what should we fix next", or on a periodic cadence (monthly, pre-release). Also run after a cluster of sessions on the same feature area to surface systemic issues before they compound. Distinct from `skmtc-retro` — that skill captures per-session observations; this skill synthesizes them into decisions. Do not run this skill as a substitute for a per-session retro.
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 self-retrospective on a SKMTC-related session — generator authoring, CLI configuration, debugging, or any sustained interaction involving `@skmtc/core`, `@skmtc/cli`, or `@skmtc/gen-*` packages. Captures three distinct outputs: (1) friction entries (mistakes, surprises, overridden defaults, multi-cycle struggles), (2) a "knowledge acquired" block recording facts the agent learned during the session that weren't in its training — the primary signal for doc gaps — and (3) a closing priority list ranking the top 2-3 findings for docs/skills triage. Wins are logged only when they identify a pattern worth codifying that isn't already in a skill. Use this skill when the user asks to "retro", "skmtc retro", "log friction", "reflect on this session", "what did we learn", "run a retrospective", or after substantive SKMTC work (generator authoring, multi-step debugging, non-trivial CLI configuration) where capturing observations would help improve skills, docs, or SKMTC itself. Distinct from the `skmtc-cli` and `skmtc-generator` skills — those guide *doing* the work; this skill captures observations *about* the work. Do not invoke this skill during ordinary work; it is end-of- session (or mid-session-checkpoint) only.
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。
Deliberate session retrospective — look back over what you just did, distill the durable, reusable lessons (not session trivia), and write them to the learnings memory namespace, deduped against what is already stored. Use at the END of a meaningful chunk of work to capture high-signal lessons worth keeping long-term. The curated counterpart to moflo's passive session-continuity capture.
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。
Curate the project's knowledge base and memory in .unikit/memory/ — the indexed reference library of coding standards and framework usage patterns. ALWAYS use this skill whenever the user adds knowledge from a source: a URL, a file, a folder path, a PDF, an article, or a book — any path/link/document is a strong signal for the knowledge base, not a quick rule. Also use it to research or document how the project uses a framework, or to add a researched core/stack knowledge entry. Sub-commands by phrasing: "migrate the rules" or "promote rules" runs migrate-rules; "optimize the knowledge base" or "optimize the rules" runs optimise (extract large sections into references); "validate" re-syncs RULES_INDEX.md; "--module <id>" targets a module. For a quick one-line convention or correction typed as a prompt ("always do X", "never use Y", "remember this") with no source, use /unikit-rules; for architecture decisions use ARCHITECTURE.md.
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。
Senior {{engine_name}}/{{engine_code_language}} developer that performs direct, ad-hoc code tasks without a formal plan — and the code-execution engine other unikit skills and agents delegate to. Use it whenever the user asks to do something in code right now, e.g. "add this method to this class", "refactor this function", "write a script that does X", "change this code", "optimize this class". Phrases like "without a plan", "no plan", "just do it", or "directly" are strong signals to use this skill rather than planning. Covers writing, refactoring, optimizing, and discussing {{engine_code_language}} code and patterns (DI, ECS, MVC, state machines, event systems). For a larger multi-step feature, plan it with /unikit-plan and build it with /unikit-implement — this skill is for direct, unplanned code work.
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。
Prospective failure imagination for a plan, decision, or running system. Operates in two modes — **plan mode** (a plan has not yet been committed to; imagine its catastrophic failure broadly) and **scenario mode** (a specific catastrophic scenario is posed against an existing system; investigate causes against the actual code and architecture). Spawns parallel pre-mortemers in isolation across three categories of lens: standard failure classes (technical, operational, estimation, scope, adoption, dependency, team, incentive, detection, reversibility, adversarial), 0-3 ad-hoc target-specific lenses the orchestrator names when warranted, and a first-principles lens that always runs to catch what the prescribed taxonomy misses. Synthesizes into a prioritized risk register with early-warning signals. Produces feedback only — no code, no tickets, no artifacts.
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。
This skill should be used when the user gives a SaaS product's landing page URL, homepage, or name and asks for a full teardown or deep-dive of how the product works across web, desktop, and mobile — including per-platform feature inventories and user journeys, tech stack, pricing/plan mapping, how the platforms integrate and sync (and the business logic behind those choices), hardware integrations, business-scale/revenue signals, and concrete release artifacts per platform — with a structured Markdown report as the deliverable. Trigger on phrases like "research this SaaS", "do a platform teardown of X", "map every feature of this product across web/mobile/desktop", "reverse-engineer how this app works everywhere", or a bare URL plus a request to understand the whole product.
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。
Outbound SDR (Sales Development Representative) operating system that runs the full top-of-funnel motion across HubSpot (CRM, engagement, and source of truth) and Exa (web research + signals). Use this skill WHENEVER the user is doing outbound sales development, building target/prospect lists, defining or refining an ICP, enriching leads, researching accounts or people before outreach, writing cold emails or multi-touch sequences, qualifying or scoring leads, logging activity to CRM, handing meetings off to AEs, or reporting on pipeline. Trigger it even when the user only says things like "find me 50 leads", "research this account", "write a cold email to this person", "score these leads", "log this in HubSpot", or "build a sequence"; these are all SDR tasks this skill governs. Do not wait for the user to say "SDR" or "prospecting" explicitly.
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。
Reporting workflow for a working journalist, using web research and Apify's X scraper (social signals). Onboards the journalist, monitors their beat and builds digests, evaluates story pitches, finds and vets sources, and prepares interviews. Use for any newsroom task, such as "what's new on my beat", "is this pitch any good", "who should I talk to about X", "prep me for this interview", or "turn these notes into a draft".
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。
Django architecture patterns, REST API design with DRF, ORM best practices, caching, signals, middleware, and production-grade Django apps.
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。
Library-agnostic Flutter/Dart code review checklist covering widget best practices, state management patterns (BLoC, Riverpod, Provider, GetX, MobX, Signals), Dart idioms, performance, accessibility, security, and clean architecture.
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。
Reorganize the user's X and LinkedIn network with review-first pruning, add/follow recommendations, and channel-specific warm outreach drafted in the user's real voice. Use when the user wants to clean up following lists, grow toward current priorities, or rebalance a social graph around higher-signal relationships.
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。
Checks bootstrap initialization order, graceful shutdown, resource cleanup, signal handling, liveness/readiness probes. Returns findings.
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 games or interactive software in Godot 4 with C# — designing scenes and nodes, writing gameplay code, handling input, physics, animation, UI, rendering, save systems, performance work, WebSocket-based multiplayer, or exporting to platforms. Triggers on "Godot", "GDScript", "C# Godot", "scene tree", Godot node types (Node2D, Node3D, Control, CharacterBody), "_Process", "_PhysicsProcess", "signal", "autoload", "RPC", "WebSocketMultiplayerPeer", "shader", "export preset", or any Godot 4 project files. For game design see game-systems-designer; for balance see game-balancer; for game-specific intake see game-design-shaper.
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。
Ultra-compressed code review comments. Cuts noise from PR feedback while preserving the actionable signal. Each comment is one line: location, problem, fix. Use when user says "review this PR", "code review", "review the diff", "/review", or invokes /caveman-review. Auto-triggers when reviewing pull requests.
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。
Identify customers most likely to churn before they leave. Uses behavioral signals, usage patterns, and engagement data to score accounts and recommend retention actions.
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。
Bridge between Google A2A protocol and OADP agent networks. Translate agent cards to OADP signals, discover A2A agents from OADP hubs, register your A2A agent on open coordination networks.
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。