517 件 ・ 関連度順
概要と使いどころ
Reconstructs the development cycle from git history, distills sequential/parallel patterns, and produces actionable insights for improving future iterations. Triggers: recall, retrospective, development analysis, what happened, dev cycle 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。
Audit a codebase for product-market fit readiness -- evaluate startup PMF signals, core value loop tightness, feature scatter vs focus ratio, user activation funnel friction, retention hook infrastructure, pricing flexibility, analytics event coverage, CI/CD iteration speed, and growth-stage maturity for pre-seed through Series A products.
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。
Delegate tasks to ANY CLI agent (claude, codex, aider, ...) running in a detached tmux session, with a race-safe done-signal protocol and multi-turn iteration. Use when delegating work to a non-Claude CLI agent, when the user says "tmux delegate", "run agent in tmux", "delegate to codex/aider", or when executor work should run in an observable background terminal instead of the Agent tool.
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。
Orchestrate AI coding agents (Claude Code, Codex, OpenCode) in isolated sandboxes using the @ai-hero/sandcastle SDK. Use when the user needs to (1) run agents AFK in Docker/Podman containers, (2) build multi-agent pipelines with plan-execute-review patterns, (3) run parallel agents on separate worktrees, (4) create iterative agent loops with maxIterations, (5) extract structured output from agent runs, (6) set up sandcastle in a new or existing project, or (7) write prompt files with template args and shell expressions.
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 task iteratively over a user-specified duration by dispatching subagents. The orchestrator stays strictly linear and time-checked, but each iteration fans out MULTIPLE subagents in parallel over independent units (and those subagents may fan out further). Shared state — a compact progress digest and a growing environment cheatsheet — lives on disk and is passed to every subagent BY REFERENCE, killing the per-subagent rediscovery tax. Every subagent first reads an initialiser preamble that points it at that shared state and makes it write findings back, so the cheatsheet populates itself; role prompts are produced ONCE on the filesystem by a single scaffold command and dispatched by path, never re-typed per dispatch. Subagents persist their results to disk and return only a tiny status, so the orchestrator's context stays small and lasts. The orchestrator classifies the goal as FINITE or OPEN-ENDED: finite lists may finish early; open-ended goals use the full duration, never idle, never manufacture busywork. Use when the user gives a task and a duration and wants it ground out iteratively by subagents over that time.
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。
Refine an existing implementation plan with a second iteration. Re-analyzes the codebase for gaps, missing tasks, and wrong dependencies. Use after /unikit-plan or to improve a /unikit-fix plan, or when the user says "improve the plan", "what's wrong with the plan", or "update the plan from research". Optional +check flag validates refinements via a fresh-context subagent.
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。
Autonomous comprehensive refactoring. Three-phase pipeline — Phase 1 /refactor (tactical, loops internally to convergence) → Phase 2 loop of /review-arch + /implement-batch until architectural findings converge below a severity floor (default HIGH+) → Phase 3 /refactor (catches tactical issues introduced by restructuring). Auto-approves /review-arch ticket proposals; pulls the andon cord on contested findings, breaking-change proposals, repeated implementation failure, or Phase-2 hard-cap exhaustion (5 architectural iterations).
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 wants to design, redesign, shape, critique, audit, polish, clarify, distill, harden, optimize, adapt, animate, colorize, extract, or otherwise improve a frontend interface. Covers websites, landing pages, dashboards, product UI, app shells, components, forms, settings, onboarding, and empty states. Handles UX review, visual hierarchy, information architecture, cognitive load, accessibility, performance, responsive behavior, theming, anti-patterns, typography, fonts, spacing, layout, alignment, color, motion, micro-interactions, UX copy, error states, edge cases, i18n, and reusable design systems or tokens. Also use for bland designs that need to become bolder or more delightful, loud designs that should become quieter, live browser iteration on UI elements, or ambitious visual effects that should feel technically extraordinary. Not for backend-only or non-UI tasks.
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 users through a structured workflow for co-authoring documentation. Use when user wants to write documentation, proposals, technical specs, decision docs, or similar structured content. This workflow helps users efficiently transfer context, refine content through iteration, and verify the doc works for readers. Trigger when user mentions writing docs, creating proposals, drafting specs, or similar documentation tasks.
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 marketing ad images using Nano Banana Pro (Gemini 3 Pro Image). Accepts campaign-planner creative briefs, reads brand bible for visual style, constructs marketing-optimized prompts, and produces platform-ready images at correct aspect ratios. Supports 1:1, 9:16, 16:9, 4:5 formats. Includes self-review loop to catch hallucinated logos, wrong text, and quality issues. Draft-first workflow (1K fast iteration, 4K final). Outputs to /tmp/marketing/assets/images/.
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。
Execute iterative improvement workflow for QuantConnect strategies. Arguments: [strategy|issue#] [--iterations=N] [--no-backtest] [--commit]
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。
Autonomously improve one measurable metric via bounded, git-tracked iterations: one scoped change, verify, keep or revert. NOT for cleanup (mk:cook), known-cause bugs (mk:fix), or shipping (mk:ship).
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。
Reflect subskill for simmer. Records iteration results in trajectory table, tracks best candidate, handles regression rollback, and passes ASI forward to the next round. Supports both single-file and workspace modes. Do not invoke directly — called by simmer orchestrator after each judge round.
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 interactive HTML/web visualizations with plotly (Python/R), bokeh (Python), and gganimate/plotly frames for animation, with awareness of current Kaleido static-export model (post-orca-EOL), HTML file-size bloat, and the limits of interactive-only output for journal submission. Use when producing zoomable/hoverable plots for notebook EDA, supplementary HTML, dashboards, or animated time-course / iteration visualizations.
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。
Write the production code that makes a pre-decided set of failing tests pass, within an explicit write_set, following an explicit behavior contract. Used by `/tdd` Step 3 and by `/swarm-dispatch` workers. The caller has already decided architecture, naming, file layout, and abstraction boundaries — this skill executes that recipe with code-structure discipline and a 5-iteration RALPH loop. No scope expansion, no design decisions, no test edits.
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 wants to design, redesign, shape, critique, audit, polish, clarify, distill, harden, optimize, adapt, animate, colorize, extract, or otherwise improve a frontend interface. Covers websites, landing pages, dashboards, product UI, app shells, components, forms, settings, onboarding, and empty states. Handles UX review, visual hierarchy, information architecture, cognitive load, accessibility, performance, responsive behavior, theming, anti-patterns, typography, fonts, spacing, layout, alignment, color, motion, micro-interactions, UX copy, error states, edge cases, i18n, and reusable design systems or tokens. Also use for bland designs that need to become bolder or more delightful, loud designs that should become quieter, live browser iteration on UI elements, or ambitious visual effects that should feel technically extraordinary. Not for backend-only or non-UI tasks.
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。
Power batch-sprint helper — hosts the two behaviours that distinguish the `power` workflow track from spec-entry. (1) Per-ticket iteration: security runs once PER TICKET over workflow.json.tickets[] while the mechanical phases run once for the batch. (2) Commit split: at the commit phase, group the batch's working tree into ordered Conventional Commits via commit-split.mjs, closure last. Invoked within a `power`-track workflow; not a standalone feature. Opt-in via velocity.power_mode.enabled; requires git.
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 AI Text Translation SDK for real-time text translation, transliteration, language detection, and dictionary lookup. Use for translating text content in applications.
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。
Systematic improvement of existing agents through performance analysis, prompt engineering, and continuous iteration.
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。
Local-only regression / benchmark skill for ui-clone-skills maintainers. Drives the standard ui-reverse-engineering pipeline against the canonical reference site (https://realfood.gov) and records AE/SSIM, iteration count, gate fail counts, and outcome to benchmark/history.csv so prompt / sub-doc / model-version drift surfaces as a trend. Trigger phrases: "run benchmark" / "regression benchmark" / "benchmark clone". The Makefile no longer has a `benchmark` target — setup is inline bash in this skill (Step 1 below). Internal: NOT registered in `.claude-plugin/plugin.json` `skills`. Not part of the public 3-skill marketplace surface. Maintainer tooling 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。
Generate beautiful, on-brand HTML artifacts — reports, diagrams, diff reviews, slide decks, plans, recaps, dashboards. Loads on creation intents ("create a plan", "make me an implementation plan", "generate a diagram", "build a slide deck", "draft a recap", "visualize this", "render this as HTML", "make me a status update") and exploration intents ("show me three layouts", "explore document shapes", "compare visual treatments", "explore a new design system", "compare replacement brand directions") and iteration intents ("make this beautiful", "polish this report", "make this less generic", "design this", "theme this", "use my brand", "iterate on this design", "review this artifact", "make this bolder", "make this quieter", "simplify this design", "animate this", "improve the look of", "give this a refresh"). Captures brand from the user's codebase, asking, or live site, then applies it to every artifact.
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。
Frontend UI design, critique, audit, polish. Use when the user wants to design, redesign, shape, critique, audit, polish, clarify, distill, harden, optimize, adapt, animate, colorize, extract, or otherwise improve a frontend interface. Covers websites, landing pages, dashboards, product UI, app shells, components, forms, settings, onboarding, and empty states. Handles UX review, visual hierarchy, information architecture, cognitive load, accessibility, performance, responsive behavior, theming, anti-patterns, typography, fonts, spacing, layout, alignment, color, motion, micro-interactions, UX copy, error states, edge cases, i18n, and reusable design systems or tokens. Also use for bland designs that need to become bolder or more delightful, loud designs that should become quieter, live browser iteration on UI elements, or ambitious visual effects that should feel technically extraordinary. Not for backend-only or non-UI tasks.
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。
Publishes HTML or Markdown as display.dev URLs with public, company, or private access. Supports signup, claiming, sharing, browsing, bounded reads, exact edits, and comment iteration. Use when the user asks to "publish this", "share this", "share with the org", "post this online", "make a private link", "share with [email]", "publish a report", "list my artifacts", "find an artifact", "publish a large file", "publish this generated HTML file", "read this artifact", "search inside this artifact", "change this passage", "make a copy of this artifact", "duplicate version", "create a display.dev account", "claim this publish", "add a company email domain", "transfer an email domain", "change the email domains add-on", "show my referral link", "show referral rewards", "watch comments on this artifact", "respond to comments", or "resolve this comment thread". Use whenever a request contains a display.dev artifact URL (`*.dsp.so/*`). Anonymous publishing returns a 30-day preview and browser claim URL.
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 leakage-safe machine learning experiments that mirror real deployment and support fair model comparisons. Use when defining prediction timing, feature eligibility, train-validation-test splits, baselines, metrics, or controlled model iterations; not for auditing whether raw labels are trustworthy.
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。