「bi」の検索結果

Use when running the dev Grafana stack and/or the Playwright e2e suite against a *packaged* plugin zip (a release/RC artifact like `hydrolix-hydrolix-datasource-<ver>.zip`) rather than the working-tree `dist/`. Unpacks the package into a timestamped `dist_<timestamp>/dist` sandbox alongside copies of the compose artifacts, so the run is reproducible and the folder stays available to experiment with afterwards. Delegates stack bring-up to `stack-run` (frozen mode: read-only mount + `DEV=false` so the mage-watcher can't rebuild the packaged Go binary), verifies signature/version, runs the suite, and treats cleanup as optional — the sandbox is deleted only with the user's approval. Apply whenever the task is "test this plugin package / zip" or "run e2e against the built 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。

Collect this machine's local Claude Code conversation data with the asz collector. Resolves the local Claude data directory (honouring CLAUDE_CONFIG_DIR and XDG_CONFIG_HOME), builds the binary, lists what is discoverable, and lands everything into the storage root. Use when asked to collect, backfill, re-collect, or inspect local Claude Code sessions, or to check what the collector can see.

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。

Act as FriendlyBet's CEO and primary front door for every FriendlyBet request through automatic company preflight. Own end-to-end routing, planning, execution coordination, department orchestration, decision-rights enforcement, quality gates, board-style reporting, and escalation only for strategic, legal, brand, cost, risk, or taste decisions. Use by default in FriendlyBet threads, with full department planning for broad, ambiguous, strategic, cross-functional, or outcome-driven requests such as SEO, new features, multi-sport expansion, product direction, release execution, company operations, or agent coordination.

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 FriendlyBet operating cost, free-tier viability, provider/API cost, GitHub Actions/Supabase/Vercel usage, documentation hygiene, company memory updates, playbook maintenance, and skill validation. Use when evaluating cost, operational burden, tooling, internal docs, company memory, or whether agent profiles should become full skills.

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。

Shape FriendlyBet Pundit content, bilingual product copy, community voice, share-card copy, social moments, video briefs, Hebrew/English wording, and group-chat friendly communication. Use when a task touches copy, Pundit tone, social videos, share text, community loops, or public-facing FriendlyBet voice.

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。

Scoring rubrics for all 5 pipeline layers (Vision, Architecture, IA, BE, FE). Use when auditing specs, running self-checks, or remediating ambiguity gaps.

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 backend spec production from completed IA shards through classify and write passes with mandatory ambiguity gates

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。

Author FE spec files, update indexes/tracker, run deepening and ambiguity gates, and enforce navigation completeness before plan-phase handoff

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 iterative IA deepening, finalize shard, update indexes/tracker, and enforce ambiguity gates before handoff

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。

Author and validate BE spec files, update indexes/tracker, run deepening and ambiguity gates, and enforce allowed next-step transitions

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 IA shard authoring via design and deepen passes, with pipeline-state-driven shard selection and ambiguity gates

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 production-readiness gates with applicability control, consolidate validation report, and issue final readiness verdict

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 error handling patterns across languages including exceptions, Result types, error propagation, and graceful degradation to build resilient applications. Use when implementing error handling, designing APIs, or improving application reliability.

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。

Comprehensive advanced Git patterns guide covering interactive rebase, cherry-pick, bisect for bug hunting, worktrees, reflog for recovery, stash management, submodules vs subtrees, hooks (pre-commit, commit-msg, pre-push), conventional commits, merge strategies, branch naming, git attributes (LFS, diff drivers), blame/log archaeology, patch workflow, sparse checkout, filter-repo, signing commits, and performance optimizations. Use when performing complex Git operations beyond basic add/commit/push.

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。

Universal AI design correction rules — SUPERSEDED. The `impeccable` skill now provides 27 deterministic anti-pattern rules plus a 12-rule LLM critique pass, which are more comprehensive and runtime-enforced via the `impeccable` CLI. This file is kept for backward compatibility — the `impeccable` skill's design laws and anti-patterns take precedence.

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。

Helps users discover and install agent skills when they ask questions like "how do I do X", "find a skill for X", "is there a skill that can...", or express interest in extending capabilities. This skill should be used when the user is looking for functionality that might exist as an installable skill.

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 direction interview methodology — SUPERSEDED. The `impeccable` skill's `/impeccable teach` command now handles design direction discovery with a more comprehensive, multi-round interview that writes PRODUCT.md and DESIGN.md. This file is kept for pipeline backward compatibility — all new design work should use `/impeccable teach` 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。

Implement structured logging with JSON formats, log levels (DEBUG, INFO, WARN, ERROR), contextual logging, PII handling, and centralized logging. Use for logging, observability, log levels, structured logs, or debugging.

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。

Deep code analysis covering security, performance, maintainability, and best practices

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。

Define security, attack surface, integration, and observability architecture with compliance escalation

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。

Smart Kotlin unit testing with auto-detection, coverage analysis, and AI edge cases. Use when generating tests for biz/ layer classes, analyzing test coverage gaps, or discovering edge cases.

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 a single Jetpack Compose @Composable function. Use when the user wants to improve, polish, animate, or refactor ONE Composable — keywords like "optimize this composable", "make this smoother", "add animation to this", "split this composable", "fix recomposition", "this composable is laggy", "polish this UI", or when user pastes/points to a single @Composable function. Analyzes the target for recomposition issues, missing animations, size/concern splits, and stability problems, then iterates with the user via AskUserQuestion to pick which optimizations to apply, then delegates implementation to the kta-compose-developer agent and summarizes changes. Input MUST be exactly one Composable (file path + function name, or function name alone).

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 this skill when working on login, logout, session restore, tokens, route guards, or any authentication and authorization behavior.

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 this skill when working on push notifications, FCM topics, device tokens, or notification-tap navigation.

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。