1,862 件 ・ 関連度順
概要と使いどころ
When a GDD is revised, scans all ADRs and the traceability index to identify which architectural decisions are now potentially stale. Produces a change impact report and guides the user through resolution.
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。
Validates completeness and consistency of the project architecture against all GDDs. Builds a traceability matrix mapping every GDD technical requirement to ADRs, identifies coverage gaps, detects cross-ADR conflicts, verifies engine compatibility consistency across all decisions, and produces a PASS/CONCERNS/FAIL verdict. The architecture equivalent of /design-review.
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。
Translate approved GDDs + architecture into epics — one epic per architectural module. Defines scope, governing ADRs, engine risk, and untraced requirements. Does NOT break into stories — run /create-stories [epic-slug] after each epic is created.
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。
Walk the causal graph in AgentDB to explain why two memories are connected, or trace a root cause. Use when the user asks "why did X happen", "what led to Y", or after an incident.
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。
Analyzing session replays, extracting persona-based behavioral patterns, and storytelling UX issues. Reads the 'why' from real user operation logs. Works with Field/Echo for persona validation.
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。
Authoring standalone and cross-team specifications: PRD/SRS/HLD/LLD, staged L0-L4 unified packages, BDD acceptance criteria, and traceability. Use for technical or multi-audience documentation; not implementation or architecture decisions.
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。
Verifying spec compliance: extracts ACs from specs, adversarially checks conformance, generates BDD scenarios and traceability matrices. Use when impl must be proven to match a PRD/SRS/AC.
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。
Diagnosis loop for bugs and failing behavior. Use for errors, stack traces, regressions, failed tests, issue-tracker bugs, stuck investigations after failed fixes, or asks to debug/fix a bug.
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 test-driven development for behavior-changing feature or fix work, and whenever the user mentions TDD, test-first, red-green-refactor, tracer bullets, integration tests, or public-interface behavior tests. Skip for docs-only, path-only rename, formatting-only, or purely mechanical chores unless explicitly requested.
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。
Deepfake detection and media safety — detect AI-generated audio, images, video, and text, trace synthesis sources, analyze media intelligence, and tell people from AI agents on a website (Agent Detection) using direct Resemble AI API calls
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。
Root cause analysis for bugs and unexpected behavior. Traces errors through code, uses structured reasoning, and hands off to fix when cause is found. Core of the debug↔fix mesh. When the diagnosed cause is a memory leak in a long-running process, escalates to perf for cost-impact framing (leaks drive OOM-restart → cold-start → autoscaler spend, often 20-40% bill inflation).
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。
Analyze repo, detect stack, trace changes to user-facing entry points, generate E2E YAML test plan
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。
Reviews BubbleTea TUI code for proper Elm architecture, model/update/view patterns, and Lipgloss styling. Use when reviewing terminal UI code using charmbracelet/bubbletea.
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。
Go application architecture with net/http 1.22+ routing, project structure patterns, graceful shutdown, and dependency injection. Use when building Go web servers, designing project layout, or structuring application dependencies.
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。
Go concurrency patterns for high-throughput web applications including worker pools, rate limiting, race detection, and safe shared state management. Use when implementing background task processing, rate limiters, or concurrent request handling.
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。
Reviews Wish SSH server code for proper middleware, session handling, and security patterns. Use when reviewing SSH server code using charmbracelet/wish.
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 BubbleTea TUI code review for terminal applications. Use when reviewing charmbracelet/bubbletea, lipgloss, bubbles, or Wish SSH code; optionally reviews each area concurrently.
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。
Diagnose problems before solving them: turn "X is broken and we don't know why" into a precise problem statement, verified root causes, solutions traced to those causes, and a rollout plan. Use whenever the user reports something failing, breaking, slowing, or recurring without a known cause: "sales dropped and we don't know why", "this keeps happening", "why does X keep failing", "find the root cause", "run a post-mortem", "5 whys"; Vietnamese "sao cứ bị vậy hoài", "tìm nguyên nhân gốc", "X đang hỏng mà không rõ vì sao". Trigger even when the user asks for solutions directly: "give me ideas to fix falling sales" is a diagnosis request. Not for open-ended ideation when nothing is broken (brainstorm-coach), understanding user needs (design-thinking), or company-level strategic bets (strategy-board).
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 ticket triage system -- routing rules, priority tags, queue structure, and first-response automation. Use when asked to "design our ticket routing", "how should we tag tickets", "set up our helpdesk", or "reduce time to first response".
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 customer support onboarding flow -- first-contact experience, proactive support touchpoints, and setup success checklist. Use when asked to "design our onboarding support", "how do we support new customers during onboarding", or "reduce early churn from setup failures".
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 or audit knowledge base -- article structure, coverage gaps, deflection rate, and maintenance process. Use when asked to "build a knowledge base", "what docs are missing", "improve our self-serve rate", or "audit our help center".
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 support metrics dashboard -- CSAT, FRT, TTR, ticket deflection rate, volume trends, and agent efficiency. Use when asked to "what metrics should support track", "build our support dashboard", "measure support quality", or "audit our support performance".
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。
Support operations reconnaissance -- audit current ticket volume, SLA compliance, knowledge base coverage, escalation paths, and CSAT to understand where support is the constraint. Use when asked to "audit our support", "why is our response time bad", "how healthy is our support operation", or "before designing a support system".
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 SLA framework -- response time targets, resolution time targets, tier definitions, and breach escalation process. Use when asked to "define our SLAs", "what response times should we commit to", "build a support tier structure", or "set up SLA monitoring".
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。