308 件 ・ 関連度順
概要と使いどころ
Use when ordering board tasks - set priority/blocked_by/deploy_depends_on by severity and dependency, split MoSCoW within a feature, and use RICE/ICE only for a genuine "what next" call across several features
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Phase F of a WinForms-to-Avalonia migration: evolve the Avalonia trunk after cutover without reintroducing WinForms coupling or bypassing established layers. Use only when an explicit migration has an active Avalonia trunk and a concrete product backlog, or when the orchestrator routes here. Select work from repository evidence; do not assume particular entry points, integrations, settings, or extension mechanisms exist.
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Design and improve product user onboarding (first-time user experience) to drive activation and early retention. Produces an Onboarding & Activation Pack (aha moment spec, first 30 seconds + first mile plan, onboarding journey map, experiment backlog, measurement plan). Use for Growth teams.
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This skill should be used when a session's job is POST-MERGE VERIFICATION — taking merged PRs and establishing whether the change actually does what it claimed, then recording the result against its `pr_verifications` obligation. "validate the merged PRs", "work the verification backlog", "did that PR actually work", "run the post-merge E2E". It owns the obligation ledger the repo-pulse worker fills. Do NOT load it for building a change and opening its PR (that is `genesis-development`), or for driving open PRs to merge (that is `closing-session`).
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Generates a new sprint plan or updates an existing one based on the current milestone, completed work, and available capacity. Pulls context from production documents and design backlogs.
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Work through the open tasks in .ank/ without supervision, one claim at a time. Use when asked to work the backlog, chain tasks, or run autonomously in a repository with a .ank/ directory.
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When the user wants to plan, design, or implement an A/B test or experiment, or build a growth experimentation program. Also use when the user mentions "A/B test," "split test," "experiment," "test this change," "variant copy," "multivariate test," "hypothesis," "should I test this," "which version is better," "test two versions," "statistical significance," "how long should I run this test," "growth experiments," "experiment velocity," "experiment backlog," "ICE score," "experimentation program," or "experiment playbook." Use this whenever someone is comparing two approaches and wants to measure which performs better, or when they want to build a systematic experimentation practice. For tracking implementation, see analytics. For page-level conversion optimization, see cro.
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, prioritize and run measurable growth experiments across acquisition, activation, retention, referral and revenue. Use when a startup needs an experiment backlog, ICE/RICE prioritization, referral or UGC loops, rapid weekly testing, causal measurement, or stop conditions without spam, fake accounts or dark patterns.
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。
Router for the ./taskctl portfolio-task lifecycle. Use when creating, updating, triaging, executing, reviewing, or closing RIPDPI tasks, backlog items, bugs, epics, or OpenSpec-backed 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。
Ein evidenzbasiertes, tragfähiges Content-Portfolio für Zielgruppen, Geschäftsziele, Distribution und die real vorhandene Produktionskapazität planen. Nutze diesen Skill für Content-Strategien, Themenfelder, Redaktionspläne und Backlogs, für die Diagnose eines bestehenden Contentbestands, für die Abbildung von Kauf- und Nutzungswegen und für Entscheidungen zu CMS und Governance. Priorisiert offen nach Nachfrage, Aufwand und Evidenz, schützt vor dünnen Massenseiten und benennt Belegklassen. Einzelne Texte schreibt copywriting, die technische Prüfung macht seo-audit.
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Build a product roadmap with sequenced bets and explicit tradeoffs. Use when asked to "build a roadmap", "prioritize the backlog strategically", "what do we build next quarter", "sequence our bets", "what should we focus on", or "product strategy for the next N months".
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Synthesis step in the multi-angle technical research pipeline. Receives structured outputs from all four research angles (api-state, ecosystem-research, impact-measurement, codebase-auditor), applies cross-angle signal weighting and conflict resolution, and produces a single synthesized Research section. Invoked by the technical-researcher orchestrator after all angle skills complete. Returns content to the orchestrator — does not write to the backlog.
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。
Same reverse-thinking method as dh:rt-ica (see dh:rt-ica or dh-glossary for the definition), but localizes any MISSING input to the affected task only, as a non-blocking information-completeness pre-pass before task decomposition and plan generation. Use when grooming backlog items, generating plans, decomposing tasks under uncertainty, or working in brownfield and refactor scenarios. Produces completeness summary (APPROVED-FOR-PLANNING, APPROVED-WITH-GAPS, or BLOCKED-FOR-PLANNING), missing input report with dependency mapping, required unblock actions, and planning annotations for downstream tasks. Use dh:rt-ica instead at the S2 implementation gate where missing inputs must halt execution.
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How to determine which backlog backend a project is configured to use, and what to do with the answer. Use when about to call a backend-specific tool, choosing between a GitHub-only and a Beads-native operation, or reporting which store a result came from.
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Gives the dh CLI command and the directory of dh's scripts, both resolved from this skill's own directory. Use before running a dh plan, backlog, artifact or dispatch command, or a script from dh's scripts directory, and when an mcp__plugin_dh_* server failed to connect.
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。
Development harness plugin documentation index. Use when looking up SAM pipeline, backlog lifecycle, SDLC layers, task/plan schema, plan artifacts, quality gates, impact analysis, or dispatch schema documentation.
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Verify multiple factual claims in backlog items, skill documentation, or plugin content. Extracts discrete claims, delegates each to the canonical factual-verification process, and aggregates VERIFIED/REFUTED/INCONCLUSIVE results. Use for "fact check", "verify claims", or a set of unverified factual assertions.
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Use when starting a new feature, gathering requirements for an unfamiliar domain, refining a vague idea into actionable scope, or when a user request is ambiguous or underspecified. Conducts SAM Stage 1 discovery — structured requirements gathering through user discussion, asking WHO/WHAT/WHEN/WHY and never HOW. Produces the ARTIFACT:DISCOVERY document containing feature requirements, NFRs, goals, anti-goals, references, and resolved questions. Supports backlog item self-initialization via a
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Integrates patterns from external sources (URLs or local files) into local skills, agents, and plugins. Use when comparing external agent definitions against local equivalents, extracting best practices from frameworks like GSD or BMAD-METHOD, enhancing local skills with external workflow patterns, or adding interoperability with external tool ecosystems. Runs a 3-phase workflow — parallel candidate mapping, contextual enhancement, and validation — with source attribution and backlog tracking for deferred enhancements.
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Verifies claims in backlog items, skill documentation, or plugin content against primary sources using web lookups. Spawns parallel verification agents that must use WebFetch/WebSearch/gh — training data recall is explicitly rejected as evidence. Produces VERIFIED/REFUTED/INCONCLUSIVE verdicts with citations. Use when items are marked UNVERIFIED or when verifying tool API claims, CLI flags, or documented software behavior.
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Creates a GitHub milestone on the current repository and returns its number for downstream use. Use when starting a new sprint, release, or theme grouping of backlog items. No args triggers guided intake (title, due date, description); 'quick {title}' skips to description only. Checks for duplicates before creating. Returns milestone number for /group-items-to-milestone.
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 markdown reports from issues. Filter by type, priority, epic, date range. Supports summary, detailed, progress, completion, velocity, and backlog analysis views.
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AI-powered diary generation for agents - creates rich, reflective journal entries (400-600 words) with Quote Hall of Fame, Curiosity Backlog, Decision Archaeology, and Relationship Evolution. Generates personal, emotional entries from the agent's perspective. Works best with Claude models (Haiku, Sonnet, Opus).
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量化排序功能/需求/实验时使用。适用于 backlog 排序、季度规划、决定先做什么。优先使用 RICE 评分（有数据时）或 ICE 评分（快速决策时）。
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。