523 件 ・ 関連度順
概要と使いどころ
Apply during planned rewrites and migrations with explicit phase boundaries. Converge on the target architecture; don't preserve smooth intermediate states with throwaway compatibility code.
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。
Calculate the relative contribution of different factors to a response variable using R² decomposition. Use when you need to quantify how much each factor explains the variance of an outcome.
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。
Apply during planned rewrites and migrations with explicit phase boundaries. Converge on the target architecture; don't preserve smooth intermediate states with throwaway compatibility code.
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。
Deciding what to build or why adoption fails. Recover the progress users hire a solution for under a circumstance, then rank by outcome and competing workarounds.
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。
Prepare a sourced Minutes meeting outcome for human-governed closeout of existing X1 work. Use when the user wants a meeting decision or commitment to close, defer, escalate, or retire a specific X1 coordination thread. Never use it to infer settlement, move money, contact anyone, or close X1 work automatically.
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。
Post-meeting debrief — analyzes what happened, compares outcomes to your prep intentions, tracks decision evolution. Use when the user says "debrief", "what just happened in that meeting", "what did we decide", "debrief that call", "post-meeting", "what changed", or right after stopping a recording.
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。
Experiment design reference for problem-class framing, Minimum Viable Experiment coaching, hypothesis formation, vetting and red flags, and experiment readiness. Use when translating a stated business outcome into candidate data-science problem classes, or when framing, vetting, scoping, or evaluating an experiment of any kind, including data feasibility, architecture, LLM, performance, use-case, UX, prototyping, and hardware experiments.
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 durable data and ML feasibility studies using the Feasibility Study Interchange Profile, constrained YAML authority, UUID URN identity, lifecycle lineage, and evidence traceability. Use when assessing whether available data and technical evidence support a proposed outcome.
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。
Continues interrupted Codex work only after read-codex-history verifies rollout identity and fork/compaction lineage — restores the original outcome, unfulfilled requests, and the next action. Use when given a Codex Session ID, asked to pick up a prior Codex run, told Codex was interrupted, fused, compacted or stuck, or asked to take over without `codex resume`. Not for a conversation Codex already natively resumed.
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。
Continues interrupted Claude Code work after local history is read and reconciled — reconstructs the original outcome, unfulfilled requests, and the next action. Use when given a Claude Code Session ID, asked to pick up prior Claude work, told a run was interrupted or compacted, or asked to take over without `claude --resume`. Not for Codex sessions (use continue-codex-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。
Transforms vague prompts or feature requests into precise, testable specifications using EARS (Easy Approach to Requirements Syntax) grounded in relevant domain theories (GTD, BJ Fogg, Gestalt). Use when requirements lack triggers or measurable outcomes, or the user asks to "optimize my prompt" / "improve this requirement" / "make this more specific".
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 a client case study that sells future work — challenge, approach, results. Use when asked to write a case study, a client success story, a project write-up, or a portfolio case for consulting/agency work. Produces a results-led case study — the client & challenge, your approach, quantified outcomes, a client quote slot, and a takeaway — structured to win the next client. Ready to export as a designed PDF.
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。
Redesign seat-based pricing for the agent era — when one human runs ten agents, per-seat models collapse. Use when agents are eroding seat counts, when asked to migrate to usage- or outcome-based pricing, to price an agent/API tier, or to defend revenue as customers automate their own usage. Produces a pricing migration plan: the new value metric, fences, agent-tier design, cannibalisation math, and a phased migration for existing customers. For general pricing and packaging strategy use pricing-strategy.
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。
Eval and improve a skill against golden cases — run the target skill blind in a fresh, context-free subagent on each example input, grade the artifact against the expected outcome, and let the gaps drive the edits. Use when the user wants to test/eval/improve/harden a skill, says "this skill keeps producing X / keeps missing Y", or hands a skill plus example input→expected-output pairs. Pairs with [write-skills](../write-skills/SKILL.md) (the authoring principles every fix obeys).
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 for VidSeeds MCP analytics and research - YouTube analytics, channel intelligence, video autopsy, outliers, competitors, trending/breakout discovery, keyword research, comment sentiment, and best-practices tools. Outcomes only; not internal scoring details.
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。
Interview you one question at a time, each with a recommendation, to settle a big outcome before agents work alone. Use when: selected by name.
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。
Simplify code, plans and systems without losing required outcomes; delete machinery that earns nothing; for code, AST-measured complexity with regression gates. Triggers: simplify, refactor, complexity, overengineered, dead code, useless guard.
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Guide real-build acceptance: literal taps, real inputs, expected outcomes, worst case first, one sitting. Triggers: testflight, human pass, acceptance test, before we ship, what should I test, release checklist, device test.
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 Agiflow task into an unambiguous, testable specification without expanding its intended outcome. Use when a task is vague, lacks acceptance criteria, has unclear scope or dependencies, or is not ready for backlog grooming.
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 Waggle automatically as portable, local project memory during meaningful coding work; retrieve prior decisions and constraints, then store only durable outcomes.
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 explaining or planning around AISTATS peer review, OpenReview review release, author-reviewer discussion, reviewer volunteer expectations, reviewer confidentiality, decision criteria, meta-review dynamics, the statistician-heavy reviewer pool, and PMLR proceedings outcomes.
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Use when targeting Agriculture, Ecosystems & Environment or deciding whether an agroecosystem-environment manuscript fits this venue. Encodes the journal's fit, the field-to-landscape environmental-outcome bar, data-reporting expectations, house style, official-submission re-check, and desk-reject heuristics.
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 explaining or planning around ACM CCS peer review, the two-cycle HotCRP workflow, decision categories including minor revision, the rebuttal window, the adversarial reviewer pool, ethics and disclosure scrutiny, meta-review dynamics, and ACM proceedings outcomes.
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 reasoning about how an ACL paper travels through ACL Rolling Review and conference commitment, covering reviewer and area-chair roles, meta-reviews, the commitment decision by senior area chairs and program chairs, Findings versus main-conference outcomes, ethics review escalation, and resubmission strategy across cycles.
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。