配送の遅延・破損・紛失・数量不足に対し、証拠収集から補償請求、運送会社との交渉までを整理し、損失額や顧客への影響に応じた対応判断を支えるスキル。
- 配送の遅延や紛失に対応したいとき
- 貨物破損の補償請求を準備したいとき
- 運送会社の料金や責任を争うとき
803 件 ・ 関連度順
概要と使いどころ
配送の遅延・破損・紛失・数量不足に対し、証拠収集から補償請求、運送会社との交渉までを整理し、損失額や顧客への影響に応じた対応判断を支えるスキル。
AIエージェントの反復作業を設計・点検し、機械で判定できる完了条件、変更禁止の境界、独立した検証、再試行上限を定めて空回りや暴走を防ぐスキル。
Webサイトや業務画面の目的・利用者に合うデザイン方針を定め、文字・配色・レイアウト・動きを整えます。既存の部品を生かし、画面幅ごとの表示も確認します。
Claude Codeの終了時に学習記録の更新日時やディスク空き容量を確認し、条件に応じて完了を止めるスキル。会話中の手順省略を示す表現にも警告します。
For product and technical management work: turn PRDs, roadmaps, RFCs, architecture reviews, and retros into decision documents. Built around the core query "pm-feature-business-case-deck", with product strategy lead judgment, buyer-ready proof, and this outcome: approve the feature, architecture, roadmap, or incident follow-up.
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。
For consulting delivery work: turn diagnosis, frameworks, and project work into a client-adoptable action plan. Built around the core query "consulting-final-deck", with engagement manager judgment, buyer-ready proof, and this outcome: accept the recommendation and commit owners to the roadmap.
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。
A designer's portfolio narrative for a senior interview — three case studies, the craft, and the judgment behind each. Built as a decision-grade career deck for hiring panel.
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。
For marketing and gtm work: bind launches, campaigns, events, and brand plans to growth and pipeline outcomes. Built around the core query "annual-marketing-plan", with GTM strategy lead judgment, buyer-ready proof, and this outcome: approve launch plan, campaign budget, or GTM motion.
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 ReasoningBank adaptive learning with AgentDB's 150x faster vector database. Includes trajectory tracking, verdict judgment, memory distillation, and pattern recognition. Use when building self-learning agents, optimizing decision-making, or implementing experience replay systems.
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 ReasoningBank adaptive learning with AgentDB's 150x faster vector database. Includes trajectory tracking, verdict judgment, memory distillation, and pattern recognition. Use when building self-learning agents, optimizing decision-making, or implementing experience replay systems.
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。
Harbor intake for external work — the captain only handles unresolved decisions. Sweeps incoming issues and PRs, verifies every claim before disposition, reuses every decision already made, and hands the maintainer a docket whose pending items each carry one question with options, recommendation, impact and evidence. Agent-autonomous for facts and for actions covered by standing authorization; signed for every new judgment. Never merges.
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。
Lift a proven skill from a host repo (e.g. your OpenClaw fork) back into gbrain's bundle so other clients can scaffold it. Editorial workflow: the CLI does the file copy + privacy lint; this skill drives the judgment-heavy genericization (scrub real names, generalize triggers, lift fork-specific conventions to references).
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 a TYPED citation/reference graph over an ingested corpus — not just embeddings. Flat similarity retrieval cannot tell you that document A *overrules* B, *distinguishes* C, or *relies_on* D. This skill extracts every inter-document reference, classifies the edge TYPE with LLM judgment, and writes first-class typed edges via `gbrain link`, so `gbrain graph-query --type` can walk the argument ("everything this brief relies on, minus anything overruled since"). Every cite-heavy corpus is the same shape: law, academic papers, patents, regulatory filings, a book's bibliography.
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 reviewing, approving, or designing commercial motion — pricing models, deal review, discount approval, partnership economics, channel mix, commercial policy, RFP/RFI response, bookings forecast. Triggers on "review this deal", "should we discount", "pricing model", "partner economics", "RFP response", "bookings forecast", "channel mix". Forks context to route to one of seven Commercial sub-skills (pricing-strategist, deal-desk, partnerships-architect, channel-economics, commercial-policy, rfp-responder, commercial-forecaster) and returns a digest. Distinct from business-growth (sales execution) and c-level-advisor/cro-advisor (strategic CRO judgment).
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。
Applies this repository's skill-authoring standard as a procedure. Use for any change to, or judgment about, a file under skills/** — a SKILL.md, a reference, a persona prompt, a bundled script's instructions: creating a skill, editing one, reviewing a skill change, or acting on review feedback (human or bot) about one. Not for src/, tests/, or scripts/ 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。
Explain how and why something has its current shape, or what happened over a window of work, grounded in evidence. Use when the user asks for an explanation. Use ce-pov for a judgment or recommendation.
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。
Triage loop for inbound HR policy questions. Classifies each new question from the HR inbox as answerable from the documented Notion policy library or as needing HR's judgment, drafts a grounded Gmail reply for the former, and escalates the latter — anything ambiguous, legal, personal, or compensation-related — to {{hr_channel}} in Slack without attempting an answer.
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。
End-to-end test the polly multi-agent coding orchestrator's critical user journeys (CUJs). Two halves — a deterministic mock-LLM driver (polly_cuj.py) that boots a throwaway local server + mock LLM and asserts the substrate (boot, bridged sys_* tool dispatch, the blast_radius / spawn_bounds / headless_subagent_purpose_guard guardrails, fan-out delegation), and a live real-CLI recipe (real claude/codex/pi, real worktrees/PRs) for polly's actual judgment. Load when developing, testing, or debugging examples/polly — its config.yaml, the claude_code/codex/pi sub-agents, the investigate/fanout/cross-review skills, or the omnigent.inner.nessie.policies guardrails — or reproducing a polly orchestration 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。
Close a matter — capture outcome, final exposure, and lessons, then archive it out of the active portfolio without deleting the record. Use when the user wants to close a matter, says "[matter] is done", or needs to record a settlement, dismissal, judgment, withdrawal, or consolidation 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。
Design, build, revise, or QA quantitative charts and figures. Use when an analytical answer needs visual judgment, whether for an inline answer, report, dashboard, notebook, or 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。
Use when a bounded real-world procedure has a deterministic happy path but brownfield, variable, or partially knowable state; when an operation must resume from verified evidence; or when deciding whether agent judgment or ordinary code should own a procedure's control loop.
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 explicitly wants autonomous progress without routine clarification stops: "plow ahead", "do not stop", "use your best judgment", "keep going until done", "finish while I am away", "do not ask questions unless truly blocked", or similar. Convert ordinary ambiguity into stated assumptions, proceed through implementation and validation, stop only for true blockers, and end with a clear recap of decisions, changes, verification, and residual risk.
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。
Experimental workflow for summarizing work that still needs human judgment across configured pull requests, issues, feedback, errors, and delivery signals. Use for a human decision queue or bounded 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。
Implement ReasoningBank adaptive learning with AgentDB's 150x faster vector database. Includes trajectory tracking, verdict judgment, memory distillation, and pattern recognition. Use when building self-learning agents, optimizing decision-making, or implementing experience replay systems.
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。