「each」の検索結果

実装計画をタスクごとに別のエージェントへ任せ、仕様への適合とコード品質を確認しながら進めるスキル。進捗をファイルに記録し、最後に変更全体もレビューします。

• 独立したタスクの実装計画を進めたいとき
• タスクごとに仕様への適合を確認したいとき
• 進捗記録から作業を再開したいとき

計画や仕様、会話を、単独で動作を確認できる小さな開発チケットに分けます。着手順を決める依存関係を明示し、確認後にローカルファイルや課題管理ツールへ登録します。

• 仕様書を開発チケットに分けたいとき
• チケットの依存関係と着手順を整理
• 広範囲の変更を段階的に進めたいとき

TypeScriptのパッケージ内部への直接参照や循環依存を検出し、公開ファイルだけを入口にする構成を、設定・検証・文書化まで整えるスキル。

• パッケージ内部への直接参照を防ぎたいとき
• 型チェックと一緒に境界を確認したいとき
• コピー用のパッケージ雛形を作りたいとき

既存機能の不具合を失敗するテストで再現し、修正、レビュー、承認後のコミットまで、各工程を担当するECCエージェントに割り振って進めるスキル。

• クラッシュや誤った出力を直したいとき
• 不具合の再発を検知するテスト作成
• 原因が分からない不具合の調査

Claude Codeの設定を点検し、重複したスキルや古いメモリ、不要な権限などを整理します。候補ごとに確認し、元に戻せる形で無効化・退避するスキルです。

• 大量追加したスキルの重複を確認したいとき
• 古いメモリや不要なフックの点検
• 重複した権限設定の整理

ボタンやフォームの操作後に状態がどう変わるかを順に追い、共有状態の意図しないリセットや非同期処理の競合で画面が期待どおりに動かない原因を調べるスキル。

• 反応しないボタンの原因調査
• 大規模改修後の共有状態の点検
• 公開前の重要な操作の監査

処理の高速化を、現状の計測、仮説ごとの変更案の比較、正しさの検証へ分解し、時間や費用の上限内で最も速い安全な案と再実行できる手順を残すスキル。

• 遅い処理を計測しながら高速化したいとき
• 同じ入力条件で実装案を比較したいとき
• 応答時間・処理量・実行費用の評価

指定した企業の製品発表、価格変更、資金調達などを定期的に追い、重要な新情報を一次情報のリンク付きでまとめるスキル。同じ出来事の重複や情報源の取得漏れも整理します。

• 競合の重要ニュースを毎週追いたいとき
• 製品発表や価格変更の継続確認
• 資金調達・提携・経営陣の動向確認

Interactive lesson tutor for the AI Engineering from Scratch curriculum. Reads LEARNING.md, fetches the next lesson, teaches it section by section in the terminal, quizzes at the end, and records progress. Works cloned or entirely over raw.githubusercontent.com — no setup required. Trigger phrases: "next lesson", "teach me", "continue the course", "let's learn", "resume learning"

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。

Application security testing (AppSec) across a whole product with Strix — decide which asset needs which test (source code, running web app, API, CI pipeline), run it, and turn the results into a ranked remediation plan. Autonomous agents exploit and prove each issue instead of emitting static-analysis alerts, so the plan is ordered by what is actually reachable. Use when the user asks for an application security review or audit, an appsec assessment, vulnerability scanning across their stack, a security review before a launch or a customer security questionnaire, or does not yet know which kind of security test they need.

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。

Read one supplied paper closely enough to reconstruct how its authors actually got there, rather than restating what the abstract claims. Use for 精读论文, 讲透这篇论文, 把这篇读懂, 作者为什么这么设计, 这个公式怎么推出来的, paper x-ray, and deep single-paper comprehension before building on, reviewing, presenting, or citing that paper. Recovers the real starting point and the bet the authors placed, separates load-bearing design from decoration, grounds each key formula in a worked micro-example with concrete numbers, and checks how far the evidence actually reaches, including where the authors are confident and where the paper does not report something. Delivers a structured Markdown long-read by default. Not a summary, not a translation, not a peer 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。

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。

Loft the shape before cutting steel — answer a design question that prose cannot settle by building a throwaway artifact: a pure logic module in a clickable shell, or structurally different UI variants behind one route. The captain reacts to the artifact; the answer folds into the decision; the artifact never docks. Use when a design question stalls in words, when a navigator map carries a loft ticket, or when a spec discussion reaches "we would have to see it".

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。

Check iMessage channel setup and review access policy. Use when the user asks to configure iMessage, asks "how do I set this up" or "who can reach me," or wants to know why texts aren't reaching the assistant.

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。

Buy-side discipline system. For each holding, maintain a written investment thesis — core thesis in 5 sentences, falsifiable assumptions, red lines, valuation anchors — and re-check it each quarter against new earnings/events. Scores thesis health 1-10 from assumption breakage and red-line triggers, and recommends hold / add / trim / exit. Use it right after buying a stock (to write the thesis) and every earnings season (to check it). Bridges the research→buy→monitor gap that most investors skip.

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。

Supply-chain bottleneck arbitrage. Given a super-trend (AI infra, energy transition, defense, semiconductor reshoring, space economy), decompose its physical supply chain down to Layer 2/3 choke points (optics, lasers, InP/SOI substrates, IC substrates, probe cards, specialty fiberglass...) and surface under-the-radar listed companies sitting on each bottleneck. Scores each link on 6 scarcity criteria, applies mandatory valuation gates (PS/PE/safety-margin) via the financial_rigor tool, and Munger-style reverse-validates. Outputs a ranked bottleneck opportunity board. Use when the user wants hidden beneficiaries of a structural trend rather than already-priced leaders.

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。

Deploy cloud-native deception across AWS, Azure, and GCP using decoy (honey) resources whose only purpose is to generate a high-fidelity alert the instant an attacker touches them: canary IAM access keys, permission-less decoy users/roles/service principals, honey object-storage buckets, and decoy secrets in Secrets Manager / Key Vault / Secret Manager. Wires detection through CloudTrail + EventBridge, Azure Sentinel honeytoken watchlists + Defender, and GCP Cloud Audit Logs, so any use of a decoy is routed to the SOC with near-zero false positives. Use when protecting cloud accounts and data stores, when an org has only on-prem honeypots and needs cloud coverage, when seeding fake AWS keys to catch credential theft and code-leak exposure, or when detecting cloud reconnaissance and lateral movement. Keywords: cloud deception, canary token AWS, honey S3 bucket, decoy IAM credentials, CloudTrail alert, GuardDuty, Sentinel honeytoken, decoy secret, honey service account, cloud honeypot, breach detection.

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 an internal network penetration test simulating an insider threat or post-breach attacker to identify lateral movement paths, privilege escalation vectors, and sensitive data exposure within the corporate network.

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。

Format CVs for academic positions, including publications, grants, teaching, and research experience. Use when the user mentions academic CV, faculty job, tenure-track, postdoc, PhD, research position, or needs to list publications, grants, conferences, or teaching.

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。

Compress large language models using knowledge distillation from teacher to student models. Use when deploying smaller models with retained performance, transferring GPT-4 capabilities to open-source models, or reducing inference costs. Covers temperature scaling, soft targets, reverse KLD, logit distillation, and MiniLLM training strategies.

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。

Systematic claim-by-claim verification for any content before it ships. Modeled on professional fact-checking desks (The New Yorker, ProPublica, IFCN standards): extract every verifiable claim, check each against live citable sources (never training data), assign a 6-level confidence status, apply corrections, and produce a scored pass/fail report. Includes a data-derived-claims gate for outputs produced FROM the brain or a database: PRODUCER ≠ VERIFIER (re-derive each claim via a different query path) and AFFILIATION ≠ AUTHORSHIP (person→thing claims resolve through typed edges), with delivery hard-blocked on unsupported claims.

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。

Makes sure no inbound lead goes unanswered. Watches web forms, the shared inbox, and the CRM for new inquiries, qualifies each one against the owner's criteria, drafts a reply in the owner's voice with real meeting times for the owner to approve and send, routes anything hot to a human right away, and logs the whole thing to the CRM. Never sends on its own. Built to run on a schedule so overnight inquiries are drafted and sorted by morning, and works from forwarded or pasted inquiries when no connector is available. Use this whenever the owner is worried about inbound leads or response time — including phrasings like "leads are going cold," "did anyone answer that inquiry," "I keep missing form submissions," "nothing falls through the cracks," "handle my inbound," "respond to this lead," or "we lose people because nobody gets back fast enough." Reach for it for a single unanswered inquiry as readily as for a standing setup.

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。

Works out what to reorder and when, from what is actually selling: pulls sales history and stock on hand from Shopify, Square, NetSuite, or an uploaded CSV, computes 7-day and 28-day sales velocity per item, projects a conservative stockout date for each, sizes a 60-day reorder quantity, and drafts the purchase orders and vendor emails to cover it. Flags the money sitting still too — overstock, dead stock, and zero-velocity items, reported as slow movers to clear rather than things to buy more of. Seasonality is applied where the history supports it and named where it does not. Nothing is ordered and no vendor is emailed without approval. Reach for this whenever stock comes up — "what do I need to reorder," "am I going to run out," "what should I order this month," "we keep running out of filters," "how much cash is sitting in the warehouse," "what is not moving," or "draft a PO for my supplier."

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。

Builds a ranked list of prospects worth contacting. Works out the owner's ideal customer profile from the customers they already have, finds look-alike companies and the right contact at each, enriches them with firmographics and buying signals, scores them, and delivers the list as an XLSX, with an offer to also create the records in the CRM. Runs on Apollo when connected and falls back to web research plus an uploaded customer list when it isn't. Use this whenever the owner wants new prospects, a target list, or help finding customers — including phrasings like "who should I be calling," "find me more customers like my best ones," "build me a prospect list," "I need leads," "who else looks like Acme," or "help me find companies in this area that need what we do." Reach for it even when the owner describes the customer they want rather than asking for a list.

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。