プロジェクトで使う業務用語や概念の境界を、具体例とコードの照合で明確にします。決まった定義を用語集に記録し、重要な設計判断の理由も必要に応じて残すスキルです。
- 曖昧な業務用語を整理したいとき
- GLOSSARY.mdの作成・更新
- 業務上の定義とコードの整合確認
381 件 ・ 関連度順
概要と使いどころ
プロジェクトで使う業務用語や概念の境界を、具体例とコードの照合で明確にします。決まった定義を用語集に記録し、重要な設計判断の理由も必要に応じて残すスキルです。
Redisを使ったキャッシュ、アクセス回数制限、複数処理の同時実行制御、メッセージ配信を設計し、キーの有効期限や接続管理も見直すスキル。
論文や研究計画を共通の評価基準で読み、研究方法、根拠、引用、文章構成を点検するスキル。評価の理由と修正の優先順位、次に直す内容を整理します。
開発前に製品の狙いを検証し、企画の実行判断、利用開始時のつまずき、機能の優先順位を整理します。根拠と次の行動を含む企画書やロードマップにまとめます。
製品の要望や企画書を、開発に着手できる具体的な要件へ整理します。業務ルール、データ、サービス間の接点、未決事項を明文化し、次の担当へ引き継ぎます。
Perlコードの入力処理、ファイル操作、外部コマンド、SQL、Web出力を点検し、具体例とチェックリストに沿って安全な実装へ見直すスキル。
MySQLとMariaDBのテーブル設計や遅いSQLを見直し、インデックス、更新処理、接続管理、複製の遅延を点検して、修正案と検証手順をまとめるスキル。
機械学習モデルを本番で使うために、データの仕様、再現可能な学習、品質評価、配備、監視、切り戻しを整理し、実装計画やレビュー項目にまとめるスキル。
資金調達に向けた投資家への初回メール、紹介依頼、面談後の連絡を作成するスキル。相手の投資方針や具体的な実績を踏まえ、簡潔で次の行動が明確な文面に整えます。
Djangoアプリのログイン、権限、入力処理、本番設定を点検します。不正な操作やスクリプト実行への対策から、ファイル投稿とAPIの保護まで見直すスキル。
ECCの現行ファイルを確認し、目的に合うスキルやコマンドの選択、導入・リセットの手順、プロジェクトへの設定や重複インストールの調査を案内するスキル。
AIエージェントの成果物を、正確さ・網羅性・明瞭さ・実行しやすさ・簡潔さの5軸で自己評価し、根拠付きの点数と優先順位を付けた改善案をまとめます。
Quietly suggest a concrete improvement after observing material, generalizable friction in agent work. Submit proactively without permission, preview, or announcement, then continue the primary task.
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 short, colloquial summary for a Paperclip summary slot: open with the 1–3 specific, concrete actions the reader needs to take right now to unblock the work, then a brief plain-language status, streaming progress as it works.
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。
OpenDesign's operating review: growth, burn, and the concrete path to sustainability without losing the open ethos. Built as a decision-grade corporate strategy deck for leadership team.
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。
Parse a structured design brief written in I-Lang protocol format into a concrete design spec. Eliminates ambiguity from vague requests like "make it professional" by requiring explicit dimensions: palette, typography, layout, mood, density, and constraints. Trigger keywords: "design brief", "create a design brief", "ilang brief", "structured brief".
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。
Zero-to-sensing path picker for RuView (WiFi-DensePose) — pick docker-demo, repo-build, or live-esp32 and run the next concrete step.
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。
Create requested artifacts early, iterate from concrete output, and verify final deliverables
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。
Evaluate and carry out non-trivial software-system changes from first principles. Use when assessing RFCs, issues, designs, features, refactors, migrations, dependency changes, or proposed fields, events, APIs, modules, and services whose need, consumers, system fit, validation, or rollback require scrutiny. Read the actual system, identify the concrete problem and named semantic consumers, choose the smallest sufficient solution, reject pseudo-requirements and speculative abstractions, and require evidence proportional to risk. Do not use for mechanical edits, source-code explanation, or a dedicated review of an already-complete diff.
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。
Codex-only team orchestration: run a named team of cooperating Codex workers with durable, script-managed state. MUST USE when the user asks Codex to create, run, coordinate, inspect, archive, or delete a team of agents/threads/sessions, or to work on something as a team in parallel. FIRST inspects the active tool surface (checking tool_search for deferred tools) and tells the user the route: native MultiAgentV2 agents (flat spawn_agent with task_name) when available, Codex App threads as the fallback, or a plain-subagent split when neither set exists. The main session is always the leader; members are defined by a concrete part, ownership area, or perspective - never a vague job role; a bundled cross-platform script writes the .omo/teams state plus an auto-generated member field manual. Use a team when the work is not perfectly isolated but parallelizing helps; use plain subagents when scope is perfectly isolated or the goal is ambiguous. Triggers: team mode, teammode, make a team, run as a team, team of agents, coordinate threads, parallel Codex threads, archive the team.
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。
Deliver a runnable local browser app so the user can operate it on the first handoff. This delivery skill does not choose whether a requested local system should be a browser app. On a current turn that explicitly says to implement a brand-new browser project now, load bundled:greenfield-project-scaffolding before project work only after no-peek or permitted top-level placement facts prove that no named or suitable current-folder target resolves the root; never hand off from planning or answer-only turns, existing work, a named or suitable target, or standalone or single-file delivery. Resolve user-blocking product or interface choices with an available interaction surface; resolving those choices alone never authorizes implementation. Always call read_skill for bundled:browser-app-delivery before creating or materially changing a local browser app that owns its start path or a playable browser game. Also load it when the user requests a paste-ready, single-file, offline, or immediately playable browser artifact, even if no local start path should remain, unless the user says they will open or check it themselves or explicitly declines verification. On completed local-server delivery, include exact start commands, a concrete local URL, and explicit browser-open wording. On completed standalone delivery, hand off the exact artifact path or paste URL and smoke result without inventing a server. Do not load it for a self-contained static file that has no owned start path if the user either says they will open or check it themselves or explicitly declines verification. Do not load it for component/style-only edits, deployed sites, backend/API-only work, browser QA, review, explanation, plan-only, or explicit stop/no-tool turns.
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。
Improve AI application with evaluation-driven development. Define eval criteria, instrument the application, build golden datasets, observe and evaluate application runs, analyze results, and produce a concrete action plan for improvements. ALWAYS USE THIS SKILL when the user asks to set up QA, add tests, add evals, evaluate, benchmark, fix wrong behaviors, improve quality, or do quality assurance for any Python project that calls an LLM model.
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 and plan end-to-end Azure IoT and Smart City solutions: requirements, architecture, security, operations, cost, and a phased delivery plan with concrete implementation artifacts.
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。