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「before」の検索結果

6,192 件 ・ 関連度順

概要と使いどころ

competitive-platform-analysis

無料日本語概要

自社の強みや顧客像を基に、比較すべき競合と調査先を選びます。直接競合・周辺競合・目標となる企業に分類し、根拠付きの候補一覧を作って詳しい比較の準備を整えます。

  • 競合比較の対象を決めたいとき
  • 直接競合・周辺競合・目標企業の分類
  • 市場調査レポートの候補を絞りたいとき
affaan-m/ECC27.9万2026年10月12日 更新

browser-qa

無料日本語概要

公開前のWeb画面をブラウザで操作し、フォームや認証、3つの画面幅での表示差分、速度指標、アクセシビリティを点検して、公開可否と修正点をまとめます。

  • ステージングの新機能を検証したいとき
  • 公開前にフォームと認証を確認したいとき
  • 3つの画面幅で表示を比較したいとき
affaan-m/ECC27.9万2026年10月12日 更新

ponytail

無料

External agent skill (MIT, github.com/DietrichGebert/ponytail). Forces the laziest solution that actually works: question whether the task needs to exist at all (YAGNI), reuse what is already in the codebase, reach for the standard library before custom code, native platform features before dependencies, one line before fifty. Climb the ladder on every coding task — writing, adding, refactoring, fixing, reviewing, or designing code, and choosing libraries or dependencies. Supports intensity levels: lite, full (default), ultra. Never cut validation, error handling, security, or accessibility.

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。

diegosouzapw/OmniRoute7.6万2026年10月11日 更新

Load relevant long-term memory from Hindsight before starting work. Use at the start of every task or request, before planning or answering, and whenever the user mentions people, projects, decisions, preferences or anything done before.

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。

vectorize-io/hindsight4.9万2026年10月13日 更新

Zero-shot time series forecasting with Google's TimesFM foundation model. Use this skill when forecasting ANY univariate time series — sales, sensor readings, stock prices, energy demand, patient vitals, weather, or scientific measurements — without training a custom model. Supports both basic forecasting and advanced covariate forecasting (XReg) with dynamic and static exogenous variables. Automatically checks system RAM/GPU before loading the model, validates dataset fit before processing, supports CSV/DataFrame/array inputs, and returns point forecasts with calibrated prediction intervals. Includes a preflight system checker script that MUST be run before first use to verify the machine can load the model and handle your specific dataset.

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。

google-research/timesfm3.4万2026年9月30日 更新

Before fixing a slow/stale/timeout alert, measure the step yourself. Kill the theory with a stopwatch, not a code change. Measure-first ops triage for temporal alerts (stale, timeout, freshness, wedged, N hours behind) from gbrain doctor, autopilot, sync, and cron monitors — runs BEFORE any timeout raise, threshold change, or pipeline rewrite.

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。

garrytan/gbrain3.1万2026年10月13日 更新

challenge

無料

Pre-mortem plan analysis. Imagine the plan failed 12 months from now and work backwards to find the weaknesses. Surfaces assumptions, dependencies, and execution risks before committing resources. Use when before significant resource commitment, before presenting to a board or investors, when feedback has been one-sidedly positive, or when there is pressure to move fast and figure it out later.

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。

alirezarezvani/claude-skills2.8万2026年8月30日 更新

Use when an n8n-mcp account targets more than one n8n instance — i.e. the `n8n_instances` tool is available, the user mentions multiple n8n instances or environments (prod vs staging, several teams or clients), a workflow / datatable / credential / execution call returns an unexpected NOT_FOUND or reads data you don't recognize, or a credential create/update/delete is refused with an `INSTANCE_AMBIGUOUS` error. Covers choosing and switching which instance this MCP session targets, verifying the target before high-stakes work — credential writes above all — and recovering from misroutes and ambiguous-write fail-closes. Always consult this skill before operating on a specific instance, before any credential create/update/delete on a multi-instance account, or when a call hits the wrong/empty data or an `INSTANCE_AMBIGUOUS` error.

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。

czlonkowski/n8n-mcp2.3万2026年10月13日 更新

ponytail

無料

Forces the laziest solution that actually works, simplest, shortest, most minimal. Channels a senior dev who has seen everything: question whether the task needs to exist at all (YAGNI), reach for the standard library before custom code, native platform features before dependencies, one line before fifty. Supports intensity levels: lite, full (default), ultra. Use on ANY coding task: writing, adding, refactoring, fixing, reviewing, or designing code, and choosing libraries or dependencies. Also use whenever the user says "ponytail", "be lazy", "lazy mode", "simplest solution", "minimal solution", "yagni", "do less", or "shortest path", or complains about over-engineering, bloat, boilerplate, or unnecessary dependencies. Do NOT use for non-coding requests (general knowledge, prose, translation, summaries, recipes).

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。

kortix-ai/suna2万2026年10月13日 更新

memori

無料

Ambient Memori long-term memory for Claude Code via local Bash. MUST TRIGGER on essentially every non-trivial user turn: run recall before drafting any substantive response, whether or not the user mentioned memory, a prior session, or past work. The default is to check memory first; do not wait to be asked. Always fire before external lookups (WebSearch/WebFetch) and before answering any question about preferences, prior decisions, constraints, project history, status, past work, or any non-trivial coding/research task. Skip only for trivial acknowledgements/closings, purely self-contained turns where prior context cannot possibly help, or when the user explicitly opts out. Use Advanced Augmentation after drafting the final response for every non-trivial turn, as the last memory step. Use recall.summary only for broad session summaries/orientation, compaction after context loss, feedback for memory quality, quota for limits, and signup only when explicitly requested.

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。

MemoriLabs/Memori1.7万2026年10月3日 更新

the-judge

無料

Evidence-first pull request judge that reviews a PR and posts one consolidated GitHub review with inline comments via the gh CLI. Runs the repo's own deterministic checks first, researches current official docs before any claim about external libraries or APIs, then reviews correctness, security, structural quality (code judo, spaghetti growth, file-size limits), and AI slop including useless code comments. Every finding must carry evidence, every comment passes a deterministic noise gate before posting, and the verdict (APPROVE, COMMENT, REQUEST_CHANGES) is weighed by findings. Use when asked to review a PR, judge this PR, review this branch or diff before merge, run the-judge, "revise esse PR", "faca o code review", or "julgue esse PR". Do NOT use for reviewing prose or documents, fixing CI failures, resolving merge conflicts, writing the fix itself, or responding to review comments (use gh-address-comments).

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。

tech-leads-club/agent-skills7,0572026年10月9日 更新

Use when an n8n-mcp account targets more than one n8n instance — i.e. the `n8n_instances` tool is available, the user mentions multiple n8n instances or environments (prod vs staging, several teams or clients), a workflow / datatable / credential / execution call returns an unexpected NOT_FOUND or reads data you don't recognize, or a credential create/update/delete is refused with an `INSTANCE_AMBIGUOUS` error. Covers choosing and switching which instance this MCP session targets, verifying the target before high-stakes work — credential writes above all — and recovering from misroutes and ambiguous-write fail-closes. Always consult this skill before operating on a specific instance, before any credential create/update/delete on a multi-instance account, or when a call hits the wrong/empty data or an `INSTANCE_AMBIGUOUS` error.

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。

czlonkowski/n8n-skills6,4192026年10月9日 更新

Establish MSBuild/.NET build performance baselines before optimizing. USE FOR: a .NET build or solution that is slow or has build-performance concerns; cold, warm, incremental, or no-op measurements; before/after comparisons; CI build output caching; static graph build decisions; artifacts output; and dependency graph trimming. Start here before build-perf-diagnostics, incremental-build, or build-parallelism. DO NOT USE for webpack, npm, JavaScript bundlers, or other non-MSBuild build systems. For detailed target/task/analyzer bottleneck analysis after baselining, use build-perf-diagnostics.

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。

dotnet/skills5,6202026年10月14日 更新

Completion-evidence route used before claiming work is complete, fixed, passing, committed, or PR-ready. Requires fresh verification output before success claims. Do not use for root-cause debugging, TDD implementation, test-report packaging, or review-feedback triage.

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。

foryourhealth111-pixel/Vibe-Skills3,6752026年8月31日 更新

[omh] Proof a change is done before merge: define and record build, lint, typecheck, test, security, docs, generated-output, and CI evidence before completion or merge. Use when the user says: verification-gate, verification gate, quality gate, release gate, test gate, build lint test, lint typecheck tests, verify before merge.

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。

rlaope/oh-my-hermes3,3632026年10月13日 更新

Validate changes before submitting a pull request. Run comprehensive checks including lint, tests, alignment review, and RFC analysis. Use before creating a PR, when asked if code is ready for review, or before pushing for PR.

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。

huggingface/OpenEnv2,7062026年10月13日 更新

Use when receiving code review feedback (especially if unclear or technically questionable), when completing tasks or major features requiring review before proceeding, or before making any completion/success claims. Covers three practices - receiving feedback with technical rigor over performative agreement, requesting reviews via code-reviewer subagent, and verification gates requiring evidence before any status claims. Essential for subagent-driven development, pull requests, and preventing false completion 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。

mrgoonie/claudekit-skills2,2282026年4月3日 更新

When the user wants to design or optimize the funnel that takes web visitors into installing and onboarding the app — including smart app banners, web-to-app deep links, deferred deep links, web onboarding (Stripe-paid web flow before app install), QR codes, "open in app" CTAs, and the trade-off between paying on web vs in-app. Use when the user mentions "web to app", "smart app banner", "Stripe before app", "web paywall before install", "Branch web SDK", "web funnel for app", "AppsFlyer OneLink web", "Universal Links", "App Links", "QR code to app", "open in app", "deferred deep link from web", or "should I sell on web first then push to app". For pure in-app onboarding, see onboarding-optimization. For deep link infra, see attribution-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。

appeeky/aso-skills2,1742026年10月7日 更新

Verifies that work is actually complete before it is claimed to be — running the checks, reading the output, and confirming the original request was satisfied rather than approximated. Use this before saying something is done, fixed, or passing; before committing or opening a pull request; and whenever a claim of success has not been backed by command output.

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。

cbrock84/headcount2,0482026年9月18日 更新

Use when about to claim work is complete, fixed, or passing, before committing or creating PRs. Evidence before assertions.

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。

a5c-ai/babysitter1,8442026年9月17日 更新

Save a structured state snapshot before stopping or handing off. Captures the active plan, recent decisions, file pointers (with line numbers), open questions, and the next 1–3 actions into a checkpoint file under `quality_reports/checkpoints/`. Optionally proposes `[LEARN]` entries to add to MEMORY.md. Use when user says "checkpoint", "save state", "snapshot before I stop", "where am I", "wrap up the session for handoff", or before a long break / model switch / collaborator handoff. Companion to (NOT replacement for) the narrative session-log workflow.

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。

pedrohcgs/claude-code-my-workflow1,6602026年9月28日 更新

Distill the current conversation into a structured note (decisions made, open questions, file pointers with line numbers, next 1–3 actions) and save to `quality_reports/session_logs/` before auto-compression. Differs from `/checkpoint` (explicit stop-point snapshot) and from auto-compaction (which truncates rather than distills). Use when context is approaching auto-compact threshold, when a long pipeline has accumulated many decisions, or when the user says "compress", "distil this session", "before we hit auto-compact", "structured handoff before context resets".

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。

pedrohcgs/claude-code-my-workflow1,6602026年9月28日 更新

Keep a change small and in the existing idiom - size the plan and weigh smaller alternatives before writing it, reuse the mechanism that already owns the behavior instead of adding a parallel one, and simplify the diff before handoff. Use when planning any change beyond a few lines, before readying a PR, or when reviewing agent-written code for bloat.

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。

octanejs/octane1,4582026年10月14日 更新

Guide the user through a quadrant walk that maps the unknowns of a task — open by listing the known knowns, then work through known unknowns, unknown knowns, and unknown unknowns one stage at a time, ending with a complete four-quadrant map in the user's hands. Use when a request is ambiguous or underspecified, the codebase or domain is unfamiliar, the user will "know it when they see it", a reference implementation must be understood before porting, mid-build deviations from the plan need capturing, or a finished change needs buy-in or verified understanding before merge. Pairs with [write-spec](../write-spec/SKILL.md) — walk the quadrants to burn off fog before slicing, and feed the finished map into the spec.

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。

dzhng/skills1,3212026年10月12日 更新