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「nes」の検索結果

1.2万 件 ・ 関連度順

概要と使いどころ

webapp-testing-jp

無料日本語概要

Simplified Japanese web application testing skill covering unit tests, E2E tests, integration tests, Japanese text validation, IME input testing, and naming conventions. Triggers on requests for Webテスト, テスト自動化, E2Eテスト, 日本語テスト, Japanese web testing.

LinkX-Japan/ai-souken-workflows62026年3月12日 更新

init

無料日本語概要

LAM ハーネスの規範層をプロジェクトへ敷く初期化スキル。 plugin コンポーネントとして配れない層(.claude/rules/ と docs/internal/ と .claude/scripts/ = managed、 および CLAUDE.md 等の starter)をファイルとして配置し、.claude/harness.json に記録する。 ランタイム(Python)が無い環境では完了を拒む。 Layer 1(.claude/settings.json の permissions)は敷かず、手作業の手順として提示する。 Use when the user installs lam-harness into a project, or runs /lam-harness:init.

sougetuOte/LivingArchitectModel42026年9月8日 更新

Quantifies biodiversity from species abundance/incidence tables using Hill numbers (iNEXT) with coverage-based rarefaction-extrapolation (Chao & Jost 2012), asymptotic richness via Chao1/ACE/jackknife as a lower bound, Baselga turnover/nestedness partition with the Podani alternative as sensitivity check, mandatory Hellinger transformation before ordination (Legendre & Gallagher 2001), Faith PD and SES_MPD/SES_MNTD with explicit null-model choice, and Maire 2015 functional-diversity dimensionality optimization. Use when comparing diversity across sites with unequal sampling effort, picking the right richness estimator for singleton-heavy amplicon data, partitioning beta diversity into turnover vs nestedness, reporting Hill-number effective species counts rather than raw entropies, computing SES_MPD with explicit null-model justification, or deciding whether to apply standard metrics to compositional amplicon data. Not for clinical 16S microbiome diversity (see microbiome/diversity-analysis).

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。

peacezha/TRACE32026年10月13日 更新

Improve agent reliability over time — diagnose why agents fail and fix the setup. Triggers on: agent keeps failing, same mistake again, agent not improving, make agent smarter, agent quality plateau, agents ignore skills, agent skips tests, fix agent behavior, agent unreliable, improve agent setup, self-improving harness, agents worse over time, tune agent instructions, agent going in circles, agent ignores AGENTS.md, repeated agent errors. Requires harness v0 and eval harness. AUTO-ROUTED from harness-engineering on symptoms. Not first setup — harness-generation first.

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。

dvy1987/agent-loom32026年8月8日 更新

Seed minimal agent harness v0 — manifest, eval checks stub, governance. AUTO-INVOKED after project-setup or retroactive-project-setup when docs/harness/manifest.json is missing. Also triggers on: generate harness, scaffold agents, agent bootstrap, first time agents in this repo, new project agent setup, set up agent harness, agent onboarding files, missing agent configuration, agent instructions setup, make agents read project rules, agent reliability setup, agents not configured. Pairs with project-setup. Evolution is harness-evolution.

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。

dvy1987/agent-loom32026年8月8日 更新

Quantifies biodiversity from species abundance/incidence tables using Hill numbers (iNEXT) with coverage-based rarefaction-extrapolation (Chao & Jost 2012), asymptotic richness via Chao1/ACE/jackknife as a lower bound, Baselga turnover/nestedness partition with the Podani alternative as sensitivity check, mandatory Hellinger transformation before ordination (Legendre & Gallagher 2001), Faith PD and SES_MPD/SES_MNTD with explicit null-model choice, and Maire 2015 functional-diversity dimensionality optimization. Use when comparing diversity across sites with unequal sampling effort, picking the right richness estimator for singleton-heavy amplicon data, partitioning beta diversity into turnover vs nestedness, reporting Hill-number effective species counts rather than raw entropies, computing SES_MPD with explicit null-model justification, or deciding whether to apply standard metrics to compositional amplicon data. Not for clinical 16S microbiome diversity (see microbiome/diversity-analysis).

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。

peacezha/HPClaw32026年10月11日 更新

Produce or apply an approved report-first proposal for workflow, ROSE, skill, command, subagent, memory, install, or harness-doc changes; use after harness-issue-triage localizes a harness problem or when the user explicitly requests harness maintenance, and do not edit core harness files without explicit human approval.

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。

Rosetears520/aili-workflows22026年9月27日 更新

production-audit

無料日本語概要

公開前や変更の取り込み後に、アプリの認証・データ・決済・運用を根拠付きで点検します。公開を妨げる問題と優先して直す項目を、本番への準備状況としてまとめるスキル。

  • 公開前に本番への準備状況を確認したいとき
  • 変更の取り込み後にリスクを確認したいとき
  • CI通過後の本番リスクの点検
affaan-m/ECC27.9万2026年10月12日 更新

cpp-coding-standards

無料日本語概要

C++コードの実装・レビュー・改修で、型の扱い、メモリ管理、例外処理、並行処理を点検するスキル。標準的な指針に沿って安全性と書き方の一貫性を整えます。

  • モダンなC++コードを書きたいとき
  • メモリの所有権と解放のレビュー
  • 既存のC++コードを改修したいとき
affaan-m/ECC27.9万2026年10月12日 更新

Manage `@metaharness/darwin` bench suites — `bench create {repo}` scaffolds a JSON suite from a repo's test corpus; `bench verify {suite.json}` checks suite well-formedness. Bench suites are the fixed evaluation corpora that `harness-evolve --bench {suite.json}` scores variants against, decoupling evolution from the repo's natural tests. Degrades gracefully when @metaharness/darwin is absent.

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。

ruvnet/ruflo7.5万2026年10月13日 更新

Run `@metaharness/darwin evolve {repo}` to mutate a harness's seven policy surfaces (planner/contextBuilder/reviewer/retryPolicy/toolPolicy/memoryPolicy/scorePolicy), sandbox-score each variant, and promote only measured wins. The model is frozen; the harness evolves. Closes the loop ADR-150 opens (score+genome describe; evolve changes). Degrades gracefully when @metaharness/darwin is absent (ADR-150 + ADR-153 architectural constraints).

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。

ruvnet/ruflo7.5万2026年10月13日 更新

Run `@metaharness/darwin security bench` (upstream "Darwin Shield" / ADR-155) — evolves a champion security-detection harness against a 10-vuln / 9-decoy corpus and grades it on TPR/FPR/patch-pass/repro/unsafe vs four baselines (B0 static, B1 LLM-single-pass, B2 fixed-agent, B3 Darwin-champion). Closest reference implementation for ruflo's own ADR-155 nightly self-learning security harness (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。

ruvnet/ruflo7.5万2026年10月13日 更新

When the user wants to generate, iterate, or scale ad creative — headlines, descriptions, primary text, or full ad variations — for any paid advertising platform. Also use when the user mentions 'ad copy variations,' 'ad creative,' 'generate headlines,' 'RSA headlines,' 'bulk ad copy,' 'creative testing,' 'write me some ads,' 'Facebook ad copy,' 'Google ad headlines,' 'LinkedIn ad text,' 'static ads,' 'ad templates,' 'iMessage ad,' 'ChatGPT ad,' 'creative strategy,' 'creative roadmap,' 'creative retro,' 'hook writing,' 'creative review page,' 'motion video ad,' 'faceless video ad,' 'UGC ad,' 'greenscreen ad,' 'TikTok/Reels ad format,' 'Meta ad format tier list,' or 'creative format taxonomy.' Use it to produce or iterate ad copy at scale. Copy avoids AI tells like 'it's not X, it's Y' reveals. For campaign strategy and targeting, see ads. For landing page copy, see copywriting. Test hypotheses must be falsifiable, naming the metric, the comparison, and the expected direction.

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。

coreyhaines31/marketingskills5.5万2026年10月14日 更新

Run the AgentRC readiness assessment on the current repository and produce a static HTML dashboard at reports/index.html. Wraps `npx github:microsoft/agentrc readiness` and hands off rendering to the @ai-readiness-reporter custom agent. Supports policies (--policy) for org-specific scoring. Use when asked to assess, audit, or score the AI readiness of a repo.

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。

github/awesome-copilot4万2026年10月14日 更新

Track multiple live deals with milestones, deadlines, action items, and status updates. Maintains a deal pipeline view and surfaces upcoming deadlines and overdue items. Use when managing a book of business, tracking process milestones, or preparing for weekly deal reviews. Triggers on "deal tracker", "deal status", "where are we on", "process update", "deal pipeline", or "weekly deal 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。

anthropics/financial-services4万2026年9月22日 更新

Generate a Business Model Canvas with all 9 building blocks. Use when creating a business model, documenting how a business creates value, or analyzing an existing business 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。

phuryn/pm-skills2.7万2026年10月10日 更新

The continual-harness refinement protocol — how an agent inspects its recent trajectory for failure signatures and improves its own harness (agent prompts, sub-agents, skills, memory) in place, mid-session, landing changes on the session branch immediately and promoting them to `main` only through a change request. Load this skill when a refinement prompt arrives mid-session, when the `harness-reflector` agent runs, or whenever you decide your own scaffolding needs repair. The sub-agent fan-out in this skill is for the top-level `harness-reflector` run only; if you loaded this as a subagent, do the four passes yourself and skip the fan-out.

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

Canonical reference for Kortix projects, Apps (sites, servers, backends with volumes) and internal business apps, the CLI, sessions, sandboxes, change requests, triggers, connectors, secrets, system skills, and the two session harnesses, pi and OpenCode. Covers `kortix.yaml` versions 1 and 2, serverless App deployments, harness configuration (`harnesses/pi/`, `harnesses/opencode/`), session identity, credential boundaries, and the complete pi and OpenCode references. Load when the user asks how Kortix works, what Kortix can do, how to deploy an App, how an agent discovers platform instructions, how to customize or configure this project's agents (create or fix an agent, subagent, skill, tool, plugin, extension, pi package, command, MCP server, model or permission rule; edit `opencode.jsonc`), how to edit `kortix.yaml`, how to use the `kortix` CLI, how to land work through a change request, or how to schedule and automate 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。

kortix-ai/suna2万2026年10月13日 更新

[omh] Business question on market, competitors, pricing: business research brief - turns a market, competitor, pricing, or customer question into a structured evidence-vs-inference brief; for raw link gathering use ulw-research, and for ongoing multi-role research use research-department. Use when the user says: research-brief, business-research, business research, research brief, decision brief, pricing decision brief, decision-ready brief, source-backed business research.

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-hermes3,3612026年10月13日 更新

Guided journey from a business with lucky months to a repeatable growth engine that produces a forecast. Orchestrates nine skills phase by phase - one-page-marketing, hundred-million-offers, predictable-revenue, contagious, influence-psychology, crossing-the-chasm, cold-start-problem, lean-analytics, negotiation - asking the user questions at every decision point and recording results in the project docs/ folder (MARKETING.md, OFFER.md, METRICS.md, GROW-BUSINESS-PLAN.md) so the journey resumes across sessions. Use when the user wants to build a marketing and sales system, manufacture predictable pipeline, engineer word-of-mouth and referrals, or says 'revenue is real but lumpy and I need growth that repeats'. If the offer, retention, or operations underneath are broken, run improve-business first; with no paying customers yet, start with create-business; when the product itself must carry the growth loops, use grow-app. For one framework in isolation, invoke that skill directly.

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。

wondelai/skills2,3972026年9月11日 更新

Translate existing code-explanation docs into another language, Chinese by default. Translates a whole `CODE_EXPLANATION/` folder into a parallel `CODE_EXPLANATION_<LANG>` copy (e.g. `CODE_EXPLANATION_ZH`), or a single file — either bilingually in place (English + translation interleaved) for small files or as a `<name>_<lang>.<ext>` sidecar copy for larger ones. Keeps filenames, code, identifiers, file paths, and technical terms in English — only the explanatory prose is translated. Use this skill whenever the user wants to translate, localize, or produce a non-English version of code-explanation / codebase documentation: phrases like "translate-explanation", "translate the code explanation", "translate the CODE_EXPLANATION folder", "localize these docs to Chinese", "make a Chinese version of the explanation", or naming any target language for the explanation files. Default to Chinese (ZH) when no language is specified.

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。

Leanmcp/gateway-skills2,1112026年10月8日 更新

Review XQUIC harness structure for bloat, duplicated facts, trigger overlap, reference drift, and missing hard checks. Use when changing AGENTS.md, harness specs, pipelines, skills, setup scripts, validation routing, or when asked to audit harness design.

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。

alibaba/xquic1,9222026年10月9日 更新

Write a Chinese annual self-review (述职报告 / 年终总结) for a performance cycle: results against OKR or KPI with evidence, the two or three things that mattered most, honest lessons, and next year's plan, in the form Chinese employers expect. Use when asked 帮我写年终总结, 写述职报告, 年度绩效自评, 半年总结, or a year-end review in Chinese. Produces the review in Chinese, a one-page summary for the presentation, a data appendix, and likely questions from the reviewer.

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。

mohitagw15856/pm-claude-skills1,4412026年10月13日 更新

Pressure-test a business or side-hustle idea before you sink money and months into it — find the real demand, the risky assumptions, and the cheapest way to test them. Use when asked to validate my business idea, is this a good business idea, test my side hustle, or should I start this. Produces a read on the core assumptions the idea depends on, who the customer really is and whether the pain is real, the cheapest experiments to test demand before building, a rough viability check (market, competition, economics), and a go/refine/rethink call — honest, not a cheerleader.

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。

mohitagw15856/pm-claude-skills1,4412026年10月13日 更新