「score」の検索結果

Audits any API documentation site by crawling every endpoint page and scoring each one across 5 checks: description quality, OpenAPI spec presence, body param descriptions, response codes, and response schema completeness. Produces a polished interactive HTML report with a summary scorecard, site-wide pattern analysis, ranked top issues, and per-endpoint findings with specific fix guidance. Trigger this skill whenever a user provides a documentation URL and asks to audit, review, analyse, or check their API docs. Also trigger for: "do the same audit for X", "audit docs.company.com", "check the API docs at X", "run the API docs audit on X", "review the docs for Y API", or pastes a URL alongside words like audit, review, crawl, check, analyse, quality, completeness, or gaps. Always use this skill — do not attempt the audit without following this structured crawl-score-report 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。

Audits any SDK documentation site and produces a fully scored, downloadable HTML report. Use this skill whenever a user provides a documentation URL and asks to audit, review, analyse, score, or check the quality of SDK docs. Also trigger for phrases like "audit the SDK docs at X", "check if the docs at X are complete", "review this SDK documentation", "how good are these docs", "run an SDK audit on X", or any time a user pastes a URL alongside words like audit, review, crawl, check, analyse, quality, completeness, or gaps. ALWAYS use this skill — do not attempt the audit without following this structured crawl → analyse → cross-reference → report 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。

How the performance score moves for your role. Use when the score context shows a declining trend, or before handing off work you have not self-checked against every criterion.

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。

Objectively evaluate a UI/web design against the pols.dev anti-slop design law: detect catalogued slop tells with cited evidence, score 8 weighted axes (color, type, components, layout, motion, execution, signature, cohesion), and emit a Slop Report with a 0–100 Slop Index and grade. Use when the user asks to "evaluate design slop", "slop report", "is this design AI slop", "audit this landing page design", "de-slop review", or wants an objective score of how generic/machine-made a design looks. To fix text (not design), use human-ai or humanizar skills instead.

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。

Audit, score, and compare repositories containing portable Agent Plugins against the official Agent Plugins specification. Use when asked to review a plugin repo, check plugin.json or mcp.json conformance, assess bundled skills and MCP servers, produce an evidence-cited 0–100 plugin scorecard, identify release blockers, or compare two agent plugins side by side.

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。

Analyze and optimize X (Twitter) posts for viral potential and reach using heuristics inspired by X's published open-source recommendation architecture. Use when user wants to: (1) Check if a post will go viral, (2) Score a tweet for engagement potential, (3) Optimize or rewrite a tweet for algorithmic reach, (4) Understand why a tweet underperformed, (5) Build audience in a specific niche. Triggers: "Check if this will go viral", "Make this post buzz", "Will this tweet perform well?", "Optimize my tweet", "How can I make this viral?", "rewrite this tweet", "improve my tweet engagement", "twitter algorithm", "tweet reach", "debug underperforming tweet", "バズるかチェックして", "Xでバズる投稿にして", "伸びるかチェックして", "この投稿を伸ばして", "投稿を改善して", "ツイートを最適化して"

Audit a website against the Forter Agentic Readiness Guide. Loads the 25 weighted rubrics in `audit/`, probes the target site (and optional source code), scores each guideline Pass/Partial/Fail/N/A with sub-check granularity, and produces a prioritized fix report. Use when a user asks "score my site against the agentic readiness guide", "audit https://… for agent readiness", or "what do I need to fix to be agent-ready".

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。

Audits whether scores, benchmarks, LLM judges, or surveys measure what we think. Use when a benchmark is saturated, a score unreliable, or judge agreement untrustworthy.

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。

Scores team or opt-in individual contribution quality from commit and PR history. Use when building engineering scorecards or coaching; for AI impact use dev-ai-coding-metrics.

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。

因果推論・効果検証（A/B テスト / ABテスト / オンライン実験 / リフト / SRM / CUPED、観察データの処置効果 / ATE / ATT / CATE / 傾向スコア / propensity score / IPW / 二重頑健 / DML / causal forest、準実験 / 差の差 / DiD / イベントスタディ / 操作変数 / IV / 2SLS / 回帰不連続 / RDD / 合成コントロール）を実行したら必ずセットで出す図と値のルーター。 proportions_ztest, chisquare, statsmodels.stats.power, dowhy, econml, causalml, doubleml, propensity, LinearDML, IV2SLS, rdrobust, rddensity, pysyncon, treat*post がコードに現れたとき、またはユーザーが「ABテストの結果を 見て」「施策の効果を推定して」「差の差で」「傾向スコアで揃えて」「閾値前後で比較して」と言ったときに使う。SRM・ バランス・並行トレンド・first-stage に言及がなくても適用する。SKILL.md のルーティング表で設計を特定し、対応する references/<設計>.md を読んでから実行する。実験でない群間比較の検定は statistical-inference-diagnostics、 予測モデルの解釈（SHAP 等）は predictive-modeling-diagnostics を使う。

教師なし分析と EDA 前処理（欠測 / 欠損 / NaN / 補完 / imputation / 外れ値処理、クラスタリング / セグメンテーション / k-means / 階層クラスタリング / GMM / DBSCAN、次元削減 / PCA / 主成分分析 / 因子分析 / UMAP / t-SNE、異常検知 / anomaly detection / 不正検知）を実行したら必ずセットで出す図と値のルーター。fillna, dropna, fill_null, SimpleImputer, IterativeImputer, missingno, KMeans, AgglomerativeClustering, DBSCAN, GaussianMixture, silhouette_score, dendrogram, PCA, FactorAnalysis, calculate_kmo, TSNE, umap.UMAP, IsolationForest, LocalOutlierFactor, pyod がコードに現れたとき、またはユーザーが「欠損を埋めて」「クラスタリングして」「主成分で 要約して」「異常を検知して」「データをきれいにして」と言ったときに使う。安定性・k の根拠・平行分析・ベースラインに 言及がなくても適用する。SKILL.md のルーティング表で手法を特定し、対応する references/<手法>.md を読んでから実行する。 教師あり予測は predictive-modeling-diagnostics、回帰・検定は statistical-inference-diagnostics を使う。

予測モデリング（教師あり機械学習 / 予測モデル / 精度評価 / 交差検証 / リーク、決定木 / ランダムフォレスト / GBDT / LightGBM / XGBoost / CatBoost、モデル解釈 / 特徴量重要度 / SHAP / PDP / ICE、時系列 / 季節性 / ARIMA / SARIMA / Prophet / VAR / 変化点 / 時系列予測）を実行したら必ずセットで出す図と値のルーター。train_test_split, cross_val_score, GridSearchCV, Pipeline, TimeSeriesSplit, DecisionTree, RandomForest, lgb., xgb., CatBoost, dtreeviz, shap., permutation_importance, PartialDependenceDisplay, statsmodels.tsa, SARIMAX, STL, adfuller, plot_acf, Prophet, ruptures がコードに現れたとき、または ユーザーが「予測モデルを作って」「精度を出して」「どの変数が効いているか」「来月を予測して」「季節性を見て」と 言ったときに使う。診断・リーク・ベースライン・残差に言及がなくても適用する。SKILL.md のルーティング表で手法を特定し、 対応する references/<手法>.md を読んでから実行する。回帰係数の推論・検定は statistical-inference-diagnostics、 効果推定は causal-inference-diagnostics を使う。

Deep clause-by-clause analysis of a contract with risk scores. Use when asked to "analyze this contract clause by clause", "score the risk in this agreement", or "what is dangerous in this contract".

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。

DRAFT. Score Luma/RSVP lists, approve against capacity, produce host-hit shortlists and day-of door packs. Systems framing — not a marketing CSV dump. Not installed by deepline skills.

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 scoring leads, qualifying prospects, prioritizing pipeline, deciding which accounts to pursue, or building a lead scoring model. Triggers: 'score this lead', 'qualify this prospect', 'is this a good lead', 'lead scoring', 'prioritize my pipeline', 'qualification framework'.

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。

Construct and score Grand Slam Offers using the Value Equation — sourced pain mining, dream outcome articulation, problems→solutions→trim-and-stack offer construction, guarantee/scarcity/bonus design, 1-10 scoring on the four Value Equation variables, pricing sanity pass, and compliance check. Use when "build an offer", "grand slam offer", "value equation", "offer stack", "make this offer irresistible", "design a guarantee", "hormozi offer", "why isn't my offer selling", "pricing and packaging for my offer", or any request to design, score, or rework a commercial offer.

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。

Weekly marketing audit and operating review. Pulls the last 7 days of source-backed marketing, analytics, content, paid media, lead, watcher, and audit data; compares it to the prior 7 days; flags urgent issues; and produces a weekly scorecard plus action list. Use when "weekly audit", "weekly marketing review", "weekly check-in", "weekly scorecard", "what changed this week", "Friday marketing review", or any request for a recurring 7-day marketing audit.

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。

Run the full quality gate on any content file. Score against 28 rules, apply policy, show detailed scorecard with fix suggestions. Works on any markdown file.

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 someone asks for an AIOS audit, asks to score their setup against the Four Cs, or says "is my AIOS working" / "audit my setup" / "find gaps in my AIOS". Produces a Four-Cs scoreboard with top-3 fixes ranked by leverage.

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。

Maps a startup's competitive landscape, scores moat strength across 6+ dimensions, and writes an investor-ready competition narrative with a positioning map. Use when the user asks for a competitive landscape, moat analysis, or positioning review and gives enough to work from: a deck, a list of competitors, or a clearly named startup. A full run takes about 30–40 minutes and searches the web, so for a passing question such as 'who are my competitors?' or 'is that a real moat?', answer briefly in chat and offer the analysis instead of starting it. When it runs, the competitor set and moat scores are checked adversarially, never recalled from memory.

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。

Simulates a realistic VC Investment Committee: three partner archetypes debate a startup's merits, concerns, and deal terms, scored across 28 dimensions. Use when the user asks to simulate an IC, or how partners would debate their startup, and gives a deck, a company description, or a specific fund. A full run takes about 15–20 minutes, so for a passing question such as 'would a VC fund us?' or 'are we fundable?', answer briefly in chat and offer the simulation instead of starting it. When it runs, partners' views come from the scored simulation, never improvised.

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。

Comprehensive audit of a user's entire Claude environment — combines Project audit (six-dimension Project Scorecard, seven anti-patterns) with Global audit (six-dimension Global Layer Scorecard) plus Cross-Layer Alignment Check across all nine layers and Evolutionary Recommendations across four pathways. Produces a unified action plan. Use when user says "full audit of everything," "audit my entire Claude setup," "full stack audit," "comprehensive review of my project and preferences," "check everything," or wants the complete health check of both a specific Project AND their global configuration. Also use when a project audit reveals cross-layer issues that require full-stack visibility. Do NOT use for auditing only a Project (use rootnode-project-audit if available) or only global layers (use rootnode-global-audit if available). Do NOT use for single prompt evaluation (use rootnode-prompt-validation if available). Run on Opus 5 or Sonnet 5 at `high` effort (both defaults); depth reduces on legacy models.

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 a generative diffusion model (DDPM or score-based) with noise scheduling, U-Net architecture, training loop, and sampling procedures including DDIM acceleration. Use when building a generative model for image, audio, or molecular synthesis; implementing DDPM from a research paper; adding a custom noise schedule or conditioning mechanism; replacing a GAN-based generator with a diffusion alternative; or prototyping before scaling with production frameworks like diffusers.

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。

DiffDock and DiffDock-L diffusion-based molecular docking. Use for blind protein-small-molecule pose prediction from a PDB file or sequence plus SMILES/SDF/MOL2, batch docking over a CSV of complexes, virtual screening triage, sampling multiple poses per complex, and reading the confidence score correctly. Also trigger on DiffDock, DiffDock-L, inference.py, confidence_model, samples_per_complex, ESM embedding preparation for docking, or blind docking without a defined box. Not for binding affinity prediction — the confidence score ranks pose plausibility, not potency.

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。