「standard」の検索結果

Use this skill when working inside the ClawTeam repository itself: local development, debugging, reviewing, testing, validating multi-agent flows, or checking whether a code change actually works end-to-end. Use the repository bootstrap scripts to standardize the local `clawteam` command and to wire project-local `.agents` and `.claude` skills back to this repository. This skill is repository-development oriented, not a general end-user usage guide.

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Standard collaboration patterns for all squad agents — worktree awareness, decisions, cross-agent communication

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。

Microsoft Style Guide + Squad-specific documentation patterns

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。

Selecting WHO handles work is the Routing table; selecting HOW they handle it (Direct, Lightweight, Standard, Full) is Response Mode. This skill contains the complete decision table, exemplar prompts for each mode, the Lightweight spawn template, and the upgrade rules. Squad coordinator loads this on demand once routing has identified the agent — to pick the right ceremony level for the 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。

Standard recovery patterns for all squad agents. When something fails, adapt — don't just report the failure.

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。

Extract clean markdown content from web pages using Defuddle CLI, removing clutter and navigation to save tokens. Use instead of WebFetch when the user provides a URL to read or analyze, for online documentation, articles, blog posts, or any standard web page. Do NOT use for URLs ending in .md — those are already markdown, use WebFetch directly.

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Transform an AI agent into a tasteful, disciplined development partner. Not just a code generator, but a collaborator with professional standards, transparent decision-making, and craftsmanship. Use for any development task: building features, fixing bugs, designing systems, refactoring. The human provides vision and decisions. The agent provides execution with taste and discipline.

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 Kiln pre-release smoke test suite plus the standard CI checks (checks.sh), diagnose every prerelease test that broke (and why), and write a clean readable report with recommended actions. Read-only — it never edits code. Use when the user wants to validate a release candidate, run prerelease tests, or asks for a "prerelease check / smoke / 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。

Generate a therapeutic indication dossier. Covers the patient population, epidemiology, disease biology, standard of care, regulatory precedent, and landmark clinical trials.

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。

Focus on implementing custom Chat Provider, helping to adapt any streaming interface to Ant Design X standard format

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。

Extract clean markdown content from web pages using Defuddle CLI, removing clutter and navigation to save tokens. Use instead of WebFetch when the user provides a URL to read or analyze, for online documentation, articles, blog posts, or any standard web page.

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。

Humanization Quality Verifier - Ensures transformation integrity and quality Validates that humanization preserves meaning, citations, and academic standards Use when: after G6 transformation, before final export, for quality assurance Triggers: verify humanization, check transformation, validate changes

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。

This skill should be used when the user asks to review a diff or pull request, write review comments, audit code quality, establish review standards, or improve how a team performs code 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。

Scaffold a new research project with standard directory structure, CLAUDE.md template, and documented README. Use this at the start of every new project to ensure consistent organization.

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 R code review protocol on R scripts. Checks code quality, reproducibility, domain correctness, and professional standards. Produces a report without editing files. Make sure to use this skill whenever the user wants their existing R code evaluated or audited — not when they want new analysis written. Triggers include: "review my R script", "check my R code", "is my code replication-ready", "audit this R file", "does this code follow conventions", "will this reproduce", "check my analysis script", "code review", "review-r", or when the user has an existing .R file and wants quality feedback rather than new code.

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。

Econometrics skill for panel data models. Activates when the user asks about: "panel data", "fixed effects", "random effects", "Hausman test", "within estimator", "between estimator", "two-way fixed effects", "clustered standard errors panel", "FE model", "RE model", "pooled OLS", "unobserved heterogeneity", "panel regression", "first difference estimator", "entity fixed effects", "time fixed effects", "面板数据", "固定效应", "随机效应", "豪斯曼检验", "双向固定效应", "面板回归", "个体效应", "时间效应", "一阶差分"

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。

Econometrics skill for OLS regression and linear models. Activates when the user asks about: "run OLS", "linear regression", "ordinary least squares", "interpret regression results", "heteroskedasticity", "multicollinearity", "regression assumptions", "robust standard errors", "GLS", "WLS", "fit a regression model", "check regression diagnostics", "OLS假设", "最小二乘法", "线性回归", "回归系数", "残差检验", "异方差", "多重共线性", "普通最小二乘", "稳健标准误", "回归诊断"

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。

Econometrics skill for descriptive statistics and summary tables. Activates when the user asks about: "descriptive statistics", "summary statistics", "summary table", "Table 1", "balance table", "means and standard deviations", "correlation matrix", "data summary", "sample characteristics", "variable distributions", "描述性统计", "描述统计", "汇总统计", "统计表", "均值标准差", "平衡性检验", "相关矩阵", "样本特征", "变量分布"

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。

Complete survival analysis library in Python. Handles right-censored data, Kaplan-Meier curves, and Cox regression. Standard for clinical trial analysis and epidemiology.

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 economic analysis outputs (fiscal briefings, macro briefings, market research, longlists, and other quantitative economic documents) against methodology standards, academic literature, and common errors. Runs structured checks across core categories including counterfactual, additionality, discounting, double counting, distributional analysis, Aqua Book RIGOUR, and Flyvbjerg-style strategic misrepresentation detection. Returns a RAG scorecard with issues ranked by severity.

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。

Standardized Python & Stata coding practices for empirical research projects

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STATA code pattern library for empirical archival accounting research. Provides tested syntax from 126 peer-reviewed JAR (Journal of Accounting Research) replication files (2017-2025). Use when the user asks procedural questions like "How do I implement [method]?" or "Show me code for [technique]" — including: entropy balancing, propensity score matching (PSM), difference-in-differences (DiD), regression discontinuity (RDD), instrumental variables (IV), event studies (CAR/BHAR), survival analysis, Fama-MacBeth regressions, bootstrap, quantile regression, reghdfe/xtreg/areg, clustering standard errors, fixed effects, esttab/outreg2 table formatting, winsorization, leads/lags. Users can specify their variables (e.g., treatment, outcomes, controls) and receive adapted syntax. NOTE: This skill provides code patterns from published papers, not research design advice.

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Perform an exhaustive, multi-pass proofread and copy-edit of an applied-microeconomics manuscript to top-economics-journal standards (AER, QJE, Econometrica, ReStud), checking prose, equations, table notes, footnotes, and citations for avoidable errors. Use before submitting or circulating an empirical economics paper.

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。

Dense, machine-readable API reference for PyFixest — high-dimensional fixed-effects OLS/WLS/IV and Poisson (feols, fepois, feglm), clustered/robust standard errors, R-style formula syntax, and post-estimation. Use when writing or debugging Python fixed-effects regressions with the pyfixest package.

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。