「consistency」の検索結果

Multi-pass deep code review for large patches (1000+ LOC) that maximizes real bug detection. Orchestrates targeted-review, shallow-review, and deep-review in parallel across all HIGH and MEDIUM risk files and commits: understands the feature holistically, splits by file and commit, runs deep review on every HIGH/MEDIUM file, targeted review across the same scope, and per-commit shallow review, followed by cross-cut consistency checks. Use when: reviewing a large patch (feature branch, multi-commit, or single large diff, 1000+ LOC), doing a thorough pre-merge review, or when shallower reviews miss bugs due to patch size. Triggers on: "review this branch", "review these commits", "review this feature", "mega review", "thorough review", "full review of X commits", or when the user specifies a commit range or feature for review.

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Run an AI impact assessment — structured intake, risk analysis, regulatory classification per regime in scope, policy consistency diff, and recommendation with conditions. Uses the house-style structure learned from the seed impact assessment in `~/.claude/plugins/config/claude-for-legal/ai-governance-legal/CLAUDE.md`. Use when user says "impact assessment for", "assess this AI use case", "run an AIA", "generate an AIA", "we need to document this AI system", "AI risk assessment for X", or follows a conditional triage result.

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。

Review vendor AI terms — agreement, addendum, or ToS AI provisions — against your governance positions; flag training-on-data, liability, model changes, and AI policy consistency. Use when user says "review this AI agreement", "check OpenAI terms", "what did we agree to with [vendor]", "vendor sent an AI addendum", "is this AI contract okay", or attaches vendor AI terms.

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Read a Canva design and return structured, actionable design feedback — visual hierarchy, copy/messaging, layout & spacing, consistency, readability, and accessibility. Read-only; makes no changes to the design. Use when the user asks to "review my design", "give me feedback on this", "critique my deck/poster/flyer", "how can I improve this design", or "what's wrong with this slide".

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。

Automatically check code changes since last tag and update documentation in docs/ directory (en, zh-CN, ja-JP) and CLAUDE.md to ensure consistency with actual code implementation

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 and realigns UI to match design system standards, spacing, tokens, and patterns. Use when the user mentions consistency, design drift, mismatched styles, tokens, or wants to bring a feature back in line with the system.

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。

Performs a final quality pass fixing alignment, spacing, consistency, and micro-detail issues before shipping. Use when the user mentions polish, finishing touches, pre-launch review, something looks off, or wants to go from good to great.

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。

Validates animation durations, enforces typography scale, checks component accessibility, and prevents layout anti-patterns in Tailwind CSS projects. Use when building UI components, reviewing CSS utilities, styling React views, or enforcing design consistency.

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 enables visual inspection of websites running locally or remotely to identify and fix design issues. Triggers on requests like "review website design", "check the UI", "fix the layout", "find design problems". Detects issues with responsive design, accessibility, visual consistency, and layout breakage, then performs fixes at the source code level.

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。

Review pull requests to code-graph-rag, a multi-language code graph parser. Focuses on graph-edge correctness in language parsers, cross-language consistency, and test fixtures that actually exercise the fix.

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Hunt HTTP request smuggling (CL.TE, TE.CL, H2.CL, H2.TE). Cause: front-end proxy and back-end server disagree on where one request ends and the next begins (Content-Length vs Transfer-Encoding header parsing inconsistency). CL.TE: front-end uses CL, back uses TE → smuggle by sending TE: chunked but with body that fits CL count. TE.CL: opposite. H2.CL: HTTP/2 downgrade, smuggle CL into HTTP/1.1 back-end. Detection tools: Burp HTTP Request Smuggler extension, smuggler.py, h2csmuggler. Confirm: time-delay technique (smuggled GET with 30s timeout) — if front-end returns slow on next victim request, smuggling works. Validate: cache poisoning chain (smuggle request that gets cached for victim), credential theft (smuggle X-Forwarded-For override that captures next user's cookies), bypass auth (smuggled internal-path request). Real paid examples from major CDN deployments. Use when hunting H1 paid programs running CDN+origin stacks, when targeting load balancer / WAF bypass.

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Predict protein structure for monomers and multimers with AlphaFold2 via the ColabFold runner (Mirdita et al. 2022, github.com/sokrypton/ColabFold; AlphaFold2 Jumper et al. 2021). Reach for this skill to fold a sequence or complex with the AF2/AF2-Multimer evoformer, to validate designed sequences by self-consistency pLDDT, ipTM, and RMSD, or to run a quick MSA-backed prediction using the public MMseqs2 server.

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。

Chinese LaTeX thesis assistant for existing .tex degree thesis projects (XeLaTeX/LuaLaTeX/latexmk). Use this skill whenever a user works on a Chinese master's or doctoral thesis needing compilation, GB/T 7714 bibliography checks, chapter structure mapping, template detection (thuthesis, pkuthss), terminology consistency, logic coherence review, heading lead-in checks, title optimization, de-AI editing, experiment chapter review, three-line table validation, or abstract structure diagnosis. Trigger even for single issues like "帮我编译论文", "检查国标格式", "看看绪论逻辑", "毕业论文", "学位论文", "硕士/博士论文", "三线表", "检查摘要", or "摘要结构".

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 enables visual inspection of websites running locally or remotely to identify and fix design issues. Triggers on requests like "review website design", "check the UI", "fix the layout", "find design problems". Detects issues with responsive design, accessibility, visual consistency, and layout breakage, then performs fixes at the source code level.

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 proofreading protocol on academic writing — papers or manuscripts. Checks grammar, typos, layout issues, consistency, and academic writing quality. Produces a report without editing files. Make sure to use this skill whenever the user wants surface-level writing errors found — not substantive academic critique. Triggers include: "proofread", "check for typos", "grammar check", "look for errors in my draft", "proofread all", "polish this", "check my writing", "are there any mistakes", "proofread before I send this", or when the user wants a clean-up pass rather than feedback on arguments or methods.

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。

Verify that every quantitative claim in the paper is traceable to an analysis output file, and that no important output was omitted. Make sure to use this skill whenever the user wants to check that the paper and analysis are consistent before submission. Triggers include: "run the quality gate", "check the paper matches the analysis", "verify consistency", "does the paper match my results", "check my numbers", "are my tables right", "quality check before submission", "verify my claims", "make sure everything is consistent", "double-check the paper against my output files", or any pre-submission integrity check between paper text and computed results.

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。

Prose quality checker for Quarto (.qmd) files, grounded in William Zinsser's *On Writing Well* (30th Anniversary Edition). Checks for clutter, weak verbs, hollow qualifiers, clichés, inflated academic voice, poor leads and endings, pronoun and tense inconsistency, and unclear explanation. Produces a structured markdown report organized by document section — never modifies the source file. Use when asked to improve prose quality, tighten writing, reduce clutter, or apply Zinsser's writing principles to a draft. For grammar and punctuation, use the proofread skill. For APSA style rules, use the apsa-style skill. Supports an optional output-file argument and an optional @sec-label argument to restrict checking to one section.

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。

Deep consistency audit of the entire repository — launches 4 parallel specialist agents to find factual errors, code bugs, broken references, count mismatches, and cross-document inconsistencies, then fixes all issues and loops until clean. Make sure to use this skill whenever the user wants a comprehensive repository-wide check — not a targeted review of a single file. Triggers include: "audit", "deep audit", "find inconsistencies", "check everything", "run a full audit", "are there any broken references", "check the whole repo", "something feels off", "run the audit loop", or after making broad changes across multiple files.

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。

Proofread and verify academic papers in LaTeX. Runs 19 sequential checks covering titles, consistency, citations, formatting, theoretical tension in motivation, concise results reporting, cross-section repetition, em-dash usage, and auxiliary-text-to-footnote conversion. Trigger when user says "check paper" / "proofread" / "paper-checker" / "校对" / "核查论文".

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Thoroughly verify all code, tables, figures, modeling decisions, and quantitative claims in an academic paper against its source R scripts and output files. Use this skill whenever you need to audit, replicate, or verify an academic research paper - including cross-checking LaTeX tables against R output, validating econometric modeling choices, ensuring sample sizes are consistent, building a verification manifest, and running automated replication tests. Trigger this skill for any mention of: paper verification, replication check, table audit, code-paper consistency, reproducing results, verifying estimates, checking coefficients, or any variant of "does the paper match the 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。

Systematic writing framework for philosophy and interdisciplinary academic papers from optimized outline to submission-ready manuscript. Use when users want to: (1) write a paper from a detailed outline, (2) ensure quality control during writing, (3) maintain consistency across chapters, (4) prepare a submission-ready manuscript, or (5) systematically execute a planned paper. Triggered by phrases like 'write the paper from this outline,' 'compose the full manuscript,' 'execute the outline,' or when users have completed strategic planning (academic-paper-strategist skill) and are ready to write. Takes optimized outline as input; outputs complete manuscript with iterative quality checks.

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 complete nurture email sequences with subject lines, preview text, and body copy using proven copywriting formulas. Use when given ICP, offer, and objections to generate full email flows, creating welcome sequences, writing promotional emails, or maintaining voice consistency throughout email campaigns. Platform: Google and Meta.

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。

Transform one long-form piece into multiple platform-specific content derivatives including LinkedIn posts, tweet threads, email snippets, ad hooks, and video scripts while maintaining voice consistency. Use when given a blog post, article, or pillar content to atomize across channels. Platform: Google and Meta.

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 codebases for quality, consistency, and broken patterns — use for pre-release or tech debt 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。