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Citation format and verification protocol for legal documents that draw on Bates-stamped source records. Defines the bracket citation format, multi-source citation rules, quotation handling, the verification pass that runs before output, and the [UNVERIFIED] flag protocol. Use this skill any time another skill produces a legal work product that cites Bates-stamped pages, including medical chronologies, deposition summaries, demand letters, case briefs, and discovery responses. Also use any time the user asks how to format a citation or verify that a claim is supported by the source.

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Drafts filing-ready proofs of claim for U.S. bankruptcy proceedings using Official Form B 410 under FRBP 3001. Handles secured, unsecured priority, and general unsecured claims with proper valuation, documentation, and bar date compliance. Use when a creditor needs to file or amend a proof of claim in a bankruptcy case.

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Generates structured bail hearing summaries from transcripts and case documents, extracting charges, arguments, conditions, and rulings. Use when summarizing bail hearings, pretrial detention decisions, bond hearings, or release condition orders.

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Produces structured aviation law summaries with Bluebook citations covering U.S. and international regulatory frameworks, treaties, and case law. Use when drafting an aviation law summary, FAA/DOT/TSA compliance overview, Montreal/Warsaw Convention liability analysis, air service agreement review, accident liability synopsis, or aviation regulatory research memo.

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Comprehensive legal applications skill covering civil/criminal/administrative litigation workflows, trial defense strategies, legal document drafting (complaints, answers, appeals, retrial petitions, enforcement applications, representation opinions, defense statements, legal opinions, etc.), arbitration (commercial & labor), mediation, enforcement procedures, evidence rules, and litigation risk assessment. Trigger when users ask about: lawsuit/litigation/trial, legal documents, court defense, evidence/cross-examination, arbitration, enforcement, legal strategy, filing a case, appeal, retrial, representation, pleading, or any legal procedural guidance.

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当AI智能体需要处理以下情形时触发本技能： 1. 当前案件/问题在现行法律中没有直接、明确的规定（法律漏洞）； 2. 需要参考已有判例、相似案件或相近法律规范来推导当前问题的处理方案； 3. 用户明确要求"参照""比照""类推适用"某一规范或案例； 4. 在法律论证中需要以"相似案件相似处理"（Like cases should be treated alike）原则支撑结论； 5. 需要评估两个或多个案件/规范之间的相似性与差异性，以判断能否进行类比； 6. 在合同解释、侵权责任认定、行政处罚裁量等场景中，需要借助类似情形的处理经验形成论证。 本技能的核心是：识别相似性基础（tertium comparationis），论证类比的正当性，并在此基础上得出合理的法律结论。

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Drafts the "Interest of Amicus Curiae" section of an amicus brief. Establishes institutional credibility, tethers the amicus's interest to the specific legal question, articulates non-party impacts, and embeds disclosure guardrails under FRAP 29 and Supreme Court Rule 37. Trigger when drafting amicus briefs, friend-of-the-court filings, interest statements, amicus disclosures, or when the user asks why an organization belongs in a case.

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由程建都律师基于一线诉讼办案流程开发的中国民事诉讼 AI 协作技能，面向执业律师和诉讼团队，覆盖民事一审 1–7 七阶段与民事二审 A0–A6 专门路径（判决上诉与三类受控裁定上诉）。适用于读取卷宗、建立事实时间线和证据矩阵，分析诉讼时效、管辖、保全、费用及上诉期限，形成起诉状、答辩状、上诉状、证据目录、质证意见、庭审提纲、客户报告和交付归档底稿；支持原告、被告、上诉人、被上诉人及多方上诉场景，并可按阶段局部执行。它不是单一文书生成提示词，而是一套将材料读取、证据分析、策略形成、文书组建和质量检查组织为可复用、可追溯闭环的 AI 辅助办案工作流。刑事、行政、再审、执行、无具体材料的纯咨询、利益冲突及结果承诺不适用；涉外、港澳台、知识产权、海事海商和破产衍生诉讼仅做识别、风险提示与专项核验闸门。所有输出均为律师工作底稿，不能替代原件核对、现行法核验和执业律师最终判断。

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对拟议 AI 用例进行合规分类：审批通过 / 有条件审批 / 不审批。 本 skill 仅覆盖中国大陆 AI 治理法规——其他法域 AI 治理请走当地服务或律所。

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Drafts U.S. regulatory client advisory summaries translating legal developments into actionable risk and compliance guidance. Use when a client needs a proactive memo, client alert, or legal-update brief for a new law, case, rulemaking, agency guidance, or pending reform. Trigger on requests for "client advisory," "regulatory update," "legal alert," "compliance briefing," "new law summary," or "quarterly advisory."

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在采购或开工之前，对拟议 AI 应用做一次结构化初始问询，产出「可继续 / 需补齐 / 不可按此形态部署」三种结论与带责任人和期限的行动清单。 方法论移植自波兰个人数据保护局（UODO）2026-08-05《初始问题清单》。覆盖 GDPR 与 AI Act 信号提示，适用于出海与境外 AI 项目； 中国大陆境内 AI 用例的红线与备案判断请走 ai-governance-use-case-triage。

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Drafts adversary proceeding complaints for U.S. Bankruptcy Court under FRBP Rule 7001. Covers dischargeability disputes (§ 523), preference actions (§ 547), fraudulent transfers (§ 548), and stay violations (§ 362). Produces a filing-ready pleading with caption, jurisdictional basis, numbered allegations, count structure, and prayer for relief. Triggers when a trustee, creditor, or party in interest needs to initiate litigation within an existing bankruptcy case.

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Drafts a recordable Abstract of Judgment to create a judgment lien on a debtor's real property. Extracts party names, monetary components, and judgment details from case documents, then applies jurisdiction-specific formatting and certification requirements. Use post-judgment in commercial litigation when enforcing monetary awards, perfecting judgment liens, or preparing lien filings with the county recorder.

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Up-to-date Zig programming language patterns for version 0.17.0-dev (0.16.0 stable APIs plus the 0.17 deltas). Use when writing, reviewing, or debugging Zig code, working with build.zig and build.zig.zon files, or using comptime metaprogramming. Critical for avoiding outdated patterns from training data - especially std.net→std.Io.net (requires Io instance), std.time timestamps removed (use clock_gettime), std.Thread.Mutex/Condition/sleep removed (use pthreads), std.crypto.random removed, build system APIs (root_module, Compile methods→Module methods), I/O APIs (buffered writer pattern), container initialization (.empty/.init), allocator selection (DebugAllocator), ArrayList now unmanaged by default, @typeInfo lowercase fields (.@"struct" not .Struct), and removed language features (async/await, usingnamespace). Also covers 0.17.0-dev deltas: b.args→run_cmd.addPassthruArgs(), std.gpu→std.spirv, @bitCast logical-bit (endian-agnostic) semantics, build configurer/maker split, and the zig-pkg/ package directory. Also covers quality tooling Zig does not ship: coverage with kcov (and why in-file tests wreck the denominator), detecting unused private functions (neither the compiler nor zlint's unused-decls finds them), duplicate detection with jscpd, zlint (NOT the same-named X.509 linter in Homebrew), and the built-in fuzzer whose testOne now takes *std.testing.Smith rather than []const u8.

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Patterns for vibe coding that produce production-quality output instead of garbage. Covers prompt engineering for AI coding, verification without reading every line, accept/reject/refine decision framework, architectural guardrails, context management (CLAUDE.md, .cursor/rules), TDD-driven vibe coding, screenshot-driven development, diff review discipline, and the anti-patterns that destroy quality. Activate on: "vibe coding", "AI coding quality", "Claude Code workflow", "AI-assisted development", "how to use AI for coding", "coding with AI", "agentic engineering workflow", "AI code quality", "vibe code without garbage", "production quality AI code", "CLAUDE.md setup", "cursorrules setup", "pre-commit hooks for AI", "TDD with AI", "test-driven vibe coding". NOT for: multi-person collaborative coding sessions (use cooperative-vibe-coding), building AI/LLM applications (use ai-engineer), prompt engineering for non-coding LLM use cases (use prompt-engineer).

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Long-running design anthropologist that builds comprehensive visual databases from 500-1000 real-world examples, extracting color palettes, typography patterns, layout systems, and interaction design across any domain (portfolios, e-commerce, SaaS, adult content, technical showcases). This skill should be used when users need exhaustive design research, pattern recognition across large example sets, or systematic visual analysis for competitive positioning.

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What you can build and do with an always-on AI agent that has episodic memory. Covers concrete product ideas, workflows, emergent capabilities from persistence plus memory, and real-world examples of deployed persistent agents. Helps you go from "I have the architecture" to "here's what it actually does for me." Activate on: "what can an always-on agent do", "persistent agent use cases", "agent applications", "proactive agent ideas", "what to build with episodic memory", "always-on agent product", "personal AI assistant ideas", "/always-on-agent-applications". NOT for: building the architecture (use always-on-agent-architecture), designing inputs (use always-on-agent-inputs), safety and privacy (use always-on-agent-safety).

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Call germline SNPs and indels with GATK HaplotypeCaller and the GVCF joint-genotyping workflow. Covers the local-reassembly + PairHMM mechanism (why HC beats pileup callers on indels), the -ERC GVCF reference-confidence model and <NON_REF> allele, BQSR-vs-DRAGSTR and --dragen-mode error modeling, allele-specific (AS_) annotations, and edge cases (ploidy, Mutect2 mitochondria mode, sex chromosomes/PAR, contamination gating). Use when deciding whether to use HaplotypeCaller vs a pileup or DRAGEN caller, whether BQSR still earns its place, whether to call per-sample GVCFs for a cohort, or how to handle non-diploid, mitochondrial, sex-chromosome, or contaminated samples. Not for post-calling filtering depth (see variant-calling/filtering-best-practices) or cohort joint-genotyping scaling (see variant-calling/joint-calling).

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Estimates time-scaled phylogenies, molecular-clock rates, effective reproduction number R_e, and population dynamics from dated pathogen genomes using TreeTime (maximum-likelihood) and BEAST2 (Bayesian; strict/relaxed clocks; coalescent, Bayesian-Skyline, Skygrid, Birth-Death-Skyline, and sampled-ancestor priors; structured coalescent via MASCOT). Covers root-to-tip clock QC via TempEst, date-randomisation tests, recombination masking via Gubbins/ClonalFrameML before clock inference for recombining bacteria, BDSKY origin-vs-rootHeight pitfalls, sampling-bias correction, multi-chain convergence diagnostics, and reconciling phylodynamic R_e with case-based R_t. Use when dating outbreak origins, estimating substitution rates, inferring R_e through time, building time-calibrated Nextstrain Augur trees, choosing between strict and relaxed clocks, fitting Birth-Death-Skyline models, diagnosing temporal-signal failure, running MASCOT for structured-population analyses, or using UShER for pandemic-scale placement.

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Classify constitutional (germline) copy number variants for clinical reporting using the 2019 ACMG/ClinGen technical standards points-based framework, with ClassifyCNV and AnnotSV for semi-automated scoring. Covers the separate copy-number-loss and copy-number-gain rubrics, the five-tier classification, ClinGen haploinsufficiency/triplosensitivity and dosage-sensitive regions, de novo and segregation evidence, and population-frequency benign evidence. Use when assigning pathogenic/likely-pathogenic/VUS/likely-benign/benign to a constitutional CNV, scoring a CNV against ACMG/ClinGen criteria, or distinguishing the automatable evidence from the case-specific evidence requiring manual input.

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Call copy number variants with the GATK best-practices workflows — the somatic CNV pipeline (CollectReadCounts, DenoiseReadCounts with tangent normalization, ModelSegments, CallCopyRatioSegments) and the germline GATK-gCNV pipeline (DetermineGermlineContigPloidy, GermlineCNVCaller cohort/case mode, PostprocessGermlineCNVCalls). Covers panel-of-normals construction, AnnotateIntervals/FilterIntervals, allelic-count integration, and QS-based filtering. Use when integrating CNV calling into a GATK variant pipeline, calling rare germline CNVs from an exome cohort, deciding between the somatic and germline GATK workflows, or diagnosing why tangent normalization removed a real event or why gCNV output has low precision.

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Fits structural equation models to GWAS summary statistics using GenomicSEM (Grotzinger 2019), including common-factor models, confirmatory factor models, ESEM, common-factor GWAS with Q_SNP heterogeneity, multivariate Wald tests, and stratified GenomicSEM partitioned heritability. Reconciles results against MTAG multi-trait analysis. Handles sample overlap via the LDSC sampling-covariance matrix, identifies and resolves Heywood cases, and verifies model fit with CFI / RMSEA. Use when modeling latent genetic architecture across correlated traits, running multivariate GWAS on a shared factor, distinguishing factor-mediated from trait-specific SNP effects, or comparing GenomicSEM common-factor results against MTAG when both depend on accurate sampling covariance.

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Treats a ctDNA assay as a molecule-counting experiment at the Poisson edge and builds its analytical-validation case the measurement-science way. Covers the genome-equivalent currency (~330 haploid copies/ng), the lambda = input_GE x VAF sampling ceiling (lambda>=3 for ~95% detection), the error-suppression ladder (raw NGS ~1e-3 -> single-strand UMI ~1e-4/1e-5 -> duplex <1e-7), the CLSI EP17 LoB/LoD/LoD95/LoQ framework, the per-locus-vs-panel-integrated LoD distinction that lets bespoke MRD reach ppm, contrived/SEQC2 reference standards, and honest LoD reporting conditioned on input mass + consensus depth + replicate detection rate. Use when stating or trusting a sensitivity claim, designing a dilution-series validation, deciding how many genome equivalents are needed at a target VAF, choosing a single-locus vs panel-integrated LoD, or auditing a "detects 0.1% VAF" claim.

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Evaluates the patient’s plan for using injected insulin in case of pump failure, including knowledge of basal-bolus dosing. Triggered by phrases such as 'Discuss sick-day plan for pump failure' or 'Review transition to injections if pump stops'.

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