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Use when a task needs the judgment of an Aerospace Engineering and Operations Technologist/Technician — verifying an installed fastener's preload against a drawing's torque callout via the T=K·D·F relationship, reducing strain-gauge data from a structural proof-load test into stress and checking it against an FEA-predicted margin, selecting and executing an NDI method against a defect type and material, reducing a wind-tunnel test point's dynamic-pressure and Reynolds-number data, or ballooning and dispositioning an AS9102 first article inspection. Distinct from an aerospace-engineer (owns the design, structural analysis, and certification basis) — this role builds, instruments, tests, and inspects the hardware the engineer specified, closing the loop with measurement rather than deriving a new analysis.

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为他山学科交叉公众号撰写微信文章，包括选择文章类型、套用排版模板、生成配图、转换HTML、添加底部模板。当用户说"写一篇公众号文章""帮我写他山文章""写公众号推文""帮我把这篇写完""补全这篇文章""继续写这篇"时使用。写完后自动触发 article-proofreading 审稿。

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统一写作流水线。任何文档/文章/报告均走此流程：研究→草稿→逻辑自检→真实性校对→画图规划→批量画图→图片自审→审稿→格式转换（HTML/LaTeX/MD）。可从任意阶段入场（已有草稿直接审核，已审稿直接转格式）。触发词：「写一篇/帮我写/写一份/我有初稿了/帮我检查逻辑/帮我配图/从画图开始/从[Stage名称]开始继续/转成HTML/转成LaTeX」。注意：「只要审稿」请直接触发 article-proofreading；「帮我审稿」不触发本 Skill。

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按郑总的审稿标准审阅中文文章草稿，检查AI腔、标题写法（4种错误类型）、绝对表达、结构层次污染、结语完整性，逐条给出修改方案。当用户说"审稿""帮我检查文章""review一下"时使用，也可在完成文章草稿后主动执行。

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Review and improve marketing copy that already exists - a page, an email, an ad, a post, a deck slide - using a fixed six-pass edit. Produces a marked-up diagnosis, a rewritten version, and a per-pass score so the user can see what changed and why. Use when the user says "review this copy", "improve this", "make this better", "tighten this", "edit this page", "does this copy work", "why is this flat", "punch this up", "proofread", or pastes existing copy and asks for feedback. Also use when copy is on-brand but underperforming. For writing new copy from nothing, see content-writer or landing-page-writer. For diagnosing a page's conversion problem beyond its words, see page-cro. For voice consistency rules, see brand-context.

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Fix bugs and small behavior changes at the narrowest responsible layer. Use when regression proof, preserved surrounding behavior, and task-relevant tests matter.

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Prove existing work meets acceptance conditions without expanding scope. Use for validation-only tasks, completion checks, focused gate runs, and last-mile proof.

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Implement reversible compatibility-safe transitions. Use for schema, data, API, protocol, configuration, or dependency migrations requiring rollback and preservation proof.

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Implement and debug OAuth 2.0 DPoP (RFC 9449) refresh token sender-constraining for WebCrypto, Node.js ES6, and browser runtimes integrating with Google's OAuth platform. Use when configuring non-extractable asymmetric key pairs (P-256), generating DPoP Proof JWTs for authorization code exchange and token refresh, or handling 400 use_dpop_nonce challenge retry loops at oauth2.googleapis.com/token. Don't use for unconstrained OAuth 2.0 flows (where refresh tokens are not bound to a client key pair), or for Google Cloud IAM / service account authentication.

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Bulletproof agent operating protocol. 15 failure-prevention rules distilled from 120+ real sessions and 10 agent definitions. Covers fabrication, constraint tracking, verification, scoping, retry discipline, and communication. Load before any task to prevent the most common agent failure modes.

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Use the Crabbox wrapper for OpenClaw remote validation across Linux, macOS, Windows, and WSL2, including delegated Blacksmith Testbox proof. Report the actual provider and id.

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Comprehensive calculus expert covering limits, derivatives, integrals, sequences, series, and multivariable calculus with rigorous proofs and practical applications

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Use when adversarially reviewing a document that makes formal or technical claims — math derivations, physics papers, statistical analyses, benchmark reports, whitepapers. Inventories every equation and quantitative claim, verifies each AS NAMED in the text (never a paraphrase or a neighboring statement), and classifies VERIFIED / REFUTED / UNVERIFIABLE / VACUOUS. Triggers on "check this paper", "verify these claims", "is this derivation right", "review this proof", "audit this benchmark", "does the math hold up". For source-code review see code-review-and-quality; for skill/agent library audits see skill-library-review; for content quality scoring see content-ops.

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Refine academic writing for computer science research papers targeting top-tier venues (NeurIPS, ICLR, ICML, AAAI, IJCAI, ACL, EMNLP, NAACL, CVPR, WWW, KDD, SIGIR, CIKM, and similar). Use this skill whenever a user asks to improve, polish, refine, edit, or proofread academic or research writing — including paper drafts, abstracts, introductions, related work sections, methodology descriptions, experiment write-ups, or conclusion sections. Also trigger when users paste LaTeX content and ask for writing help, mention "camera-ready", "rebuttal", "paper revision", or reference any academic venue or conference. This skill handles both full paper refinement and section-by-section editing.

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Prove — or honestly fail to prove — a specific technical claim: "the fix works", "it's deployed", "the service is running", "the site is done", "there are no vulnerabilities". Atomizes the claim, picks the shortest decisive signal on the evidence ladder, and returns a verdict from a fixed vocabulary (pass / partial / fail / skip) with an explicit coverage boundary. NOT code review, NOT a fix, NOT orchestration — only "what is proven, and what we merely hope". Triggers — "prove it works", "is it really done?", "are you sure?", "we deployed — is it live?", "verify that", "did we actually check?".

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Audit agent runtimes and their tests for lifecycle inference, capability overload, context pollution, correlated verification, prompt-only control, false success, dead compatibility paths, test-only seams, and complexity without contribution. Use for whole-repository agent audits, slop or dead-code triage, test contribution reviews, large refactors, tool/context simplification, and cleanup requests that need proof before deleting code or tests.

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Produces an enforcement-aware Animal Welfare Act compliance audit for USDA/APHIS-regulated facilities. Maps Form 7002 inspection citations to verified 9 C.F.R. Parts 1-3 requirements, analyzes NCI severity and recurrence patterns, evaluates core compliance programs (PVC, IACUC, housing, records, transport), and outputs a prioritized corrective action plan with proof artifacts. Use when auditing AWA compliance, reviewing USDA inspection reports, preparing for license renewal, conducting diligence, or assessing enforcement risk. Trigger: Animal Welfare Act, AWA, USDA, APHIS, Form 7002, IACUC, PVC, exhibitor, dealer, research facility.

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Drafts adverse possession complaints and quiet title pleadings. Structures jurisdictional foundations, legal property descriptions, and element-by-element proof of actual, open, continuous, exclusive, and hostile possession. Use when filing adverse possession claims, quiet title actions, or prescriptive ownership pleadings.

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Diagnose and optimize timing-critical Chisel RTL for FPGA implementation while preserving cycle semantics. Use for Vivado timing bottlenecks, long ready or admission paths, queue and issue selection, free-list bank mapping, priority encoders, one-hot arbitration, wide muxes, late-arriving forwarding or override data, high-fanout controls, cross-module predicates, register-boundary changes, emitted-Verilog inspection, or routed-DCP A/B analysis. Also use when a source-level simplification needs proof that it changes timing without changing architectural state.

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Rapidly generate up to 25 distinct ad creative hypotheses for testing. Produces a matrix of angles (pain, benefit, social proof, urgency, curiosity, comparison) x formats (static, carousel hook, UGC-style, bold-text overlay) with headline, visual prompt, and rationale for each, then generates the visuals with any image tool. Use when the user wants "ad variations", "ad concepts", "creative testing batch", "give me 25 ads", or paid-social creative ideation. Part of the Creative Production set.

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Cryptographic security for agentic systems — zero-trust agent networking, signed message envelopes (JWS/JWE), capability-based security (ocaps), Merkle tree audit trails, WASM sandboxing, and formal verification. Covers CLI dev tool security, mTLS between agents, permission boundaries (least privilege for AI agents), and supply chain security for skills/plugins. Activate on: "agent security", "zero trust agents", "secure agent communication", "capability-based security", "ocap", "signed messages between agents", "agent audit trail", "sandbox agent execution", "agent permissions", "mTLS agents", "cryptographic verification", "agent supply chain", "OWASP agentic", "prove agent did X", "tamper-proof agent logs". NOT for: application-level SAST scanning (use security-auditor), network firewall rules (use infrastructure), SOC2/HIPAA compliance (organizational), or prompt injection defense (use prompt-engineer).

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Orchestrate autonomous AI development pipelines through your Kanban board (Asana, GitHub Projects, Linear). Manages multi-worker Claude Code dispatch, deterministic quality gates, adversarial review, per-task cost tracking, and crash-proof pipeline execution.

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Use for lateral thinking, or when ideas feel stuck or incremental: "we've tried everything", "need a surprising angle", "break the pattern", "give me a wild idea that could work". Uses provocations and reframes. Skip for rule lookups or strict logical proofs.

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当用户在不确定情境下倾向于参考他人行为做决策、或发现自己在跟随群体行动却说不清原因时激活此 skill。 典型场景：看到"销量第一"标签就产生信任、新环境中观察别人怎么做自己就怎么做、被伪造的社会证据（罐头笑声、假好评）影响判断。 不适用于：有明确标准和专业知识的决策、刻意的社会学习与模仿、有意识地参考他人经验的理性比较。

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。