「stl」の検索結果

Run a series of pre-release checks on the repo.

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KRACK (CVE-2017-13077..082) and FragAttacks (CVE-2020-24586..588 + 26139-26147) — key reinstallation, fragmentation, and aggregation attacks against WPA2 supplicants. Covers Vanhoef's test scripts, viability against modern patched stacks (mostly mitigated post-2021), residual unpatched embedded devices and IoT vendors, and the practical limitations of these attacks in modern engagements. Use when assessing legacy supplicants, embedded clients, or vendors with poor patch cadence.

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Generate architecture procedurally in Three.js and film it assembling — a small geometry vocabulary that builds pagodas, castles, domes and spires from parameters instead of mesh files, hip roofs with flying eaves driven by a single profile function, and a clipping-plane build animation where everything below a rising line is finished work and scaffolding stands above it. Use for construction studies, architectural title sequences, procedural landmarks, or any hero object that should build itself rather than fade in.

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Draws original hand-written SVG spot scenes in the Line interior style, wide airy rooms or terraces where slim, realistic people do design and coding work. A thin uniform indigo outline (1.4 px at 480 wide) runs around mostly white fills. Sparse flat accents (teal, sage, coral, mustard, lavender, peach wood) cover under 7% of the card. Pale lavender 1 px background decor (brick clusters, pendant lamps, framed posters) sits behind, and a long floor line with end dashes runs under it all. Covers the palette, line weights, heads and hands from a parts toolkit, composition and a render-critique loop. Use when asked for line-art, thin-line or outline illustrations, indigo line art, office, desk, home-workspace, remote-work or team scenes, or interior spot illustrations for empty states, onboarding screens, 404 pages, blog headers, feature spots, landing sections or marketing cards.

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Complete deBridge Protocol SDK for building cross-chain bridges, message passing, and token transfers on Solana. Use when building cross-chain applications, bridging assets between Solana and EVM chains, or implementing trustless external calls.

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Hunt TLS/SSL and DNS misconfigurations — missing HSTS (downgrade attack), weak cipher suites, expired/invalid certificates, mTLS bypass, missing SPF/DKIM/DMARC (email spoofing), DNS Zone Transfer (AXFR), dangling CNAME subdomain takeover, CAA records. Most of these are Info/Low on their own — this skill is opinionated about which findings actually pay (spoofable DMARC with delivered-to-inbox proof, AXFR returning internal hosts, dangling-CNAME takeover) versus which get rejected as best-practice noise (missing CAA, missing HSTS with no MitM position). Use during recon to find infrastructure weaknesses, and to TRIAGE them honestly before reporting.

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Hunting skill for subdomain takeover vulnerabilities. Includes modern provider fingerprints — Microsoft Azure DevOps `cloudapp.azure.com` regional-pool re-issue (1-click OAuth ATO via wildcard `reply_to`, Binary Security), Zendesk help-desk takeover → email interception → password reset chain (0xprial writeup), Vercel `cname.vercel-dns.com` deleted-project takeover, plus general Fastly CDN service re-attach and S3 dangling-bucket cookie-scope techniques. Use when hunting subdomain takeover — emphasis on ATO-chain primitives (OAuth `redirect_uri`, cookie-domain, email DNS).

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Hunting skill for cache poison vulnerabilities. Built from 10 public bug bounty reports including X-Forwarded-Host poisoning, X-HTTP-Method-Override / GCS cache, reflected→stored XSS via cache, classic Omer-Gil Web Cache Deception, Cloudflare Cache Deception Armor bypass, session-token cache deception, Akamai hop-by-hop smuggling → server-side edge poisoning, and Kettle's 2024 path-normalization WCD against Cloudflare/Fastly/GCP. Host/X-Forwarded-Host injection that reaches app logic (reset-link poisoning, routing SSRF, OAuth issuer) is owned by hunt-host-header; this skill owns the case where the poisoned response is CACHED and served to other users. Use when hunting cache poisoning, Web Cache Deception, CDN-fronted apps.

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VS-Enhanced Evidence Quality Appraiser - Prevents Mode Collapse with context-adaptive quality assessment Enhanced VS 3-Phase process: Avoids automatic tool application, delivers research-specific evaluation strategies Use when: appraising study quality, assessing risk of bias, grading evidence Triggers: quality appraisal, RoB, GRADE, Newcastle-Ottawa, risk of bias, methodological quality

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Industry and market research. Market sizing, structure, competition, regulation, supply chains, pricing, M&A. Produces a single compact, source-cited research report with Porter's Five Forces, HHI / CR4, PESTLE, and trade flows. Supports UK, US, EU, Australia, and global scope, with multi-geography comparison.

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Read 微信公众号 articles from mp.weixin.qq.com links using available web or browser tools. Report verification walls honestly; reading alone does not modify notes or queues.

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批评与自我批评：在工作完成、阶段验收、收到批评或同类错误反复出现时，对成果和过程做诚实、具体、基于事实的审视，输出可执行的改进项，并处理外来批评而不辩解。触发信号包括 review、复盘、审查、"帮我看看有没有问题"、"你确定吗"；任务刚开始或只是单步查询时不触发。 English: Criticism and self-criticism. After delivery, at a review checkpoint, on receiving criticism, or when the same mistake recurs, examine the result and the process honestly and concretely, produce actionable fixes, and accept valid criticism without defensiveness. Triggers include review, retrospective, audit, "check this for problems", "are you sure"; skip at the start of a task or for one-step lookups.

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[omh] Rust ownership, lifetime, or unsafe trouble: prepare Rust changes with ownership, error, and API discipline, and escalate any unsafe, FFI, or lock-free change to the UB checklist. Use when the user says: rust, rust code, rust skill, rustlang, borrow checker, lifetime error, ownership error, trait bound.

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Amazon Redshift is NOT PostgreSQL; corrects LLM mistakes; covers SQL, metadata, connectivity/auth, storage, query performance, and operations. Applies ONLY to Redshift (provisioned or Serverless). Pushes back on: CREATE INDEX, string_agg, pg_catalog, text type, SERIAL, stl_query. Triggers on: Redshift SQL, Redshift CREATE TABLE, Redshift COPY/UNLOAD, slow or suddenly slow Redshift query, EXPLAIN plan, queue wait, stale statistics/ANALYZE, result cache, Redshift permission denied, Redshift disk full, storage growth, snapshot/backup cost, ghost rows/bloat, VACUUM, spill to disk, distribution skew, Redshift system views, QUALIFY, PIVOT, MERGE, materialized views, Redshift Data API (Python/boto3), Redshift workload management (WLM), concurrency scaling, Redshift resize, Spectrum, awsdatacatalog, connection failures (SSL/TLS, ODBC/JDBC, connection limit), IAM/SAML federation, IAM Identity Center, datashares. Does NOT apply to: S3 policies, Athena, Glue/Iceberg outside Redshift, Aurora, RDS, DynamoDB.

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Guided journey from a shipped app that works but feels rough to a product that fits the job, flows without friction, reads clearly, and persuades honestly. Orchestrates nine skills phase by phase - jobs-to-be-done, ux-heuristics, design-everyday-things, refactoring-ui, microinteractions, made-to-stick, influence-psychology, high-perf-browser, steve-jobs-design-review - asking the user questions at every decision point and recording results in the project docs/ folder (CUSTOMER.md, DESIGN.md, POSITIONING.md, IMPROVE-APP-PLAN.md) so the journey resumes across sessions. Use when the user wants to fix a clunky product, cut UX friction, sharpen in-app copy, or says 'the app works but feels rough'. Not for code, tests, or hardening - use improve-code-quality (fresh prototype) or remove-technical-debt (aged); no app yet, create-app; needs growth loops, grow-app; marketing-site friction, improve-website; one leaking flow, conversion-optimization. For one framework in isolation, invoke that skill directly.

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Run a structured 5-day process to prototype, test, and validate product ideas with real users. Use when the user mentions "design sprint", "validate before we build", "rapid prototype", "test with users", or "should we build this". Also trigger when a team is stuck in endless debate over a high-stakes product decision, or wants to de-risk a costly idea before investing in development. Covers mapping, sketching, deciding, prototyping, and testing across Monday-Friday. For ongoing experimentation and MVPs, see lean-startup. For customer job analysis, see jobs-to-be-done. For non-leading user interviews, see mom-test.

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Defines and manages service levels — setting targets that reflect what customers need, measuring honestly, and handling breaches. Use this to write or negotiate an SLA, decide what to measure and at what threshold, respond to a missed service level, or work out why a service that meets its targets still has unhappy customers.

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Answers a business question with data without fooling yourself — framing the question so an answer would change something, choosing the right comparison, checking the data before trusting it, recognizing the traps that produce confident wrong answers (aggregation reversals, survivorship, regression to the mean, multiple comparisons), and reporting uncertainty honestly. Use this to run an analysis, review one before acting on it, or work out why two people looking at the same data reached opposite conclusions.

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Runs the ongoing relationship with accounts after the sale — segmenting coverage against account value, building a health score that predicts rather than describes, running reviews customers find worth attending, forecasting renewals honestly, and finding expansion that follows usage instead of quota. Use this to design a customer success motion, decide who gets a named contact, work out why renewals surprise you, or fix a health score everyone ignores.

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Clinical Research Bias Assessment - Case-Control Study (NOS) v2.3.0. Use when you need to assess the bias of a case-control study using the Newcastle-Ottawa Scale (NOS) criteria, or when evaluating the quality of a medical paper.

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Evaluates the quality of cohort studies using the Newcastle-Ottawa Scale (NOS). Use when the user provides a cohort study article or text and needs a quality assessment report.

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Read Microsoft Excel (.xlsx) files robustly with `openpyxl` (or `pandas`). Covers multi-sheet workbooks, header rows, empty cells, merged cells, comma-separated list cells, and converting a sheet to a list-of-dicts the rest of your code can consume. Use when a task input or reference document is an `.xlsx` file rather than JSON/CSV.

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Analyzes 3D mesh files (STL) to calculate geometric properties (volume, components) and extract attribute data. Use this skill to process noisy 3D scan data and filter debris.

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Write idiomatic C++ code with modern features, RAII, smart pointers, and STL algorithms. Handles templates, move semantics, and performance optimization. Use PROACTIVELY for C++ refactoring, memory safety, or complex C++ 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。