Results for “sample”

Use this skill when a company needs a written risk assessment method before it builds or rescores a register, or when the current method produces registers where everything scores 3. Triggers: "write our risk methodology", "define likelihood and impact scales", "what is our risk appetite", "risk acceptance criteria", "who can accept a risk", "our auditor says the method is not repeatable", "risk matrix for our ISMS". Drafts a short method with likelihood and impact anchors in the company's own money, hours and records, a scoring rule, an acceptance threshold with an authority ladder, reassessment triggers, and a calibration test on five sample risks.

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Expert PE review of a submittal (shop drawings, product data, samples, equipment brochures) against specs, drawings, code questions and trade coordination. Produces findings with both sources, trade routing and a completeness gate. Triggers: 'review submittal', 'review shop drawings'.

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Systematically interpret infrared spectra to identify functional groups present in a sample. Covers diagnostic region analysis (4000-1500 cm-1), fingerprint region assessment (1500-400 cm-1), hydrogen bonding effects, and compilation of a functional group inventory with confidence levels.

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Generate jigsaw puzzles via generate_puzzle() or geom_puzzle_*() with parameter validation against inst/config.yml. Supports rectangular, hexagonal, concentric, voronoi, and snic puzzle types with configurable grid, size, seed, offset, and layout parameters. Use when creating puzzle SVG files for a specific type and configuration, testing generation with different parameters, generating sample output for documentation or demos, or creating ggplot2 puzzle visualizations.

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Design an acoustic levitation system that uses standing waves to trap and suspend small objects at pressure nodes. Covers ultrasonic transducer selection, standing wave formation between a transducer and reflector, node spacing and trapping position calculation, acoustic radiation pressure analysis, and phased array configurations for multi-axis manipulation. Use when designing contactless sample handling for chemistry, biology, materials science, or demonstration purposes.

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Evaluate and compare levitation mechanisms for a given application through a structured trade study. Covers magnetic (passive diamagnetic, active feedback, superconducting), acoustic (standing wave, phased array), aerodynamic (hovercraft, air bearings, Coanda effect), and electrostatic (Coulomb suspension, ion traps) mechanisms. Use when selecting the most appropriate levitation approach for transport, sample handling, display, bearings, or precision measurement applications.

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Select an OCR/HTR engine by benchmarking candidates on the same labelled samples — source ground truth from open datasets (e.g. Hugging Face PAGE-XML corpora) or hand-transcription, wrap every engine behind a transcribe(image_path) -> str adapter (vision-LLMs via any OpenAI-compatible endpoint, dedicated HTR REST APIs, cloud OCR), and score with zero-dependency raw CER, lenient CER, WER, and a critical name/date token diff. Use when choosing an engine for handwriting or historical-document transcription, when published accuracy claims need honest verification on your own material, or when a records workflow must surface confident-but-wrong names and dates that a low aggregate CER hides.

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Use when ingesting text samples to extract quantitative writing style metrics. Produces a structured JSON style profile with vocabulary patterns, sentence structure, tone markers, and formatting preferences. Invoke before voice-clone-generator to establish style constraints.

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Design and build runnable iOS UI mockups in SwiftUI, including UI direction, multiple visual or interaction variants, realistic sample data, state switching, Xcode Previews, and Simulator validation. Use when the user wants to explore what an iOS screen should look like, compare SwiftUI UI ideas, create a clickable native prototype, validate an app flow before production implementation, or asks for a SwiftUI mock, iOS mockup, native prototype, 画面モック, UI案, SwiftUIで動くモック, or 実際に触れるiOSモック.

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Design A/B tests with hypotheses, variants, sample sizes, and analysis plans. TRIGGERS - Use when user wants to run A/B tests, split tests, or experiment with variations.

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Use when you need authoritative classification, threat-name, MITRE ATT&CK mapping, dynamic-analysis or sandbox results on a file hash, or when you need network threat intelligence for a URL/domain/IP from ReversingLabs Spectra Analyze (A1000). Returns verdict, risk score, AV detection ratio, threat name, behavioural tags, and pivot candidates (parent containers, extracted files, related samples by family). Commonly invoked by /hash-investigation and /malware-analysis. Other agents/skills can chain this for deeper malware enrichment beyond VirusTotal.

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Prepare video URLs or local video files for GitHub Copilot analysis by extracting captions, sampled frames, contact sheets, and a prompt packet. Use when the user asks Copilot to watch, inspect, summarize, or diagnose a video, screen recording, demo, webinar, YouTube/Loom/TikTok/X/Vimeo URL, or .mp4/.mov/.mkv/.webm file.

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"Apply Partial Least Squares SEM (PLS-SEM) with reflective and formative measurement models to maximize explained variance in endogenous constructs. Use this skill when the user has small samples, formative indicators, or exploratory models, needs to assess AVE/CR/HTMT, or when they ask 'should I use PLS or CB-SEM', 'how do I handle formative constructs', or 'what is the path coefficient significance'.".

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"Apply Bayesian averaging to rank items by combining observed ratings with prior expectations. Use this skill when the user needs to rank items with varying review counts, build a 'top rated' list that handles low-sample items fairly, or implement IMDB-style weighted rating — even if they say 'weighted average rating', 'IMDB formula', or 'ranking with prior'.".

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Designing clinical trials — phases, randomization, endpoints, sample size, and CONSORT-compliant reporting.

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Developer marketing and developer relations for B2B SaaS with technical audiences. Use this skill when the buyer or user is a developer: documentation as a marketing surface, quickstarts and time-to-first-call, SDKs and sample apps, developer community and DevRel programs, open-source strategy, and technical content that survives engineer scrutiny. Also triggers on: developer marketing, DevRel, developer relations, developer experience, DX, docs, documentation, quickstart, SDK, API marketing, open source strategy, developer community, technical content, dev audience, hacker news, engineering blog.

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Design rigorous A/B test plans with hypothesis, sample size calculation, Minimum Detectable Effect (MDE), randomization strategy, and decision rules. Includes guardrail metrics and rollout playbook. Use when planning product experiments, conversion optimization, or data-driven feature decisions.

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Design, analyze, and document A/B tests for conversion, onboarding, pricing, lifecycle, and product experiments. Use when the user asks for `/ab-test-setup`, experiment design, sample size, statistical significance, A/B test analysis, ICE-scored test backlogs, or avoiding common testing mistakes.

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Detect and rewrite AI writing patterns to make content sound authentically human. Supports voice calibration from the author's own writing samples. Use when asked to humanize text, remove AI patterns, calibrate voice, audit content for AI detectability, or check if writing sounds like ChatGPT. Triggers: /humanize, /voice-calibrate, /audit-ai

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Web shell samples for detection and analysis: PHP, ASP, ASPX, JSP, Python, Perl shells. Use for security research and detection system testing.

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Execute and analyze malware samples within a highly controlled, instrumented sandbox environment to observe their true behavior, network communications, file system modifications, and registry changes in real-time.

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Identifies and unpacks packed binaries: detecting packers from section names and entropy, automatically unpacking UPX, and manually unpacking custom packers by finding the OEP and dumping. Activates for requests to unpack a packed sample, detect a packer, or recover the original binary from UPX or a custom packer.

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Structures a clear, actionable malware analysis report covering summary, sample identity, capabilities, IOCs, ATT&CK mapping, and detection guidance for both technical and decision-making audiences. Activates for requests to write, structure, or review a malware analysis or reverse-engineering report.

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Reverse engineers malware written in less-common compiled languages (Nim, Crystal, V, Zig, D) by detecting language-specific runtime signatures, name-mangling, and runtime strings to orient analysis. Activates for requests to reverse Nim malware, identify the source language of an exotic binary, or analyze Crystal/V/Zig/D compiled samples.

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