「code analysis」の検索結果

Use when the user wants to know what will break if they change something, or needs safety analysis before editing code. Examples: "Is it safe to change X?", "What depends on this?", "What will break?"

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Evaluate code (especially LLM-generated) for structural simplicity using Rich Hickey's "Simple Made Easy" framework. Use this skill whenever reviewing a PR, diff, or code snippet for accidental complexity — particularly when the code was generated by an AI coding assistant and line-by-line review isn't feasible. Also use when the user asks about complecting, simplicity vs. easiness, structural coupling, or concept deduplication. Trigger on phrases like "is this simple", "does this complect", "review for complexity", "structural analysis", or any reference to Hickey, Simple Made Easy, or grey-box review.

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Run a retro for personal global ~/.copilot assets and turn incident learnings into updates for copilot-instructions, instructions, skills, agents, and hooks. Not for workspace/repository assets, VS Code User Data assets, or a private skills repository. Triggers on retro, retrospective, incident learning, error analysis, copilot setup, instructions update, インシデント, and 知見反映.

Super Base Context — project doc loader & synchronizer. Triggers even without explicit "load docs"/"sync docs." READ MODE — load architecture/modules/coding/decision docs when work references project state: code work (write/modify/remove); design (features/APIs/schemas/architecture); review (modules, past solutions); tech selection; ADR research; migration/refactor planning; performance/security analysis; tests; code reviews; any spec/plan/design/ADR referencing project. WRITE MODE — NET DELTA vs. last doc sync: additions/modifications/REMOVALS/deprecations of previously-synced code or decisions (docs revert: delete BCU file/ADR), AND rollbacks. User signals: sync docs/done/ready to commit/pre-commit/record decision. Auto-fires before final task-completion reply. WRITE MODE does NOT fire on: brainstorming, generic/read-only Q&A, in-session try-and-undo with no net change, already-synced.

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Validate Rust code quality with rustfmt, clippy, cargo check, and security analysis. Use for Rust codebases to ensure idiomatic Rust code and best practices.

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Validate Python code quality with formatting, type checking, linting, and security analysis. Use for Python codebases to ensure PEP 8 compliance, type safety, and code quality.

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Validate TypeScript/JavaScript code quality with ESLint, Prettier, type checking, and security analysis. Use for TypeScript/JS codebases to ensure code quality and standards.

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Multi-language code quality validation (Python, JS/TS, Shell, SQL) — formatting, linting, type-checking, complexity analysis with auto language detection. Use when checking code quality or running linters. Trigger on "lint", "type-check", "quality check", "run the linters", "check code quality".

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Write structured legal memoranda following the Issue-Rule-Analysis-Conclusion (IRAC) framework. Suitable for internal legal opinions, advisory memos, and compliance assessments. Use when legal analysis needs to be documented for decision-makers. Do not use as a substitute for licensed legal advice on high-stakes matters.

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Conduct strategic analysis using Porter's Five Forces, PESTEL, and SWOT frameworks. Assess competitive dynamics, macro environment, and internal capabilities. Synthesize into strategic implications with ranked options. Use when entering new markets, evaluating competitive position, or strategic planning.

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Read and interpret financial statements — Income Statement, Balance Sheet, and Cash Flow Statement. Calculate key ratios, identify trends, and produce an analysis narrative. Use when reviewing company performance, preparing for investor meetings, or conducting due diligence. Do not use for preparing or auditing financial statements — this is an analysis tool only.

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Full ASVS 5.0 compliance assessment against a codebase and/or architecture diagrams. Reads all 346 controls from the companion CSV, performs targeted code analysis per control, and produces a complete matrix marked COMPLIANT / NON_COMPLIANT / NOT_RELEVANT — with per-control reasoning and evidence (code snippets, file:line references, diagram observations). Outputs a reviewed CSV matrix and a self-contained HTML evidence report.

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This skill provides expert-level guidance for debugging and fixing bugs in VS Code extensions. Use when investigating runtime errors, fixing memory leaks, resolving WebView issues, debugging activation problems, fixing TypeScript type errors, or troubleshooting extension communication failures. Covers systematic debugging workflows, common bug patterns, root cause analysis, and prevention strategies.

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Automates IDA Pro analysis with IDAPython by generating scripts that enumerate functions, decode strings, rename by signature, and export analysis results, and by documenting the headless idat batch invocation. Activates for requests to script IDA Pro, write IDAPython automation, or run IDA in batch/headless mode.

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Statically analyzes macOS Mach-O malware: parsing the header and load commands, handling fat/universal binaries, reading linked dylibs and entitlements, and checking code signatures to infer capability and trust. Activates for requests to analyze a Mach-O binary, inspect macOS malware, or parse load commands and entitlements.

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Deobfuscates malicious JavaScript from droppers, web pages, and HTA/scriptlets: unrolling string-array and char-code encodings, resolving eval/Function chains, and statically recovering payloads and URLs without executing untrusted code. Activates for requests to deobfuscate JavaScript, decode obfuscated JS, or analyze a malicious script dropper.

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N-round adversarial review pipeline for empirical research output — the chain from data to LaTeX tables to a manuscript that cites them. A Claude drafter proposes minimal diffs, a deterministic mechanical battery gates every diff from a clean state with a regression gate, a Codex reviewer files check-backed critiques, and a blind judge panel decides residual disputes. Manual-invoke ONLY: trigger when the user explicitly runs /adversarial-empirical-review or names 'adversarial-empirical-review' / 'adversarial empirical review'. Do NOT auto-trigger on generic 'review my results', 'check my tables', or manuscript-editing requests. For prose-style refinement use style-emulation instead; this skill AUDITS WHETHER THE TABLES ARE CORRECT — that each number in the tables is what the analysis code computes, reproduces from the data, and is internally consistent. It is an empirical + code review: the manuscript is read only to resolve table numbering, and prose is not examined.

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Analyze ENCODE functional genomics screens including CRISPR screens, MPRA (Massively Parallel Reporter Assays), and STARR-seq. Find screen data in ENCODE, process results, identify functional elements, and integrate with epigenomic annotations.

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Evaluate ENCODE experiment quality using standard metrics and audit flags. Use when the user asks about data quality, wants to filter for high-quality experiments, needs to interpret quality metrics (FRiP, NSC, RSC, NRF, IDR, TSS enrichment, fragment size), wants to understand ENCODE audit warnings, needs to compare quality across experiments, or is deciding whether data is usable for their analysis. Also use when the user mentions QC, quality control, or data filtering.

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Integrate multiple ENCODE data types (RNA-seq, ATAC-seq, Histone ChIP-seq, TF ChIP-seq) for a tissue/cell type to build a comprehensive regulatory landscape. Use when the user wants to answer "what are the enhancers, promoters, and regulatory elements active in my tissue, and which transcription factors control them?" by layering expression, chromatin accessibility, histone marks, and TF binding data. Follows the Mawla et al. 2023 framework for cross-assay integration of islet cell type-specific data. Handles chromatin state annotation (ChromHMM), enhancer-gene linkage, TF motif enrichment, and cell type-specific regulatory element identification. Use for ANY multi-omic analysis, enhancer discovery, regulatory network construction, or epigenomic characterization using ENCODE data.

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Evaluate code (especially LLM-generated) for structural simplicity using Rich Hickey's "Simple Made Easy" framework. Use this skill whenever reviewing a PR, diff, or code snippet for accidental complexity — particularly when the code was generated by an AI coding assistant and line-by-line review isn't feasible. Also use when the user asks about complecting, simplicity vs. easiness, structural coupling, or concept deduplication. Trigger on phrases like "is this simple", "does this complect", "review for complexity", "structural analysis", or any reference to Hickey, Simple Made Easy, or grey-box review.

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Systematic technical debt analysis across architecture, testing, documentation, and infrastructure. Investigates the codebase, scores findings by impact and effort, and generates a prioritized TECH_DEBT.md remediation plan. Delegates to specialized skills for code quality (scout) and linting (lint-fix). Use when assessing overall project health, planning cleanup sprints, or onboarding to an unfamiliar codebase.

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General code quality review — project guideline compliance, bug detection, code quality analysis.

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。

fMRI data analysis — preprocessing, GLM modeling, and group-level inference for task and resting-state studies.

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。