「code analysis」の検索結果

Deobfuscates malicious JavaScript code used in web-based attacks, phishing pages, and dropper scripts by reversing encoding layers, eval chains, string manipulation, and control flow obfuscation to reveal the original malicious logic. Activates for requests involving JavaScript malware analysis, script deobfuscation, web skimmer analysis, or obfuscated dropper investigation.

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。

Perform static analysis of malicious PDF documents using peepdf, pdfid, and pdf-parser to extract embedded JavaScript, shellcode, and suspicious objects.

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。

Identifies and unpacks UPX-packed and other packed malware samples to expose the original executable code for static analysis. Covers both standard UPX unpacking and handling modified UPX headers that prevent automated decompression. Activates for requests involving malware unpacking, UPX decompression, packer removal, or preparing packed samples for 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。

Standard procedure for onboarding new software projects: Feature analysis, code quality review, onboarding checklist, and task creation.

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。

Developer assistant (ATI successor). Provides a quick project overview via headless scan and routes to the available coding tools: CodeCommander MCP (analysis/refactor/diagnose) and the ellmos-code-tools module. Pure tool routing + scan, no own store.

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。

Perform root cause analysis on a bug fix. Use when the user says 'run RCA on [commit/PR]', 'root cause analysis', or 'analyze what caused this bug'. Accepts a commit SHA, PR number, issue, or description of a fix.

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。

Use when working with Aws Codecommit — aWS CodeCommit repository management and analysis. Covers repository inventory, branch details, pull request status, commit history, approval rules, and trigger configurations. Use when inspecting repositories, reviewing pull requests, auditing branch policies, or analyzing commit activity.

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。

Use when working with Aws Codepipeline — aWS CodePipeline CI/CD pipeline management and execution analysis. Covers pipeline inventory, stage and action status, execution history, pipeline triggers, artifact stores, and action type configurations. Use when inspecting pipeline health, debugging failed stages, reviewing execution history, or auditing pipeline configurations.

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。

Use when working with Aws Codebuild — aWS CodeBuild project management and build analysis. Covers build project inventory, build history, build phase details, environment configurations, source credentials, report groups, and build metrics. Use when inspecting build projects, debugging build failures, reviewing build environments, or analyzing build performance.

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。

Analyze git repositories to build a security ownership topology (people-to-file), compute bus factor and sensitive-code ownership, and export CSV/JSON for graph databases and visualization. Trigger only when the user explicitly wants a security-oriented ownership or bus-factor analysis grounded in git history (for example: orphaned sensitive code, security maintainers, CODEOWNERS reality checks for risk, sensitive hotspots, or ownership clusters). Do not trigger for general maintainer lists or non-security ownership questions.

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。

Use only when the user explicitly requests strict code-cell-only output for a Jupyter or undergraduate data-science task, or when an ITX2007 assignment requires that format. Do not activate for ordinary data analysis or explanation requests.

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。

Audit Xcode project configuration, build settings, scheme behavior, and script phases to find build-time improvements with explicit approval gates. Use when a developer wants project-level build analysis, slow incremental builds, guidance on target dependencies, build settings review, run script phase analysis, parallelization improvements, or module-map and DEFINES_MODULE configuration.

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。

Apply approved Xcode build optimization changes following best practices, then re-benchmark to verify improvement. Use when a developer has an approved optimization plan from xcode-build-orchestrator, wants to apply specific build fixes, needs help implementing build setting changes, script phase guards, source-level compilation fixes, or SPM restructuring that was recommended by an analysis skill.

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。

Detects and prevents code injection attacks targeting serverless functions (AWS Lambda, Azure Functions, Google Cloud Functions) through event source poisoning, malicious layer injection, runtime command execution, and IAM privilege escalation via function modification. The analyst combines static analysis of function code, CloudTrail event correlation, runtime behavior monitoring, and IAM policy auditing to identify injection vectors across the expanded serverless attack surface including API Gateway, S3, SQS, DynamoDB Streams, and CloudWatch event triggers. Activates for requests involving Lambda security assessment, serverless injection detection, function event poisoning analysis, or serverless privilege escalation investigation.

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。

Deobfuscates malicious JavaScript code used in web-based attacks, phishing pages, and dropper scripts by reversing encoding layers, eval chains, string manipulation, and control flow obfuscation to reveal the original malicious logic. Activates for requests involving JavaScript malware analysis, script deobfuscation, web skimmer analysis, or obfuscated dropper investigation.

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。

Perform static analysis of malicious PDF documents using peepdf, pdfid, and pdf-parser to extract embedded JavaScript, shellcode, and suspicious objects.

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。

Identifies and unpacks UPX-packed and other packed malware samples to expose the original executable code for static analysis. Covers both standard UPX unpacking and handling modified UPX headers that prevent automated decompression. Activates for requests involving malware unpacking, UPX decompression, packer removal, or preparing packed samples for 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。

Financial analyst agent skill and plugin for Claude Code, Codex, Gemini CLI, Cursor, OpenClaw. Ratio analysis, DCF valuation, budget variance, rolling forecasts. 4 Python tools (stdlib-only).

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。

Deep, excruciating code review. Use anytime to analyze code for correctness, edge cases, security, performance, and design issues. Not tied to baseline—this is pure code 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。

Expert code reviewer specializing in code quality, security vulnerabilities, and best practices across multiple languages. Masters static analysis, design patterns, and performance optimization with focus on maintainability and technical debt reduction.

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。

Assesses RNA-seq data quality specifically for alternative splicing analysis. QC layers include experimental design audit (library prep, read length, depth, replicates), STAR 2-pass cohort-style alignment, junction saturation curves and discovery plateau detection, novel-vs-known junction ratio diagnostics, junction-overhang distribution, splice-site strength scoring (MaxEntScan intrinsic + SpliceAI context-aware), strandedness verification, GENCODE basic vs comprehensive choice, and rRNA contamination screening. Splicing analysis is more demanding than DGE on read length, depth, library prep, alignment strategy, and annotation choice — failures silently bias PSI estimates and inflate novel-junction false positives. Use when evaluating data suitability for splicing analysis, troubleshooting low event detection, or designing sequencing experiments where AS is a primary endpoint.

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。

Assesses RNA-seq data quality specifically for alternative splicing analysis. QC layers include experimental design audit (library prep, read length, depth, replicates), STAR 2-pass cohort-style alignment, junction saturation curves and discovery plateau detection, novel-vs-known junction ratio diagnostics, junction-overhang distribution, splice-site strength scoring (MaxEntScan intrinsic + SpliceAI context-aware), strandedness verification, GENCODE basic vs comprehensive choice, and rRNA contamination screening. Splicing analysis is more demanding than DGE on read length, depth, library prep, alignment strategy, and annotation choice — failures silently bias PSI estimates and inflate novel-junction false positives. Use when evaluating data suitability for splicing analysis, troubleshooting low event detection, or designing sequencing experiments where AS is a primary endpoint.

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。

Conduct multi-round deep research on any GitHub Repo. Use when users request comprehensive analysis, timeline reconstruction, competitive analysis, or in-depth investigation of GitHub. Produces structured markdown reports with executive summaries, chronological timelines, metrics analysis, and Mermaid diagrams. Triggers on Github repository URL or open source projects.

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。

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?"

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。