「parsing」の検索結果

Detect unauthorized SaaS and cloud service usage (shadow IT) by parsing proxy access logs, DNS query logs, and firewall/netflow data with Python pandas to aggregate traffic by domain, classify domains against known SaaS categories, and score risk by data volume and user count. Use when auditing an organization for unsanctioned cloud/SaaS usage or generating a shadow IT discovery report with remediation recommendations.

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Parses Software Bill of Materials (SBOM) in CycloneDX and SPDX JSON formats to identify supply chain vulnerabilities by correlating components against the NVD CVE database via the NVD 2.0 API. Builds dependency graphs, calculates risk scores, identifies transitive vulnerability paths, and generates compliance reports. Activates for requests involving SBOM analysis, software composition analysis, supply chain security assessment, dependency vulnerability scanning, CycloneDX/SPDX parsing, or CVE correlation.

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Reverse engineer Go-compiled malware in Ghidra by parsing Go buildinfo and pclntab structures, recovering stripped/obfuscated function names (e.g. via GoResolver), and extracting embedded module/dependency strings and types from Go binaries. Use when analyzing a Go-language malware sample, deobfuscating a garble-packed Go binary, or recovering function names and third-party dependencies from a stripped Go executable.

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Analyze Windows LNK shortcut files and Jump List artifacts with LECmd, JLECmd, and manual Shell Link Binary Format parsing to establish evidence of file access, program execution, and user activity that persists even after the target file is deleted. Use when investigating Windows user activity, reconstructing file-access or program-execution timelines, or examining recent/frequently-used file evidence in a forensic exam.

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Parse and analyze Cobalt Strike Malleable C2 profiles with dissect.cobaltstrike (profiles and beacon-payload configs) and pyMalleableC2 (AST parsing) to extract HTTP/DNS transforms, URIs, headers, sleep/jitter, and injection behavior, then generate network detection signatures. Use when reverse-engineering a captured malleable profile or building detections against Cobalt Strike Beacon traffic.

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Optimize resumes for Applicant Tracking Systems, check ATS compatibility, and analyze keyword match. Use when the user mentions ATS, applicant tracking, keyword optimization, parsing, or getting past resume screening software.

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Extract structured data from LLM responses with Pydantic validation, retry failed extractions automatically, parse complex JSON with type safety, and stream partial results with Instructor - battle-tested structured output library

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Use this skill any time a .pptx file is involved -- as input, output, or both. This includes: creating slide decks, pitch decks, or presentations; reading, parsing, or extracting text from any .pptx file; editing, modifying, or updating existing presentations; combining or splitting slide files; working with templates, layouts, speaker notes, or comments. Trigger whenever the user mentions 'deck', 'slides', 'presentation', 'pitch', or references a .pptx filename.

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Use this skill any time a .docx file is involved -- as input, output, or both. This includes: creating Word documents, reports, letters, memos, or proposals; reading, parsing, or extracting text from any .docx file; editing, modifying, or updating existing documents; working with templates, tracked changes, comments, headers/footers, or tables of contents. Trigger whenever the user mentions 'Word doc', 'document', 'report', 'letter', 'memo', or references a .docx filename.

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Use this skill any time a .xlsx file is involved -- as input, output, or both. This includes: creating spreadsheets, financial models, dashboards, or trackers; reading, parsing, or extracting data from any .xlsx file; editing, modifying, or updating existing workbooks; working with formulas, charts, pivot tables, or templates; importing CSV/TSV data into Excel format. Trigger whenever the user mentions 'spreadsheet', 'workbook', 'Excel', 'financial model', 'tracker', 'dashboard', or references a .xlsx/.csv filename.

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Produce consistent, auditable release notes from Conventional Commits. Separates commit parsing, semantic-bump logic, and changelog rendering for automated releases with editorial control. Use when cutting a release, generating CHANGELOG.md from git history, computing the next semantic version from commits, automating release notes in CI, or planning a hotfix/rollback. Examples: 'generate the changelog for v1.4.0', 'what version bump do these commits require', 'we need an emergency hotfix process'.

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Use when an RFP, RFI, RFQ, security questionnaire, vendor questionnaire, or proposal request arrives and the team needs a structured response — parsing multi-section buyer-dictated requirements (MANDATORY vs WEIGHTED vs NICE-TO-HAVE), building a Shipley-method proof-point matrix mapping each requirement to a verifiable proof point, articulating 3-5 win-themes that ladder up across requirements, and producing a Shipley-derived winrate estimate that informs a bid / no-bid / partner-bid recommendation. For Bid Managers, Proposal Leads, Directors of Sales, and Sales Engineers at the response-strategy moment. Surfaces GAP requirements explicitly — never invents claims. NOT free-form proposal narrative authoring, NOT contract redline, NOT marketing collateral.

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Mandatory routing rules for Antigravity CLI. Invoke when exploring a codebase, reading files for analysis, listing context-mode tools, searching, parsing, counting, comparing, summarizing, fetching web content, or running data-heavy commands.

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Write JavaScript or Python for the n8n Custom Code Tool (@n8n/n8n-nodes-langchain.toolCode) — the AI-agent-callable tool, NOT the workflow Code node. Use when building a Code Tool attached to an AI Agent, writing code that an LLM will invoke, parsing the `query` input, returning a string result, defining an input schema for structured arguments (specifyInputSchema, jsonSchemaExample, DynamicStructuredTool), or troubleshooting errors like "Wrong output type returned", "No execution data available", "The response property should be a string, but it is an object", "Cannot assign to read only property 'name'", or an AI agent that refuses to call the tool. Covers the critical differences between Code node and Code Tool: return format (string vs `[{json:{...}}]`), unavailability of `$fromAI`/`$input`/`$helpers` in the Code Tool sandbox, naming rules for AI invocation, and when to use `toolWorkflow`/HTTP Request Tool instead.

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Generates production-ready TypeScript CLIs via a 3-tier template system (manual arg parsing, Commander.js, oclif), each shipping full implementation, docs, package.json, strict config, JSON output, and exit-code compliance. USE WHEN create CLI, build CLI, command-line tool, wrap API, add command, upgrade tier, TypeScript CLI. NOT FOR LifeOS skill scaffolding (use CreateSkill).

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Search and retrieve arXiv academic papers by topic, category, or paper ID — with AlphaXiv-enriched AI-generated overviews. Uses arXiv Atom API across cs.AI/cs.LG/cs.CL/cs.CR/cs.MA/cs.SE/cs.IR. Three workflows: Latest, Search, Paper. USE WHEN arxiv, papers, latest papers, research papers, recent ML papers, paper lookup, summarize paper, latest LLM papers, AI safety papers, cs.AI latest. NOT FOR general research (Research), URL parsing, or annual reports.

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This skill should be used for project-level decisions about LLM-powered systems: whether an LLM is the right primitive for the task at hand, the shape of a multi-stage batch or agent pipeline, token and cost estimation, choosing between single-agent and multi-agent at the project level, structured output design for downstream parsing, and structuring agent-assisted iteration. Use this when the unit of work is a whole project or a multi-stage pipeline. Route individual tool design to tool-design and individual skill-loading or context-budget tactics to context-optimization.

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Use this skill any time a .pptx file is involved in any way — as input, output, or both. This includes: creating slide decks, pitch decks, or presentations; reading, parsing, or extracting text from any .pptx file (even if the extracted content will be used elsewhere, like in an email or summary); editing, modifying, or updating existing presentations; combining or splitting slide files; working with templates, layouts, speaker notes, or comments. Trigger whenever the user mentions "deck," "slides," "presentation," or references a .pptx filename, regardless of what they plan to do with the content afterward. If a .pptx file needs to be opened, created, or touched, use this 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。

Extract structured data from LLM responses with Pydantic validation, retry failed extractions automatically, parse complex JSON with type safety, and stream partial results with Instructor - battle-tested structured output library

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。

CCPM - spec-driven project management: PRD → Epic → GitHub Issues → parallel agents → shipped code. Use this skill for anything in the software delivery lifecycle: writing a PRD ('write a PRD for X', 'let's plan X', 'scope this out'), parsing a PRD into an epic, decomposing an epic into tasks, syncing to GitHub ('sync the X epic', 'push tasks to github'), starting work on an issue ('start working on issue N', 'let's work on issue N'), analyzing parallel work streams, running standups ('standup', 'run the standup'), checking status ('what's next', 'what's blocked', 'what are we working on'), closing issues, or merging an epic. Use ccpm any time the user is talking about shipping a feature, managing work, or tracking progress — even if they don't say 'ccpm' or 'PRD'. Do NOT use for: debugging code, writing tests, reviewing PRs, or raw GitHub issue/PR operations with no delivery context.

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Handle Excel files with irregular headers, merged cells, and unknown header row positions using pattern-matching and index-based extraction.

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。

Audio production with diagnostic analysis, timecode parsing from documents, and verified export workflow

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。

Parses and processes SARIF files from static analysis tools like CodeQL, Semgrep, or other scanners. Triggers on "parse sarif", "read scan results", "aggregate findings", "deduplicate alerts", or "process sarif output". Handles filtering, deduplication, format conversion, and CI/CD integration of SARIF data. Does NOT run scans — use the Semgrep or CodeQL skills for that.

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Scans a codebase for security vulnerabilities using CodeQL's interprocedural data flow and taint tracking analysis. Triggers on "run codeql", "codeql scan", "build codeql database", "SAST scan", "taint analysis", "dataflow analysis", or "find vulnerabilities in this repo". Covers Python, JavaScript/TypeScript, Go, Java/Kotlin, C/C++, C#, Ruby, and Swift. Supports "run all" (security-and-quality + security-experimental) and "important only" (high-precision) scan modes, and creates data extension models for project-specific sources and sinks. For fast single-file pattern matching, or when no build is available for a compiled language, use the semgrep skill; to parse SARIF that already exists rather than produce it, use the sarif-parsing 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。