「parsing」の検索結果

Phase 2 of the prd-taskmaster pipeline: spec generation and task parsing. Loads a template (comprehensive|minimal), fills it with DISCOVER-phase constraints and answers, validates the spec (placeholders_found, grade thresholds), parses the PRD into tasks via task-master, runs TaskMaster's native complexity analysis, and expands every task into verifiable subtasks. Autonomous-safe. Declares GENERATE complete so HANDOFF can follow.

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使用Fluentd的regexp插件解析MySQL慢查询日志，将其切分为时间、用户、查询时间和SQL内容四个字段，并配置字段长度限制以避免解析错误。

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Generates a Python CLI tool for bidirectional conversion between 4-byte floating-point numbers and hexadecimal memory representations, featuring a continuous loop and robust input parsing.

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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.

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Execute long-running tasks in background isolates to keep the UI responsive. Use when performing heavy computations, parsing large datasets, or choosing between async/await and isolates.

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Build command-line apps in R using the Rapp package. Use when creating a CLI tool in R, adding argument parsing to an R script, turning an R script into a command-line app, shipping CLIs in an R package, or using Rapp (the alternative Rscript front-end). Also use for shebang scripts, exec/ directory in R packages, or subcommand-based R tools.

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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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Write robust, portable shell scripts with proper error handling, argument parsing, and testing. Use when automating system tasks, building CI/CD scripts, or creating container entrypoints.

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Build professional command-line interfaces in Python, Go, and Rust using modern frameworks like Typer, Cobra, and clap. Use when creating developer tools, automation scripts, or infrastructure management CLIs with robust argument parsing, interactive features, and multi-platform distribution.

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Use the ax CLI instead of curl + throwaway parsing scripts whenever you fetch a URL, explore an unknown web page, or extract structured data from HTML. Trigger whenever you are about to write an inline script (python3 heredoc, node -e, regex over HTML) or a bare curl for one-off web fetching, scraping, or page exploration.

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Author and review GitHub Actions workflow YAML safely so syntactically-valid YAML can't ship a workflow that GitHub Actions refuses to run. USE FOR: editing, adding, or reviewing any file under .github/workflows/, writing run-name/name/if/env/run values that contain ${{ }} expressions, diagnosing a run that fails with 'This run likely failed because of a workflow file issue' and no jobs starting, deciding when a workflow scalar must be quoted, validating workflows with actionlint. DO NOT USE FOR: authoring application YAML unrelated to GitHub Actions, Azure Pipelines, GitLab CI, or non-workflow YAML. SCOPE: this skill covers *syntactic/structural* correctness of workflow YAML (quoting, parsing, actionlint); for *semantic and functional* workflow design (what a workflow should do, agentic-workflow behavior), see .github/agents/agentic-workflows.agent.md — the two are complementary. INVOKES: actionlint (downloaded pinned binary) plus git/grep for inspection.

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Use Sep for high-performance separated-value parsing and writing in .NET, including delimiter inference, explicit parser/writer options, and low-allocation row/column workflows. USE FOR: delimited data needs are performance-sensitive and allocation-aware; project needs explicit control over separator inference, escaping, trimming, and header behavior;. DO NOT USE FOR: unrelated stacks; generic tasks that do not need this specific guidance. INVOKES: inspect the repository context, edit targeted files, and run relevant build, test, lint, or validation commands when changes are made.

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Use SharpConsoleUI to build full terminal (TUI) applications in .NET — equally suited to full-screen single-window apps and multi-window desktops with overlapping draggable windows — using a compositor, a DOM layout engine, and 40+ reactive controls (data tables, tree views, forms, an embedded PTY terminal, markdown, charts, video). USE FOR: interactive console apps, full-screen TUIs, multi-window terminal desktops, dashboards, wizards, and admin/monitoring UIs that need focus, mouse, and flicker-free rendering over local terminals or SSH; NativeAOT console tools. DO NOT USE FOR: simple line-based CLI output or argument parsing; non-interactive scripts; GUI/desktop (WPF/WinForms) or web UIs. INVOKES: inspect the project, add the SharpConsoleUI package, scaffold a window/control tree, and build/run to verify the app renders.

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Network traffic analysis, PCAP parsing, IDS/IPS rule creation, firewall configuration auditing, and network anomaly detection

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Security log parsing, anomaly detection, SIEM query building, Sigma rule creation, and correlation rule development across Splunk, Elastic, QRadar, and Microsoft Sentinel

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Decision rubric for when an LM agent should write-and-run code (Program-of-Thought / code interpreter) versus reason in natural language: classify each step as deterministic- computable (emit + execute code, feed the result back) vs judgment (stay in prose). Use when designing or debugging an agent step that does arithmetic/parsing/data transforms, when prose reasoning hallucinates a computation (under-coding), or when a sandbox round- trip is wasted on a judgment task (over-coding). Search keywords: code interpreter, agent does math wrong, calculator hallucination, when to run code vs reason, program of thought, PoT, tool vs reasoning.

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CLI command development specialist. Use when creating commands, designing argument parsing, automating tasks, or implementing CLI best practices. Specializes in command design patterns and user experience.

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PumpFun bonding curve math, graduation mechanics, instruction parsing, and PumpSwap migration

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Consult PostgreSQL's parser and grammar (gram.y) to understand SQL syntax, DDL statement structure, and parsing rules when implementing pgschema features

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Use when implementing Stripe webhook endpoints and getting 'Raw body not available' or signature verification errors - provides raw body parsing solutions and subscription period field fixes across frameworks

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Use when users need to debug, modify, or extend the code-forge application's CLI commands, argument parsing, or CLI behavior. This includes adding new commands, fixing CLI bugs, updating command options, or troubleshooting CLI-related issues.

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Pythonic wrapper around RDKit with simplified interface and sensible defaults. Preferred for standard drug discovery: SMILES parsing, standardization, descriptors, fingerprints, clustering, 3D conformers, parallel processing. Returns native rdkit.Chem.Mol objects. For advanced control or custom parameters, use rdkit directly.

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Primary Python toolkit for molecular biology. Preferred for Python-based PubMed/NCBI queries (Bio.Entrez), sequence manipulation, file parsing (FASTA, GenBank, FASTQ, PDB), advanced BLAST workflows, structures, phylogenetics. For quick BLAST, use gget. For direct REST API, use pubmed-database.

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Guide to interpreting BUSCO completeness statuses: why Duplicated BUSCOs count as complete, parsing output files, computing/comparing completeness across proteomes/genomes, common counting mistakes. Use when running BUSCO QC, comparing assemblies, or reporting completeness. See also: prokka-genome-annotation for annotation workflows feeding BUSCO.

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