{"passport":{"unfragile":{"@version":"1.0","version":"2026-05","artifact":{"id":"github-nikolaydubina--go-recipes","slug":"nikolaydubina--go-recipes","name":"go-recipes","type":"repo","url":"https://github.com/nikolaydubina/go-recipes","page_url":"https://unfragile.ai/nikolaydubina--go-recipes","categories":["frameworks-sdks"],"tags":["awesome","awesome-list","benchmarking","code-generation","code-visualization","command-line-tool","compilers","data-visualization","developer-tools","documentation","go","golang","profiling","static-analysis","tests","visualization"],"pricing":{"model":"open_source","free":true,"starting_price":null},"status":"active","verified":false},"capabilities":[{"id":"github-nikolaydubina--go-recipes__cap_0","uri":"capability://automation.workflow.yaml.to.markdown.documentation.generation.with.structured.content.transformation","name":"yaml-to-markdown documentation generation with structured content transformation","description":"Transforms a single source-of-truth YAML file (page.yaml) into formatted README.md documentation using the mdpage tool. The system parses hierarchical YAML structures defining tool categories, entries, and metadata, then applies templating rules to generate consistent markdown output with table of contents, section headers, and formatted tool descriptions. This content-as-code approach ensures documentation consistency and enables programmatic updates without manual markdown editing.","intents":["Generate consistent documentation from a structured data source without manual markdown editing","Maintain a single source of truth for tool catalog that can be version-controlled and audited","Automate documentation updates when tools or categories change","Create reproducible documentation builds with consistent formatting across all entries"],"best_for":["Go developers maintaining curated tool collections or knowledge bases","Technical documentation teams needing version-controlled, programmatically-generated docs","Open-source projects with frequently-updated tool catalogs"],"limitations":["Requires manual YAML structure maintenance — no GUI editor for content updates","Template customization requires modifying mdpage tool source code","No built-in support for dynamic content or real-time tool metadata fetching","YAML schema changes require coordination across page.yaml and mdpage parsing logic"],"requires":["Go 1.13+ (mdpage tool is written in Go)","page.yaml file with valid YAML syntax following go-recipes schema","Write access to repository for README.md generation"],"input_types":["YAML structured data (page.yaml with tool definitions, categories, metadata)"],"output_types":["Markdown formatted text (README.md with HTML headers, tables of contents, formatted sections)"],"categories":["automation-workflow","documentation-generation"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-nikolaydubina--go-recipes__cap_1","uri":"capability://memory.knowledge.curated.go.tool.discovery.and.reference.indexing.across.15.development.categories","name":"curated go tool discovery and reference indexing across 15+ development categories","description":"Aggregates and organizes a comprehensive catalog of Go development tools, commands, and techniques across 15+ functional categories (Testing, Dependencies, Code Visualization, Code Generation, Refactoring, Error Handling, Build, Assembly, Execution, Monitoring, Benchmarking, Documentation, Security, Static Analysis, AI Tools). Each tool entry includes installation instructions, usage examples, prerequisites, and categorization, enabling developers to discover lesser-known utilities and patterns relevant to their specific workflow stage. The repository acts as a searchable knowledge base indexed by development phase and tool type.","intents":["Discover Go tools and techniques for a specific development task (e.g., 'how do I visualize code dependencies?')","Find installation and usage examples for lesser-known Go utilities without searching multiple sources","Learn about Go development patterns and best practices organized by workflow stage","Compare alternative tools within a category to choose the best fit for a project"],"best_for":["Go developers seeking to expand their toolkit beyond standard library and well-known packages","Teams onboarding new Go developers who need a structured reference for Go ecosystem tools","Open-source maintainers looking for tools to improve code quality, testing, or documentation"],"limitations":["Catalog is manually curated — not automatically updated when tools release new versions","No integration with package registries (pkg.go.dev) to verify tool availability or versions","Tool descriptions are static snapshots — may become outdated if tools change significantly","No search functionality beyond GitHub's text search or browser find-in-page"],"requires":["Go 1.13+ (for most tools in the catalog)","Internet access to clone repository and install referenced tools","Familiarity with Go development workflow to understand tool categories"],"input_types":["User queries (natural language search for tool categories or use cases)"],"output_types":["Structured tool catalog (markdown with tool names, descriptions, installation commands, examples, prerequisites)"],"categories":["memory-knowledge","search-retrieval"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-nikolaydubina--go-recipes__cap_10","uri":"capability://automation.workflow.go.playground.and.interpreter.environments.for.interactive.execution","name":"go playground and interpreter environments for interactive execution","description":"Indexes Go execution environments including the official Go Playground, local interpreters, and interactive REPL tools that enable developers to execute Go code snippets without compilation. Tools support code sharing, version selection, and integration with documentation. This enables rapid prototyping, learning, and code sharing.","intents":["Execute Go code snippets interactively without local setup or compilation","Share executable code examples with colleagues or in documentation","Prototype and test code ideas quickly before integrating into projects","Learn Go language features through interactive experimentation"],"best_for":["Go learners and educators teaching Go concepts","Developers prototyping code ideas quickly","Teams sharing executable code examples in documentation or issues"],"limitations":["Go Playground has execution time limits (a few seconds) — cannot run long-running code","Playground has restricted access to standard library (no network, file I/O)","Local interpreters are not official Go tools — may have compatibility issues","Playground code cannot import external packages — limited to standard library"],"requires":["Internet access (for official Go Playground)","Optional: local interpreter installation for offline execution"],"input_types":["Go source code snippets"],"output_types":["Execution output (stdout, stderr)","Shareable playground URLs"],"categories":["automation-workflow","text-generation-language"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-nikolaydubina--go-recipes__cap_11","uri":"capability://data.processing.analysis.runtime.monitoring.goroutine.analysis.and.profiling.tool.reference","name":"runtime monitoring, goroutine analysis, and profiling tool reference","description":"Documents Go runtime monitoring tools including goroutine analyzers, memory profilers (pprof, memprof), CPU profilers, and runtime metrics collectors. Tools are indexed with examples showing how to enable profiling, analyze goroutine leaks, detect memory issues, and monitor runtime behavior. This enables developers to diagnose performance issues and resource leaks in production.","intents":["Profile CPU usage to identify hot functions and optimization opportunities","Analyze memory allocation patterns and detect memory leaks","Monitor goroutine count and detect goroutine leaks","Collect runtime metrics and trace execution for performance analysis"],"best_for":["Go teams operating production services requiring performance monitoring","Developers debugging performance issues and resource leaks","Projects implementing comprehensive observability and monitoring"],"limitations":["Profiling adds overhead — may impact performance of profiled application","Profiling data requires interpretation — raw profiles are difficult to understand","Goroutine analysis tools cannot automatically detect all types of leaks","Memory profiling may miss short-lived allocations or fragmentation issues"],"requires":["Go 1.13+","pprof tool (built into Go runtime)","Optional: external profiling tools (Datadog, New Relic) for production monitoring"],"input_types":["Running Go applications with profiling enabled","CPU and memory profiles (pprof format)"],"output_types":["Profile visualizations (flame graphs, call graphs)","Memory allocation reports","Goroutine analysis and leak detection results"],"categories":["data-processing-analysis","monitoring-profiling"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-nikolaydubina--go-recipes__cap_12","uri":"capability://data.processing.analysis.benchmarking.and.performance.testing.framework.reference","name":"benchmarking and performance testing framework reference","description":"Indexes Go benchmarking tools and techniques including the standard testing.B framework, benchmark runners (benchstat, benchcmp), and performance regression detection tools. Tools are documented with examples showing how to write benchmarks, compare performance across versions, and detect regressions. This enables developers to measure and optimize performance systematically.","intents":["Write and run benchmarks to measure function performance","Compare benchmark results across code versions to detect performance regressions","Analyze benchmark variance and statistical significance","Integrate benchmarking into CI/CD pipelines for continuous performance monitoring"],"best_for":["Go teams implementing performance-driven development practices","Projects requiring continuous performance monitoring and regression detection","Developers optimizing performance-critical code paths"],"limitations":["Benchmarks are sensitive to system load and environment — results may vary across runs","Benchmark results require statistical analysis — simple comparisons can be misleading","Benchmarking adds complexity to test suites — requires discipline to maintain","Micro-benchmarks may not reflect real-world performance characteristics"],"requires":["Go 1.13+","Standard testing package knowledge","Optional: benchstat or benchcmp tools for statistical analysis"],"input_types":["Go benchmark code (testing.B functions)","Benchmark result files (from 'go test -bench')"],"output_types":["Benchmark execution results (ns/op, B/op, allocs/op)","Performance comparison reports","Regression detection alerts"],"categories":["data-processing-analysis","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-nikolaydubina--go-recipes__cap_13","uri":"capability://text.generation.language.documentation.generation.and.enhancement.tool.catalog","name":"documentation generation and enhancement tool catalog","description":"Indexes Go documentation tools including godoc, pkgsite, and documentation generators that extract comments and generate formatted documentation. Tools are documented with examples showing how to write effective documentation comments, generate HTML documentation, and integrate documentation into CI/CD pipelines. This enables developers to maintain high-quality, automatically-generated documentation.","intents":["Generate formatted HTML documentation from Go source code comments","Write effective documentation comments following Go conventions","Host and serve documentation for packages and modules","Integrate documentation generation into CI/CD pipelines"],"best_for":["Go library and package maintainers documenting public APIs","Teams implementing documentation-driven development practices","Projects requiring automated documentation generation and hosting"],"limitations":["Documentation quality depends on comment quality — tools cannot improve poor comments","godoc has limited formatting capabilities — complex documentation may require custom tools","Documentation generation requires discipline to maintain — comments can become outdated","Integration with external documentation platforms requires custom scripting"],"requires":["Go 1.13+","godoc tool (built into Go toolchain)","Optional: pkgsite or custom documentation generators"],"input_types":["Go source code with documentation comments"],"output_types":["HTML formatted documentation","Markdown documentation","Hosted documentation websites"],"categories":["text-generation-language","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-nikolaydubina--go-recipes__cap_14","uri":"capability://safety.moderation.security.vulnerability.scanning.and.dependency.auditing","name":"security vulnerability scanning and dependency auditing","description":"Documents Go security tools including vulnerability scanners (govulncheck, nancy), dependency auditors (go mod audit), and security analysis tools that detect known vulnerabilities in dependencies and code. Tools are indexed with examples showing how to scan for vulnerabilities, audit dependencies, and integrate security checks into CI/CD pipelines. This enables developers to maintain secure codebases and track security issues.","intents":["Scan dependencies for known security vulnerabilities","Audit go.mod files for vulnerable package versions","Detect security issues in code patterns and configurations","Integrate security scanning into CI/CD pipelines for continuous monitoring"],"best_for":["Go teams implementing security-first development practices","Projects with strict security requirements and compliance obligations","Organizations requiring continuous vulnerability monitoring"],"limitations":["Vulnerability databases are not comprehensive — some vulnerabilities may not be detected","False positives are common — not all detected issues are exploitable in context","Vulnerability scanning requires network access to vulnerability databases","Remediation requires manual code changes — tools cannot automatically patch vulnerabilities"],"requires":["Go 1.13+","govulncheck tool (built into Go 1.18+)","Internet access to vulnerability databases","Optional: nancy or other third-party vulnerability scanners"],"input_types":["go.mod and go.sum files","Go source code (for code analysis)"],"output_types":["Vulnerability reports (text, JSON, or HTML format)","Dependency audit results","Remediation recommendations"],"categories":["safety-moderation","data-processing-analysis"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-nikolaydubina--go-recipes__cap_15","uri":"capability://safety.moderation.static.analysis.and.code.quality.checking.tool.reference","name":"static analysis and code quality checking tool reference","description":"Indexes Go static analysis tools including linters (golangci-lint, go vet), code quality checkers (gocyclo, gofmt), and style enforcement tools. Tools are documented with examples showing how to configure linters, enforce code style, detect code smells, and integrate analysis into CI/CD pipelines. This enables developers to maintain consistent code quality and catch issues early.","intents":["Detect code quality issues and potential bugs through static analysis","Enforce consistent code style and formatting across teams","Measure code complexity and identify overly complex functions","Integrate static analysis into CI/CD pipelines for continuous quality monitoring"],"best_for":["Go teams implementing code quality standards and style guides","Projects requiring continuous code quality monitoring","Organizations with strict code review and quality requirements"],"limitations":["Static analysis tools produce false positives — not all flagged issues are real problems","Linter configuration requires discipline — overly strict rules can slow development","Static analysis cannot detect all types of issues (e.g., logic errors, performance problems)","Tool integration requires CI/CD pipeline configuration and maintenance"],"requires":["Go 1.13+","go vet tool (built into Go toolchain)","Optional: golangci-lint or other linter aggregators"],"input_types":["Go source code (*.go files)"],"output_types":["Linting reports (text, JSON, or HTML format)","Code quality metrics (complexity, duplication)","Style violation reports"],"categories":["safety-moderation","code-generation-editing"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-nikolaydubina--go-recipes__cap_16","uri":"capability://code.generation.editing.ai.assisted.code.completion.and.analysis.integration","name":"ai-assisted code completion and analysis integration","description":"Documents integration of AI tools (GitHub Copilot, LLM-based code analysis) with Go development workflows. Includes patterns for using AI for code completion, refactoring suggestions, and code analysis. Tools are indexed with examples showing how to enable AI assistance in editors and leverage AI for code review and optimization.","intents":["Use AI-powered code completion to accelerate development","Leverage LLMs for code analysis, refactoring suggestions, and optimization recommendations","Integrate AI tools into existing Go development workflows and CI/CD pipelines","Use AI for code review assistance and quality improvement"],"best_for":["Go developers using modern AI-assisted development tools","Teams exploring AI-powered code review and analysis","Projects implementing AI-assisted development workflows"],"limitations":["AI-generated code requires careful review — may contain bugs or security issues","AI tools require API keys and may have usage limits or costs","AI suggestions may not follow project-specific patterns or conventions","Privacy concerns with sending code to external AI services"],"requires":["Go 1.13+","IDE or editor with AI integration support (VS Code with Copilot, etc.)","API keys for AI services (GitHub Copilot, OpenAI, etc.)","Optional: local LLM setup for privacy-conscious deployments"],"input_types":["Go source code","Code context and prompts"],"output_types":["AI-generated code suggestions","Code analysis and optimization recommendations","Code review feedback"],"categories":["code-generation-editing","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-nikolaydubina--go-recipes__cap_2","uri":"capability://code.generation.editing.go.testing.tool.catalog.with.coverage.visualization.mutation.testing.and.test.runners","name":"go testing tool catalog with coverage visualization, mutation testing, and test runners","description":"Indexes and documents Go testing tools including coverage visualization (gocover, gocov), test runners (gotestsum, richgo), mutation testing frameworks (stryker, go-mutesting), and test data generation utilities. Each tool entry includes installation commands, usage examples, and integration patterns with standard Go testing workflows. This enables developers to enhance test visibility, automate test execution, and improve test quality beyond the standard 'go test' command.","intents":["Visualize code coverage reports in a more readable format than standard coverage output","Run tests with enhanced output formatting and parallel execution control","Perform mutation testing to verify test quality and catch weak test cases","Generate test data and fixtures for property-based or table-driven testing"],"best_for":["Go teams implementing comprehensive testing strategies and CI/CD pipelines","Developers wanting to improve test visibility and coverage metrics","Projects requiring mutation testing to validate test suite effectiveness"],"limitations":["Each tool requires separate installation and configuration — no unified testing framework","Mutation testing tools can be slow for large codebases (may require 10-100x test execution time)","Coverage visualization tools produce static reports — no real-time coverage tracking","Integration with CI/CD systems requires custom scripting for each tool"],"requires":["Go 1.13+ (for most testing tools)","Standard Go testing package knowledge","Individual tool installation (each tool has separate binary or package)"],"input_types":["Go test files (*_test.go)","Coverage profiles (*.out from 'go test -coverprofile')"],"output_types":["Coverage reports (HTML, JSON, or text format)","Test execution logs with enhanced formatting","Mutation testing results (mutation survival rates, killed mutations)"],"categories":["code-generation-editing","testing-tools"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-nikolaydubina--go-recipes__cap_3","uri":"capability://data.processing.analysis.dependency.management.and.architecture.visualization.tool.reference","name":"dependency management and architecture visualization tool reference","description":"Documents Go dependency management tools (go mod, go mod graph, go mod why), dependency visualization utilities (modgraph, depcheck), and architecture enforcement tools that help developers understand and control module dependencies. Tools are indexed with examples showing how to visualize dependency graphs, detect circular dependencies, enforce architectural boundaries, and manage version conflicts. This enables developers to maintain healthy dependency structures and prevent architectural drift.","intents":["Visualize module dependency graphs to understand codebase structure and identify circular dependencies","Enforce architectural boundaries and prevent unwanted cross-module dependencies","Analyze and manage version conflicts in large dependency trees","Detect unused dependencies and optimize module imports"],"best_for":["Go teams managing large monorepos or multi-module projects","Developers implementing architectural governance and dependency policies","Projects requiring dependency visualization for documentation or onboarding"],"limitations":["Visualization tools produce static graphs — no interactive exploration of large dependency trees","Architecture enforcement requires manual rule definition — no automatic pattern detection","Go modules system has limitations (no transitive dependency pinning) that tools cannot overcome","Circular dependency detection only works at module level, not package level"],"requires":["Go 1.11+ (for go modules support)","go.mod and go.sum files in project","Individual tool installation for visualization and analysis"],"input_types":["go.mod files (module definitions)","go.sum files (dependency checksums)","Source code (for architecture analysis)"],"output_types":["Dependency graphs (DOT format, PNG, SVG visualizations)","Architecture violation reports (text or JSON)","Module dependency lists and version information"],"categories":["data-processing-analysis","code-visualization"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-nikolaydubina--go-recipes__cap_4","uri":"capability://data.processing.analysis.code.visualization.and.call.graph.generation.for.structural.analysis","name":"code visualization and call graph generation for structural analysis","description":"Indexes tools for generating code diagrams, call graphs, and visual representations of Go code structure (go-callvis, goplantuml, goda). Tools support multiple output formats (SVG, PNG, PlantUML) and can visualize function call hierarchies, package dependencies, and architectural relationships. This enables developers to understand complex codebases visually and generate documentation diagrams without manual drawing.","intents":["Generate call graphs showing function call hierarchies and dependencies","Create architecture diagrams from code structure automatically","Visualize package relationships and module boundaries","Generate documentation diagrams for onboarding and architectural reviews"],"best_for":["Developers working with large or unfamiliar Go codebases needing visual understanding","Teams creating architectural documentation and design reviews","Projects requiring automated diagram generation for CI/CD pipelines"],"limitations":["Call graphs can become unreadable for large codebases with many functions","Visualization tools require graphviz or similar external dependencies","Dynamic function calls (via reflection or interface dispatch) cannot be visualized","Generated diagrams may require manual refinement for presentation quality"],"requires":["Go 1.13+","Graphviz or similar graph rendering tool (for SVG/PNG output)","Individual tool installation (go-callvis, goplantuml, goda)"],"input_types":["Go source code (*.go files)","Package paths or function names to visualize"],"output_types":["SVG or PNG diagrams","PlantUML or DOT format graph definitions","HTML interactive visualizations"],"categories":["data-processing-analysis","code-visualization"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-nikolaydubina--go-recipes__cap_5","uri":"capability://code.generation.editing.code.generation.and.boilerplate.automation.for.structs.interfaces.and.mocks","name":"code generation and boilerplate automation for structs, interfaces, and mocks","description":"Documents Go code generation tools that automate creation of structs, enums, interfaces, mocks, and other boilerplate code (mockgen, stringer, easyjson, go-enum). Tools are indexed with examples showing how to use code generation directives, integrate with build pipelines, and maintain generated code. This enables developers to reduce manual boilerplate and keep generated code in sync with source definitions.","intents":["Generate mock implementations of interfaces for testing without manual coding","Create string representations (String() methods) for enums and custom types","Generate JSON marshaling/unmarshaling code for performance-critical paths","Automate creation of builder patterns, constructors, and factory methods"],"best_for":["Go teams using test-driven development with extensive mocking requirements","Projects requiring high-performance JSON serialization","Developers wanting to reduce boilerplate code and improve code consistency"],"limitations":["Generated code can diverge from source if generation directives are not re-run","Code generation adds build complexity — requires integration with build tools (go generate)","Generated code is harder to debug and understand than hand-written code","Some tools have limited customization — generated code may not match project style"],"requires":["Go 1.13+","go generate support (built into Go toolchain)","Individual tool installation (mockgen, stringer, easyjson, etc.)","Build pipeline integration (Makefile, build scripts, or IDE support)"],"input_types":["Go source code with generation directives (//go:generate comments)","Interface definitions (for mock generation)","Struct definitions (for JSON marshaling, string methods)"],"output_types":["Generated Go source files (*_mock.go, *_string.go, *_easyjson.go)","Mock implementations of interfaces","String and JSON serialization methods"],"categories":["code-generation-editing","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-nikolaydubina--go-recipes__cap_6","uri":"capability://code.generation.editing.code.refactoring.and.import.management.tool.reference","name":"code refactoring and import management tool reference","description":"Indexes Go refactoring tools that automate code transformation, import organization, and structural changes (goimports, gopls, gorename, gofmt, gofumpt). Tools are documented with examples showing how to apply refactorings, organize imports, rename symbols across codebases, and format code consistently. This enables developers to safely refactor large codebases and maintain consistent code style.","intents":["Automatically organize and clean up imports in Go files","Rename symbols (functions, types, variables) across entire codebases safely","Apply consistent code formatting and style rules","Perform structural refactorings (extract functions, move code) safely"],"best_for":["Go teams maintaining large codebases requiring consistent style and structure","Developers performing large-scale refactorings with safety guarantees","Projects integrating code quality tools into CI/CD pipelines"],"limitations":["Refactoring tools rely on AST analysis — may miss edge cases with reflection or code generation","Some refactorings require manual verification even with automated tools","Tool integration requires IDE support or custom build scripts","Refactoring tools may not understand project-specific patterns or conventions"],"requires":["Go 1.13+","gopls language server (for IDE integration) or individual tool installation","IDE or editor with refactoring support (VS Code, GoLand, vim with gopls)"],"input_types":["Go source code (*.go files)","Refactoring directives (IDE commands or CLI arguments)"],"output_types":["Refactored Go source code","Organized imports","Formatted code following style rules"],"categories":["code-generation-editing","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-nikolaydubina--go-recipes__cap_7","uri":"capability://code.generation.editing.error.handling.and.panic.recovery.pattern.reference","name":"error handling and panic recovery pattern reference","description":"Documents Go error handling patterns, panic recovery techniques, and stack trace analysis tools. Includes patterns for error wrapping (errors.Is, errors.As), custom error types, panic recovery in goroutines, and tools for analyzing error logs and stack traces. This enables developers to implement robust error handling and debug production issues effectively.","intents":["Implement consistent error handling patterns across codebases","Wrap and chain errors with context while preserving error types","Recover from panics in goroutines and prevent process crashes","Analyze stack traces and error logs to diagnose production issues"],"best_for":["Go teams implementing production-grade error handling and observability","Developers building resilient services with goroutine management","Projects requiring comprehensive error tracking and debugging"],"limitations":["Error handling patterns are language features, not tools — require developer discipline","Stack trace analysis tools are often project-specific or require custom integration","Panic recovery in goroutines requires explicit implementation — no automatic mechanism","Error context can be lost if not properly wrapped at each layer"],"requires":["Go 1.13+ (for errors.Is and errors.As)","Understanding of Go error interface and error wrapping patterns","Optional: error tracking tools (Sentry, Rollbar) for production monitoring"],"input_types":["Go source code with error handling patterns","Stack traces and error logs from running applications"],"output_types":["Error handling code examples","Stack trace analysis and interpretation","Error recovery patterns and best practices"],"categories":["code-generation-editing","safety-moderation"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-nikolaydubina--go-recipes__cap_8","uri":"capability://automation.workflow.build.optimization.cross.compilation.and.binary.analysis.tooling","name":"build optimization, cross-compilation, and binary analysis tooling","description":"Indexes Go build tools and techniques including compiler optimizations (ldflags, build tags), cross-compilation configuration, binary size analysis (bloat, go-size), and build caching strategies. Tools are documented with examples showing how to optimize build times, reduce binary sizes, and analyze compiled artifacts. This enables developers to create efficient, portable binaries and optimize build pipelines.","intents":["Optimize binary size by removing debug symbols, stripping unused code, and analyzing bloat","Configure cross-compilation for multiple platforms and architectures","Analyze compiled binaries to understand size distribution and dependencies","Optimize build times through caching and parallel compilation"],"best_for":["Go teams building containerized applications or embedded systems with size constraints","Projects requiring multi-platform distribution (Linux, macOS, Windows, ARM)","Developers optimizing CI/CD build times and artifact sizes"],"limitations":["Binary size optimization may impact debuggability — stripped binaries are harder to debug","Cross-compilation requires testing on target platforms — cannot be fully validated locally","Build optimization techniques vary by Go version — may require version-specific configuration","Binary analysis tools provide insights but cannot automatically optimize code"],"requires":["Go 1.13+","Understanding of Go build system (go build, build tags, ldflags)","Optional: binary analysis tools (bloat, go-size) for size optimization"],"input_types":["Go source code","Build configuration (build tags, ldflags, environment variables)","Compiled binaries (for analysis)"],"output_types":["Optimized binaries for multiple platforms","Binary size analysis reports","Build time metrics and optimization recommendations"],"categories":["automation-workflow","code-generation-editing"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-nikolaydubina--go-recipes__cap_9","uri":"capability://data.processing.analysis.assembly.generation.and.low.level.code.visualization","name":"assembly generation and low-level code visualization","description":"Documents tools for generating and analyzing Go assembly code (objdump, go tool asm, perf). Enables developers to inspect compiled assembly, understand performance characteristics, and optimize hot paths at the instruction level. 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