{"passport":{"unfragile":{"@version":"1.0","version":"2026-05","artifact":{"id":"github-alirezarezvani--claude-skills","slug":"alirezarezvani--claude-skills","name":"claude-skills","type":"skill","url":"https://alirezarezvani.medium.com/","page_url":"https://unfragile.ai/alirezarezvani--claude-skills","categories":["app-builders"],"tags":["agent-plugins","agent-skills","agentic-ai","ai-coding-agent","anthropic-claude","claude-ai","claude-code","claude-code-plugins","claude-code-skills","claude-skills","codex-skills","coding-agent-plugins","cursor-skills","developer-tools","gemini-cli-skills","openai-codex","openclaw","openclaw-plugins","openclaw-skills","prompt-engineering"],"pricing":{"model":"open_source","free":true,"starting_price":null},"status":"active","verified":false},"capabilities":[{"id":"github-alirezarezvani--claude-skills__cap_0","uri":"capability://tool.use.integration.domain.organized.skill.package.installation.across.8.ai.platforms","name":"domain-organized skill package installation across 8+ ai platforms","description":"Installs modular, self-contained skill packages (48 total across 6 domains: Marketing, Product, Engineering, C-Level, Project Management, Regulatory/Quality) into Claude Code, Cursor, VS Code, Copilot, Goose, Amp, Codex, Letta, and OpenCode via standardized marketplace.json configuration and platform-specific plugin.json manifests. Each skill package bundles Python CLI tools, reference frameworks, templates, and documentation following a 4-component structure (SKILL.md, scripts/, references/, assets/), enabling agents to discover and load domain expertise without manual configuration.","intents":["I want to add pre-built marketing, engineering, or compliance skills to my Claude Code agent without writing custom prompts","I need to deploy the same skill set across multiple AI coding platforms (Cursor, VS Code, Copilot) with consistent behavior","I want to install only the skills relevant to my team (e.g., just engineering skills) without bloating my agent with unrelated domains"],"best_for":["teams using multiple AI coding agents (Claude Code, Cursor, Copilot) who need skill parity across platforms","enterprises deploying domain-specific agents (marketing, product, engineering, compliance) with standardized tooling","developers building custom agents (Letta, OpenCode) who want to reuse pre-built skill packages"],"limitations":["Marketplace discovery requires platform-specific plugin.json registration — not all platforms support dynamic skill loading equally","Skills are Python-first (68+ CLI tools using standard library only) — agents without Python runtime cannot execute tool scripts directly","Installation is package-level, not granular — you install entire skill domains, not individual tools within a skill","No built-in version management or dependency resolution — skill updates require manual re-installation"],"requires":["Target AI platform with plugin/skill support (Claude Code, Cursor, VS Code, Copilot, Goose, Amp, Codex, Letta, or OpenCode)","Python 3.7+ runtime for executing CLI tools bundled in skill packages","Git or direct file access to clone/download skill packages from repository"],"input_types":["marketplace.json configuration (JSON)","plugin.json manifests (JSON)","SKILL.md documentation (Markdown)"],"output_types":["installed skill packages in agent context","executable Python CLI tools registered with agent","reference frameworks and templates available to agent prompts"],"categories":["tool-use-integration","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-alirezarezvani--claude-skills__cap_1","uri":"capability://tool.use.integration.python.cli.tool.execution.with.standard.library.only.constraint","name":"python cli tool execution with standard library only constraint","description":"Executes 68+ production-ready Python CLI tools embedded in skill packages that use only Python standard library (no external dependencies like requests, pandas, or numpy) to ensure portability across agent runtimes and reduce installation friction. Tools are invoked by agents as executable scripts (tool1.py, tool2.py) with stdin/stdout interfaces, enabling agents to chain tool outputs without requiring LLM calls between steps. Each tool is documented in scripts/README.md with usage examples and expected input/output formats.","intents":["I want my agent to execute utility functions (data transformation, file processing, API calls) without managing Python dependencies","I need tools that work in any Python environment without pip install or virtual env setup","I want to chain multiple CLI tools together in agent workflows without LLM latency between steps"],"best_for":["agents running in sandboxed or restricted Python environments (e.g., cloud functions, containers with minimal dependencies)","teams avoiding dependency hell and version conflicts across multiple agent deployments","developers building deterministic, reproducible agent workflows where tool behavior is predictable"],"limitations":["Standard library only constraint limits tool capabilities — no HTTP client libraries (requests), data science (pandas, numpy), or async frameworks","CLI interface (stdin/stdout) adds serialization overhead vs direct function calls — JSON parsing/encoding per tool invocation","No built-in error handling or retry logic — agents must implement their own error recovery for failed tool executions","Tools cannot access external APIs directly (no requests library) — agents must provide API responses as input or use separate API-calling tools"],"requires":["Python 3.7+ with standard library modules (json, csv, re, subprocess, pathlib, etc.)","Agent runtime capable of spawning subprocess or executing Python scripts","Input data formatted as JSON or plain text (tools parse stdin)"],"input_types":["JSON (stdin)","plain text (stdin)","command-line arguments"],"output_types":["JSON (stdout)","plain text (stdout)","exit codes (0 for success, non-zero for errors)"],"categories":["tool-use-integration","code-generation-editing"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-alirezarezvani--claude-skills__cap_10","uri":"capability://planning.reasoning.c.level.advisory.skills.with.strategic.planning.and.executive.decision.support","name":"c-level advisory skills with strategic planning and executive decision support","description":"Provides 2 production-ready C-level advisory skills (c-level-advisor/ domain) designed for executive decision-making and strategic planning: CEO advisor skill (business strategy, market analysis, competitive positioning, board reporting) and CTO advisor skill (technology strategy, architecture decisions, engineering team management, technical roadmap). Skills bundle Python CLI tools for business metrics calculation and analysis, reference frameworks for strategic planning methodologies (OKRs, balanced scorecard, technology strategy frameworks), and templates (board decks, strategic plans, technology roadmaps). cs-ceo-advisor and cs-cto-advisor agents are pre-configured to use C-level skills combined with project management and regulatory skills. C-level advisory is an emerging domain (2 skills) with planned expansion.","intents":["I want an agent that can help me develop business strategy and analyze competitive positioning","I need an agent that advises on technology strategy and architecture decisions for my engineering organization","I want to prepare board reports and strategic plans with agent assistance"],"best_for":["CEOs and CTOs using Claude Code or Cursor who want strategic planning assistance","executive teams building multi-agent systems (CEO advisor + CTO advisor + product manager) for organizational decision-making","consulting firms building executive advisory agents for clients"],"limitations":["C-level skills are emerging (2 skills) — coverage is limited compared to engineering (18 skills) or marketing (5 skills)","Strategic advice is framework-based — agents provide planning templates and analysis structures, not proprietary business insights","No integration with business intelligence platforms (Tableau, Looker) — agents cannot access real business metrics","Executive decision support is advisory only — agents cannot execute decisions or access company systems"],"requires":["Business context (company strategy, market position, competitive landscape)","Python 3.7+ for executing business metrics tools","Claude Code, Cursor, or other platform with C-level skill support"],"input_types":["business metrics (revenue, growth, market share)","competitive analysis (text, JSON)","strategic goals (text, OKRs)","technology landscape (text, architecture diagrams)"],"output_types":["strategic plans (markdown, JSON)","board decks (markdown, templates)","competitive analysis (text, JSON)","technology roadmaps (markdown, diagrams)"],"categories":["planning-reasoning","text-generation-language"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-alirezarezvani--claude-skills__cap_11","uri":"capability://planning.reasoning.project.management.and.compliance.skills.with.regulatory.and.quality.frameworks","name":"project management and compliance skills with regulatory and quality frameworks","description":"Provides 6 project management skills (project-management/ domain) and 12 regulatory/quality management skills (ra-qm-team/ domain) covering project planning, team coordination, regulatory compliance, quality assurance, and risk management. PM skills include: project planning skill (timeline creation, resource allocation, risk planning), agile/scrum skill (sprint planning, backlog management, velocity tracking), stakeholder management skill (communication plans, status reporting), and 3 additional PM skills. Regulatory/Quality skills include: compliance skill (regulatory requirement tracking, audit preparation), quality assurance skill (QA strategy, test planning, defect management), risk management skill (risk identification, mitigation planning), and 9 additional regulatory/quality skills. Each skill bundles Python CLI tools for project metrics and compliance tracking, reference frameworks (PMBOK, ISO standards, regulatory requirements), and templates (project plans, compliance checklists, audit reports).","intents":["I want an agent that helps me plan projects, allocate resources, and track progress against timelines","I need an agent that ensures our product meets regulatory requirements and quality standards","I want to prepare for audits and compliance reviews with agent assistance"],"best_for":["project managers using Claude Code or Cursor who want AI-assisted project planning and tracking","regulated industries (healthcare, finance, pharma) who need compliance and quality management agents","enterprises building multi-domain agents that include project management and compliance oversight"],"limitations":["Project management tools are planning-based — agents generate plans and templates, not real-time project tracking","No integration with project management platforms (Jira, Asana, Monday.com) — agents cannot access actual project data","Compliance tools are checklist-based — agents provide compliance frameworks, not automated compliance monitoring","Quality assurance tools are strategy-based — agents plan QA approaches, not execute tests or monitor quality metrics"],"requires":["Project context (scope, timeline, resources, constraints)","Regulatory requirements (industry standards, compliance frameworks)","Python 3.7+ for executing project and compliance tools","Claude Code, Cursor, or other platform with PM/compliance skill support"],"input_types":["project scope and requirements (text, JSON)","regulatory requirements (text, markdown)","team composition and skills (JSON, text)","compliance frameworks (text, markdown)"],"output_types":["project plans (markdown, JSON, Gantt charts)","compliance checklists (markdown, JSON)","audit reports (markdown, templates)","quality assurance plans (markdown, JSON)"],"categories":["planning-reasoning","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-alirezarezvani--claude-skills__cap_12","uri":"capability://tool.use.integration.agent.native.slash.commands.for.quick.skill.access","name":"agent-native slash commands for quick skill access","description":"Provides optional slash commands (/.claude/ directory) that enable quick access to skills and agents within Claude Code and compatible platforms. Slash commands are shortcuts that trigger skill execution or agent instantiation without explicit tool calling. For example, /marketing-content might trigger the content creator skill, /code-review might trigger the code review skill, /ceo-advisor might instantiate the CEO advisor agent. Slash commands are platform-specific (Claude Code, Cursor, VS Code) and optional — agents can also access skills via explicit tool calling. Slash commands improve user experience by reducing friction for common operations.","intents":["I want to quickly access a skill without typing out full tool names or function signatures","I want to instantiate a pre-configured agent (CEO advisor, product manager) with a single slash command","I want to discover available skills and agents by typing / and seeing suggestions"],"best_for":["users of Claude Code, Cursor, and VS Code who want quick skill access","teams using slash commands for common operations (code review, content creation, compliance checking)","developers building agent-native interfaces that prioritize discoverability"],"limitations":["Slash commands are platform-specific — not all platforms (Copilot, Letta, OpenCode) support them equally","Slash command discovery is limited to platform UI — no centralized registry of available commands","Slash commands cannot pass complex arguments — limited to simple parameters or predefined options","Slash commands are optional — agents can still access skills via explicit tool calling, making them redundant"],"requires":["Platform support for slash commands (Claude Code, Cursor, VS Code)","Slash command definitions in .claude/ directory","Agent runtime that interprets slash commands"],"input_types":["slash command text (e.g., /marketing-content)","optional parameters (text, flags)"],"output_types":["skill execution results","agent instantiation","command suggestions (autocomplete)"],"categories":["tool-use-integration","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-alirezarezvani--claude-skills__cap_2","uri":"capability://planning.reasoning.5.layer.architecture.with.agent.skill.separation.and.relative.path.resolution","name":"5-layer architecture with agent-skill separation and relative path resolution","description":"Implements a 5-layer architecture (Distribution, Agent Orchestration, Skill Implementation, Governance, Automation) that decouples agents from skills using relative path resolution (../../) to enable agents to discover and load skills dynamically without hardcoding paths. Agents (cs-content-creator, cs-demand-gen-specialist, cs-product-manager, cs-ceo-advisor, cs-cto-advisor) live in agents/ directory and reference skills via relative paths, allowing the same agent definition to work across different installation contexts (local, cloud, container). Governance layer enforces standards (quality gates, testing, CI/CD) across all skills.","intents":["I want to build agents that can dynamically load skills from any installation path without hardcoding absolute paths","I need to enforce consistent quality, testing, and governance across 48+ skills without manual oversight","I want to reuse the same agent definition across different deployment environments (local dev, staging, production)"],"best_for":["teams managing 5+ production agents with shared skill dependencies and governance requirements","organizations deploying agents across multiple environments (local, cloud, container) with path portability needs","developers building extensible agent frameworks where skills are discovered at runtime"],"limitations":["Relative path resolution (../../) is fragile if directory structure changes — no validation that paths exist at runtime","5-layer architecture adds abstraction overhead — developers must understand all layers to debug issues","Governance enforcement (quality gates, testing) requires CI/CD integration — manual deployments bypass standards","Agent-skill separation assumes skills are stateless — no built-in support for shared state or inter-skill communication"],"requires":["Directory structure matching claude-skills layout (agents/, marketing-skill/, engineering-team/, etc.)","CI/CD system (GitHub Actions, GitLab CI) for automation layer enforcement","Python 3.7+ for skill execution and governance tooling"],"input_types":["agent definitions (CLAUDE.md, plugin.json)","skill packages (SKILL.md, scripts/, references/, assets/)","governance standards (markdown, JSON)"],"output_types":["resolved skill paths at runtime","quality gate reports (test results, linting, coverage)","agent-skill binding configuration"],"categories":["planning-reasoning","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-alirezarezvani--claude-skills__cap_3","uri":"capability://planning.reasoning.domain.specific.agent.orchestration.with.role.based.skill.binding","name":"domain-specific agent orchestration with role-based skill binding","description":"Defines 5 production agents (cs-content-creator, cs-demand-gen-specialist, cs-product-manager, cs-ceo-advisor, cs-cto-advisor) that bind to domain-specific skill subsets via agent definitions in agents/ directory. Each agent is configured with CLAUDE.md and plugin.json manifests that specify which skills to load (e.g., cs-ceo-advisor loads c-level-advisor skills + project-management skills). Agents are role-based (content creator, demand gen specialist, product manager, CEO, CTO) and can be instantiated independently or composed into multi-agent systems. Agent definitions include prompt templates, tool bindings, and execution constraints.","intents":["I want to create a marketing agent that only has access to marketing and demand-gen skills, not engineering or compliance tools","I need to define a CEO advisor agent that combines C-level advisory skills with project management and regulatory knowledge","I want to instantiate multiple role-based agents (content creator, product manager, CTO) that collaborate on a project"],"best_for":["enterprises with role-based teams (marketing, product, engineering, C-level) who want dedicated agents per role","organizations building multi-agent systems where agents need different skill sets and permissions","teams using Claude Code, Cursor, or other platforms that support agent definitions"],"limitations":["Agent definitions are static — skill bindings are fixed at agent creation time, not dynamic at runtime","No built-in inter-agent communication or state sharing — agents cannot directly call other agents or share context","Role-based binding assumes non-overlapping skill domains — agents with overlapping skills may have conflicting tool implementations","Agent instantiation is platform-specific — agent definitions must be adapted for each platform (Claude Code vs Cursor vs Copilot)"],"requires":["Agent definition files (agents/CLAUDE.md, agents/{agent-name}/plugin.json)","Skill packages for each role (marketing-skill/, engineering-team/, c-level-advisor/, etc.)","Target platform with agent support (Claude Code, Cursor, VS Code, Copilot, Letta, OpenCode)"],"input_types":["agent definitions (CLAUDE.md, plugin.json)","skill package references (relative paths)","role specifications (text, JSON)"],"output_types":["instantiated agent with bound skills","agent prompt templates","tool registry for agent"],"categories":["planning-reasoning","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-alirezarezvani--claude-skills__cap_4","uri":"capability://memory.knowledge.standardized.skill.package.documentation.and.knowledge.base.generation","name":"standardized skill package documentation and knowledge base generation","description":"Generates comprehensive skill documentation via SKILL.md master documents (500-1500 lines per skill) that bundle domain expertise, executable Python tools, reference frameworks, and templates into self-contained packages. Each SKILL.md includes skill overview, tool documentation (scripts/README.md), reference frameworks (references/ directory with markdown files), and user-facing templates (assets/ directory). Documentation is human-readable (markdown) and machine-parseable (structured sections with consistent formatting), enabling agents to extract tool signatures, usage examples, and domain knowledge. Reference frameworks provide expert knowledge bases (e.g., marketing frameworks, engineering best practices) that agents can cite or extend.","intents":["I want to understand what tools and frameworks are available in a skill without reading source code","I need my agent to extract tool signatures and usage examples from skill documentation to generate correct function calls","I want to provide domain expertise (marketing frameworks, engineering best practices) to agents in a structured, reusable format"],"best_for":["teams documenting complex skills (48+ skills across 6 domains) with consistent structure and formatting","developers building agents that parse skill documentation to discover tools and frameworks dynamically","organizations creating knowledge bases that combine executable tools with expert reference material"],"limitations":["SKILL.md documentation is manually maintained — no automatic generation from code, risking drift between docs and implementation","Markdown format is human-readable but not machine-structured (no JSON schema, YAML, or formal grammar) — parsing requires regex or heuristics","Reference frameworks are static documents — no versioning or update mechanism when frameworks evolve","Documentation size (500-1500 lines per skill) may exceed agent context windows, requiring summarization or chunking"],"requires":["Markdown editor or IDE for writing SKILL.md files","Consistent documentation template (structure, sections, formatting)","Python tools in scripts/ directory with clear input/output signatures","Reference frameworks in references/ directory (markdown files)"],"input_types":["skill domain knowledge (text, frameworks, best practices)","Python tool source code (scripts/)","templates and examples (assets/)"],"output_types":["SKILL.md documentation (markdown, 500-1500 lines)","scripts/README.md (tool documentation)","references/ (framework documents)","assets/ (templates)"],"categories":["memory-knowledge","text-generation-language"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-alirezarezvani--claude-skills__cap_5","uri":"capability://automation.workflow.quality.gates.and.governance.enforcement.via.ci.cd.automation","name":"quality gates and governance enforcement via ci/cd automation","description":"Enforces quality standards across 48 skills via automated CI/CD pipelines (GitHub Actions, GitLab CI) that validate skill packages against governance rules before deployment. Quality gates include: linting (code style, markdown formatting), testing (unit tests for Python tools), documentation validation (SKILL.md completeness, reference framework presence), and standards compliance (adherence to skill package structure). Governance layer (5th layer in architecture) defines standards in standards/ directory (5 governance standards) and automation layer (5th layer) implements CI/CD checks. Failed quality gates block skill deployment, ensuring only production-ready skills are distributed.","intents":["I want to ensure all 48 skills meet minimum quality standards (documentation, testing, code style) before they're installed by users","I need to prevent skill deployments that violate governance rules (missing SKILL.md, incomplete tool documentation, test failures)","I want to automate quality validation so developers don't manually review every skill update"],"best_for":["teams managing 10+ skills with distributed development and need centralized quality control","organizations with compliance requirements (regulatory, quality management) that demand automated validation","developers using GitHub or GitLab who want to enforce standards via CI/CD without manual gates"],"limitations":["CI/CD automation requires GitHub Actions or GitLab CI setup — not portable to other version control systems (Gitea, Bitbucket)","Quality gates are rule-based and static — cannot adapt to context-specific requirements (e.g., different standards for different skill domains)","Failed quality gates block deployment but don't provide remediation guidance — developers must manually fix issues","No built-in rollback mechanism — if a skill passes quality gates but fails in production, manual intervention is required"],"requires":["GitHub or GitLab repository with CI/CD support","GitHub Actions or GitLab CI configuration files (.github/workflows/, .gitlab-ci.yml)","Python 3.7+ for linting and testing tools","Standards definitions in standards/ directory (markdown, JSON)"],"input_types":["skill package files (SKILL.md, scripts/, references/, assets/)","standards definitions (markdown, JSON)","CI/CD configuration (YAML)"],"output_types":["quality gate reports (pass/fail, violations)","test results (coverage, failures)","linting reports (style violations, markdown errors)","deployment approval/rejection"],"categories":["automation-workflow","safety-moderation"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-alirezarezvani--claude-skills__cap_6","uri":"capability://memory.knowledge.multi.domain.skill.library.with.48.production.ready.packages","name":"multi-domain skill library with 48 production-ready packages","description":"Provides a curated library of 48 production-ready skill packages organized across 6 domains: Marketing (5 skills), Product (5 skills), Engineering (18 skills), C-Level Advisory (2 skills), Project Management (6 skills), and Regulatory/Quality (12 skills). Each skill is a self-contained package with Python CLI tools, reference frameworks, and templates, designed to be installed independently or composed into agents. Skills are versioned, documented, and tested before distribution. The library covers functional areas from content creation and demand generation (marketing) to code review and architecture design (engineering) to compliance and quality management (regulatory).","intents":["I want to find pre-built skills for my team's domain (marketing, engineering, product, compliance) without building from scratch","I need to install only the skills relevant to my use case (e.g., just engineering skills for a dev team)","I want to see what capabilities are available across all domains to understand what agents I can build"],"best_for":["teams in marketing, product, engineering, or compliance who want domain-specific agent capabilities","enterprises building multi-domain agents (e.g., CEO advisor combining C-level, product, and compliance skills)","developers exploring what pre-built skills exist before deciding to build custom skills"],"limitations":["Skill coverage is curated, not exhaustive — some domains may have gaps (e.g., only 2 C-level advisory skills vs 18 engineering skills)","Skills are domain-specific — cross-domain skills (e.g., a skill combining marketing + engineering) are rare","Skill quality varies by domain — engineering skills may be more mature than emerging domains like C-level advisory","Skills are Python-based — teams using other languages (JavaScript, Go, Rust) cannot directly use skill tools without wrapping"],"requires":["Access to claude-skills repository (GitHub clone or marketplace installation)","Python 3.7+ for executing skill tools","Target AI platform (Claude Code, Cursor, VS Code, Copilot, etc.)"],"input_types":["skill package metadata (marketplace.json, plugin.json)","skill documentation (SKILL.md, README.md)"],"output_types":["installed skill packages","executable Python CLI tools","reference frameworks and templates"],"categories":["memory-knowledge","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-alirezarezvani--claude-skills__cap_7","uri":"capability://code.generation.editing.template.based.skill.refactoring.and.standardization","name":"template-based skill refactoring and standardization","description":"Provides reusable templates in templates/ directory that standardize skill package structure, documentation format, and tool implementation patterns across all 48 skills. Templates include: skill package structure template (SKILL.md outline, scripts/ layout, references/ organization), Python tool template (CLI argument parsing, stdin/stdout handling, error handling), documentation template (skill overview, tool documentation, framework sections), and agent definition template (CLAUDE.md, plugin.json). Developers use templates to create new skills or refactor existing skills to match standards, ensuring consistency and reducing development time. Templates are versioned and updated as standards evolve.","intents":["I want to create a new skill that follows the same structure and conventions as existing skills","I need to refactor an existing skill to match current standards without rewriting from scratch","I want to ensure my new skill documentation, tools, and templates follow the same patterns as the library"],"best_for":["developers contributing new skills to the library who need guidance on structure and conventions","teams maintaining 10+ skills who want to enforce consistent patterns without manual review","organizations onboarding new developers who need to understand skill development workflow"],"limitations":["Templates are static documents — no automated scaffolding or code generation to create skill packages","Template updates require manual propagation to existing skills — no automatic refactoring of old skills to match new templates","Templates assume Python-only tools — teams using other languages must adapt templates manually","Template compliance is not enforced — developers can ignore templates and create non-standard skills"],"requires":["Access to templates/ directory in repository","Understanding of skill package structure (SKILL.md, scripts/, references/, assets/)","Python 3.7+ for implementing tool templates"],"input_types":["template files (markdown, Python, JSON)","skill domain and purpose (text)"],"output_types":["new skill package structure","SKILL.md documentation","Python CLI tools","reference frameworks and templates"],"categories":["code-generation-editing","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-alirezarezvani--claude-skills__cap_8","uri":"capability://text.generation.language.marketing.domain.skills.with.content.creation.and.demand.generation","name":"marketing domain skills with content creation and demand generation","description":"Provides 5 production-ready marketing skills (marketing-skill/ domain) that enable agents to perform content creation, demand generation, campaign planning, and marketing analytics. Skills include: content creator skill (blog post generation, social media content, email campaigns), demand generation specialist skill (lead generation strategies, funnel optimization, conversion analysis), marketing analytics skill (campaign performance tracking, ROI calculation), brand strategy skill (brand positioning, messaging frameworks), and marketing automation skill (campaign orchestration, lead nurturing). Each skill bundles Python CLI tools (e.g., content templates, analytics calculators), reference frameworks (marketing methodologies, best practices), and templates (campaign plans, content calendars). cs-content-creator and cs-demand-gen-specialist agents are pre-configured to use marketing skills.","intents":["I want my agent to generate marketing content (blog posts, social media, emails) based on brand guidelines and target audience","I need an agent that can analyze campaign performance and suggest optimizations for lead generation and conversion","I want to create marketing campaigns with proper planning, timeline, and resource allocation using agent assistance"],"best_for":["marketing teams using Claude Code or Cursor who want AI-assisted content creation and campaign planning","startups with small marketing teams who need agent-powered demand generation and analytics","enterprises building marketing automation agents that need domain expertise in content and campaigns"],"limitations":["Marketing skills are template-based — agents generate content outlines and plans, not final production-ready content","No direct integration with marketing platforms (HubSpot, Marketo, Salesforce) — agents cannot pull real campaign data or push results","Analytics tools are calculation-based (ROI, conversion rates) — agents cannot access actual marketing data without manual input","Content generation relies on agent LLM capabilities — skill tools provide frameworks and templates, not content itself"],"requires":["Marketing domain knowledge (target audience, brand guidelines, campaign goals)","Python 3.7+ for executing marketing analytics tools","Claude Code, Cursor, or other platform with marketing skill support"],"input_types":["brand guidelines (text, markdown)","target audience profiles (JSON, text)","campaign goals and metrics (text, numbers)","historical campaign data (CSV, JSON)"],"output_types":["content outlines and templates (markdown)","campaign plans (markdown, JSON)","analytics reports (text, JSON)","optimization recommendations (text)"],"categories":["text-generation-language","data-processing-analysis"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-alirezarezvani--claude-skills__cap_9","uri":"capability://code.generation.editing.engineering.domain.skills.with.code.review.architecture.and.testing","name":"engineering domain skills with code review, architecture, and testing","description":"Provides 18 production-ready engineering skills (engineering-team/ domain) covering code review, architecture design, testing strategies, performance optimization, security hardening, and DevOps practices. Skills include: code review skill (static analysis, style checking, best practices), architecture design skill (system design patterns, scalability analysis), testing skill (unit test generation, test strategy planning), performance optimization skill (profiling, bottleneck identification), security skill (vulnerability scanning, hardening recommendations), DevOps skill (CI/CD pipeline design, infrastructure as code), and 11 additional specialized skills. Each skill bundles Python CLI tools (linters, test generators, performance calculators), reference frameworks (design patterns, testing methodologies, security standards), and templates (code review checklists, architecture diagrams, test plans). Engineering skills are the most mature domain (18 skills) reflecting high demand.","intents":["I want my agent to review code changes and suggest improvements based on best practices and style guides","I need an agent that can analyze system architecture and recommend scalability improvements","I want to generate test plans and unit tests for new code using agent assistance"],"best_for":["engineering teams using Claude Code or Cursor who want AI-assisted code review and architecture analysis","startups with small engineering teams who need agent-powered testing and performance optimization","enterprises building engineering automation agents (code review bots, architecture advisors, test generators)"],"limitations":["Code review tools are analysis-based (linting, style checking) — agents cannot execute code or run tests directly","Architecture analysis is pattern-based — agents cannot access actual system metrics or performance data","Test generation is template-based — agents generate test outlines, not production-ready test code","Security analysis is rule-based — agents cannot perform dynamic security testing or vulnerability scanning"],"requires":["Source code access (local files, Git repository)","Python 3.7+ for executing engineering tools (linters, test generators)","Claude Code, Cursor, or other platform with engineering skill support"],"input_types":["source code (Python, JavaScript, Java, Go, etc.)","architecture diagrams (text, markdown)","test requirements (text, JSON)","performance metrics (numbers, JSON)"],"output_types":["code review reports (markdown, JSON)","architecture recommendations (markdown, diagrams)","test plans and templates (markdown, Python)","performance analysis (text, JSON)"],"categories":["code-generation-editing","planning-reasoning"],"confidence":0.5,"matches":0,"success_rate":0}],"trust":{"score":39,"verified":false,"data_access_risk":"high","permissions":["Target AI platform with plugin/skill support (Claude Code, Cursor, VS Code, 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insights","builder identity is not verified yet","no observed match outcomes 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