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Generates comprehensive documentation explaining how a codebase works, including architecture, key components, data flow, and development guidelines. Use when user wants to understand unfamiliar code, create onboarding docs, document architecture, or explain how the system works.
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Analyze a codebase for high-leverage architectural improvements and explain evidence, tradeoffs, and next steps. Use explicitly for architecture audits or deep-module refactoring opportunities.
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Audits cross-cutting codebase health, security and maintainability; not a single-change review or specialist audit.
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Explores codebase structure, affected files, blast radius, related tests, and local conventions for a focused topic. Use when review or planning needs structural lookup without bloating main context.
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Deeply analyze an existing codebase feature by tracing execution paths, mapping architecture layers, understanding patterns and abstractions, and documenting dependencies. Use this skill when you need to understand how a feature works before modifying or extending it, when dispatched as a sub-task during feature-dev exploration, or when the user asks "how does X work in this codebase".
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Codebase'i derinlemesine anla. Onboarding, architecture discovery, dependency mapping.
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Knowledge graph integration for token-efficient codebase understanding. Uses codebase-memory MCP for AST indexing, dependency graphs, and smart context selection. 6-71x token savings vs raw file reading.
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Meta-skill for internal codebase exploration at varying depths (quick/deep/architecture)
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Codebase'i knowledge graph olarak analiz et. Dependency, call graph, hotspot analizi.
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Scan a codebase for deepening opportunities, present them as a visual HTML report, then grill through whichever one you pick.
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Build cross-platform .NET applications with Uno Platform targeting WebAssembly, iOS, Android, macOS, Linux, and Windows from a single XAML/C# codebase. USE FOR: building cross-platform apps from a single C# and XAML codebase; targeting WebAssembly, iOS, Android, macOS, Linux, and Windows simultaneously; migrating WPF or UWP. 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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Analyze codebase with tokei (fast line counts by language) and difft (semantic AST-aware diffs). Get quick project overview without manual counting. Triggers on: how big is codebase, count lines of code, what languages, show semantic diff, compare files, code statistics.
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Statistical rule discovery from Go codebase patterns.
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A 5-minute gate the coder runs at project kickoff (and again whenever the repo shape changes). Classifies the workspace into Greenfield / Brownfield-large / Mid-size-familiar / Library-SDK, then maps the state to an agent strategy (autonomy, context primitive, tool choice). Use BEFORE picking Cursor vs Claude Code vs Aider, BEFORE turning on repo-map, BEFORE writing the first prompt. Skip only if the same repo was gated within the last day and nothing changed. Search keywords: greenfield vs brownfield, new project vs existing codebase, project setup strategy, legacy codebase agent, where to start a coding agent.
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Use when auditing a codebase for semantic duplication - functions that do the same thing but have different names or implementations. Especially useful for LLM-generated codebases where new functions are often created rather than reusing existing ones.
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Scans an existing codebase and generates project-specific skills that capture inferred conventions such as naming, file organization, framework usage, data access, error handling, and testing style. Writes into the project's chosen skill directory (e.g., `.claude/skills/`, `.agents/skills/`, or a custom path). Use when the user asks to "extract skills from the codebase", "create project skills", "infer project conventions as skills", "codify patterns as skills", or "mine the repo for best practices".
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Analyze a codebase and produce a structured threat model at .turbo/threat-model.md covering assets, trust boundaries, attack surfaces with existing mitigations, attacker stories, and calibrated severity. Use when the user asks to "create a threat model", "threat model", "threat model this codebase", "security analysis", "analyze the attack surface", "what are the threats", or "identify security risks".
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Survey any codebase as a senior advisor and produce prioritized, self-contained implementation plans for OTHER models/agents to execute. Strictly read-only on source code — never implements, fixes, or refactors anything itself. Use when asked to audit a codebase, find improvement opportunities (bugs, security, performance, test coverage, tech debt, migrations, DX), suggest features or where to take the project next (roadmap, product direction), or generate handoff plans for another agent to implement.
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Scan a codebase for deepening opportunities, present them as a visual HTML report, then grill through whichever one you pick.
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Uses 1M context window to ingest an entire codebase and output a file-by-file migration plan. Supports JS to TS, React class to hooks, framework migrations, and more. Generates migration-plan.md with file inventory, dependency graph, migration order, file-by-file changes, estimated effort, and risk assessment.
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Provides autonomous project pattern learning by analyzing the codebase to discover development conventions, architectural patterns, and coding standards, then generates project rule files in .claude/rules/. Use when user asks to "learn from project", "extract project rules", "analyze codebase conventions", "discover project patterns", or wants to auto-generate Claude Code rules for the current project.
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Runs a three-tier codebase audit (git history, targeted scans, full review) with gating. Use when auditing a codebase before release or after incidents.
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Detects codebase bloat via dead code, duplication, complexity, and doc bloat scans. Use when codebase feels large or before a release.
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Presents adaptive codebase challenge questions with multiple-choice and trace exercises. Use when testing contributor knowledge of the codebase.
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