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Investigate slow SQL, write complex joins and summaries, and design database structures. Uses execution plans, which show how queries run, to guide index choices and query rewrites, with before-and-after performance measurements.
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Generate a comprehensive marketing website for a web app — multi-page with real screenshots, animated GIF walkthroughs, feature deep-dives, and workflow demonstrations. Browses the running app, captures screens and sequences, and produces a deployable site that actually teaches people what the product does. Especially useful for complex or agentic apps that are hard to explain. Triggers: 'showcase site', 'product page', 'show off the app', 'marketing site', 'demo site', 'product showcase', 'explain the app', 'how do I market this'.
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Turn pull request changes, commits, and test evidence into a self-contained HTML guide. Explain the problem, system context, before-and-after behavior, and key code changes so reviewers know where to focus.
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Reconstructed reference notes on US FAA approval guidance for airborne software and airborne electronic hardware, built from four public-domain sources (FAA Order 8110.49A, AC 20-115D, AC 20-152A, AC 00-69; documents dated 2017-07-21 to 2022-10-07, pinned 2026-10-12). Use for how FAA certification staff plan and conduct software reviews (certification liaison, desk versus on-site review, review planning agreements), how the level of FAA involvement (LOI) is picked and scored with the Appendix A worksheets, how software conformity inspection works (software part and installation conformity, ASE and ASI tasks, Form 8120-10), what AC 20-115D recognizes and how DO-178B processes and tool qualification transition to DO-178C/DO-330 (supplements, FLS, UMS, legacy software changes), and what AC 20-152A adds for airborne electronic hardware (simple versus complex custom devices, robustness and HDL code coverage, tool assessment, previously developed hardware, COTS IP, COTS devices, circuit board assemblies), and what AC 00-69 adds as best practices for change impact analysis, data and control coupling, and design-level error handling (best practices, not guidance and not a means of compliance). SCOPE LIMITS: FAA guidance only, and guidance is not regulation (ACs are acceptable means, not the only means); no RTCA DO-178C or DO-254, EUROCAE ED-12C or ED-80, supplement, or SAE ARP text, which are copyrighted and named only (see the avionics-signpost pack); no AC 00-72 (named, not packed); no DO-178C software-level objective tables; no EASA AMC 20-115D or AMC 20-152A content (use easa-rules); reflects the pinned source dates, not later FAA actions; synthesized reference notes, not legal advice and not a substitute for the source documents. LICENCE: Public Domain (US Government work, 17 U.S.C. 105).
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Quickly understand an unfamiliar codebase or project by mapping its architecture, identifying key components and data flows, and surfacing complexity hotspots. Load when the user asks to understand a repo, explain how something works, map the architecture, onboard to a codebase, or explore how components connect. Also triggers on "walk me through this codebase", "how does this project work", "explain the architecture", "what does this repo do", "show me the structure", "onboard me", or any request to build a mental model of a codebase before making changes.
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Review code for security, performance, quality, and maintainability. Get findings organized by severity, with file locations, explanations of impact, and example fixes, plus code metrics and complexity comparisons for refactoring reviews.
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Help junior developers and AI newcomers understand code through guided questions and progressive hints. Support debugging, concept learning, and critical review of AI-generated code so learners can explain their reasoning and work toward solutions themselves.
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World-class explainer video expertise combining the visual storytelling of Kurzgesagt, the simplification genius of Common Craft, and the conversion science of high-performing SaaS landing pages. Explainer videos transform complex ideas into clear, compelling stories. Great explainers don't just inform—they illuminate. They take abstract concepts and make them feel obvious. The best explainer videos understand that simplicity is the ultimate sophistication, that showing beats telling, and that the goal isn't to impress with complexity—it's to make the viewer feel smart. Use when "explainer, explainer video, how it works, product demo, onboarding video, training video, educational video, whiteboard, animated explainer, explain this, simplify, concept video, SaaS video, explainer, video, animation, educational, product, demo, onboarding, SaaS" mentioned.
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Teaches you how to break large tasks into stages, save your place between sessions, and recover smoothly when a task gets interrupted. Use when planning a multi-day project, for breaking down large work into manageable stages, during recovery from an interrupted session, when managing complex ongoing work, or when the user says "cowork stopped in the middle", "token limit", "task too large", "context management", "how to do big tasks", "session got cut off", "cowork forgot what we were doing", "how do I work on something over multiple days", "it lost track of the project", or "my task is too big for one session".
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Coordinate structured thinking and multi-agent parallel execution for complex tasks. Use when tackling multi-step projects, planning parallel work, breaking down complex problems, coordinating specialist tasks, facing architectural decisions, or when user mentions "workflow", "orchestration", "multi-step", "coordinate", "parallel execution", "structured thinking", "break this down", "plan this out", "how should I approach", or needs help planning complex implementations.
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Analyzes ticket complexity and maps dependencies against an existing codebase before sprint planning. Triggers on 'how complex is this ticket', 'what should we work on first', 'can we fit this in the sprint', 'tech review before planning', 'plan the sprint'. NOT for writing implementation plans (see mk:plan-creator); NOT for scope/ambition review (see mk:plan-ceo-review).
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Decompose tasks into structured, outcome-defined process entries with complexity triage. Load when user says "decompose this", "break this down", "what steps do I need", "plan this out", "what's the process for", "how do I approach this", or when any complex task needs structured execution planning. Includes a problem-understanding pass before complexity triage. Routes to `problem-to-plan` when the user needs planning deliverables (spec + plan + TODO). Does NOT replace brainstorming — brainstorming is design approval (upstream), this is execution planning (downstream).
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Socratic mentoring for junior developers and AI newcomers. Guides through questions, never answers. Triggers: "help me understand", "explain this code", "I'm stuck", "Im stuck", "I'm confused", "Im confused", "I don't understand", "I dont understand", "can you teach me", "teach me", "mentor me", "guide me", "what does this error mean", "why doesn't this work", "why does not this work", "I'm a beginner", "Im a beginner", "I'm learning", "Im learning", "I'm new to this", "Im new to this", "walk me through", "how does this work", "what's wrong with my code", "what's wrong", "can you break this down", "ELI5", "step by step", "where do I start", "what am I missing", "newbie here", "junior dev", "first time using", "how do I", "what is", "is this right", "not sure", "need help", "struggling", "show me", "help me debug", "best practice", "too complex", "overwhelmed", "lost", "debug this", "/socratic", "/hint", "/concept", "/pseudocode". Progressive clue systems, teaching techniques, and success metrics.
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Review blog posts, landing pages, and guides for readability. Estimate reading difficulty, identify long sentences and jargon, and simplify wording and paragraph structure so broad audiences can follow the content more easily.
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Plan study sample sizes, estimate statistical power—the chance of detecting an assumed effect—and find the smallest detectable effect. Supports standard tests and simulations for complex designs, with sensitivity analyses and sample size justifications.
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Review code changes for unnecessary complexity, including unused flexibility, avoidable dependencies, and abstractions with little purpose. Receive concise findings that name what to remove, what can replace it, and how many lines could be cut.
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Compare code structure across two commits, tags, or directories to identify security-relevant changes. Produces a report on new attack paths, privilege boundaries, complexity, and how widely a change could affect other functions.
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Interpret .NET coverage reports, which show code exercised by tests, to explain missing coverage and stalled progress. Calculate the gains needed to reach a target and, when requested, combine coverage with complexity to rank risk.
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Choose how an AI team handles each task, from a direct coordinator answer to parallel work by several agents. Includes decision criteria, example requests, and a short assignment template for small tasks.
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Token-efficient code analysis via 5-layer stack (AST, Call Graph, CFG, DFG, PDG). 95% token savings.
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Cross-functional what-if modeling for compound adversity -- shows how one problem cascades into the next. Use when facing complex risk scenarios, strategic decisions with major downside, or multi-variable threats.
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Token-efficient code analysis via 5-layer stack (AST, Call Graph, CFG, DFG, PDG). 95% token savings.
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Enter explore mode for technical work — a thinking partner for {{engine_name}} code, architecture, and implementation decisions before you write any code. Use it to investigate a technical solution, design the architecture of a feature, choose between frameworks or libraries, compare implementation approaches, analyze how existing code or a system works, or deeply root-cause a complex bug without fixing it yet. The ultra mode adds adaptive artifacts (a C4 view, ADRs, a dependency graph) to the research folder — run it on "ultra research", "ultra explore" or "ultraresearch"; otherwise run the default. Trigger on "let's explore this technical solution", "how should we architect this feature", "which framework should we use", "run an ultra research on the save system", "investigate this error deeply". Research and analysis only — it never writes code. This is the CODE / engineering explorer — for GAME-DESIGN, GDD, mechanics, or balance research (no code) use /unikit-gd-explore.
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Estimate the full development cost of an existing codebase from lines of code, architectural complexity, and team-composition overhead. Use for 'how much would this cost to build', 'what did this codebase cost', development-cost or build-cost estimates, calendar-time estimates, and Claude/AI ROI on a delivered codebase. Estimates by measured LOC and complexity, not by ticket volume.
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