'multi-file' 검색 결과

Deploy a 2-layer parallel agent hierarchy for large, parallelizable work — big refactors, multi-file migrations, codebase-wide audits, bulk generation. A top-tier commander (Fable or Opus) orchestrates the swarms; the user picks a power level (Max Power / Heavy / Balanced / Economy) that sets the Opus/Sonnet/Haiku model mix per layer. Layer 1 is 3-50+ specialist agents, each with its own full context window; Layer 2 is 2+ sub-agents per member. Includes git safety, tiered sizing, a pre-deploy gate, phantom-completion checks, and multi-wave follow-up.

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Automate 7-phase feature development with specialized agents (code-explorer, code-architect, code-reviewer). Use for multi-file features, architectural decisions, or encountering ambiguous requirements, integration patterns, design approach errors.

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Build a precise, step-by-step action plan before making any code changes. Use this skill whenever the user describes a feature, bug fix, refactor, or any multi-file change. Also use when the user says "plan", "think through", "what would it take", or describes a problem without jumping to code. TRIGGER BEFORE writing any code for non-trivial changes. Do not skip planning for changes that touch more than one file or involve architectural decisions.

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Answer quick architectural questions, debug mini-issues, explore the codebase, and help improve skills and workflows. Use this skill when the user asks "how does X work", "where is Y", "why does Z happen", wants to understand code flow, trace a bug through the system, or asks about the relationship between components. Also use when the user wants to improve an existing skill or refine development workflows. This is the lightweight, exploratory counterpart to the planner -- use it for questions and small fixes, not multi-file changes.

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Build software with Cursor, the AI-powered code editor. Use when a user asks to configure Cursor rules, set up .cursorrules files, use Composer for multi-file edits, integrate MCP servers, or optimize AI-assisted coding workflows.

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Suede AI umbrella router for the public Suede pack: selects the right specialist across copy, design, code review and grading, SEO and visibility, launch packaging, MCP QA, iOS and Android shipping, growth, and creator rights work. Use when a request crosses two or more Suede lanes, when the user wants the full public skill pack loaded from one installable path, when they ask which Suede skill fits a task, or when only this umbrella skill is installed. NOT FOR: a request that names one lane and can go straight to its specialist; a multi-file repo change that should be built and reviewed as one DAG (use suede-graph-flo-xr).

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Suede Thought Graph shipping search for a multi-file repo change. Use when competing implementation plans need one evidence-gated selection before any build. Halts on hazards, collisions, budget exhaustion, or no safe winner. Reads production; never deploys. NOT FOR: bulk independent work (use a separate private worker-fleet pass); findings-only diff review (use suede-code-review); CI or branch-protection wiring (use suede-ci-gate); copy-only shipping (use suede-ship-copy).

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Suede-owned operations-architecture discipline that fixes the shape of a system before anyone builds it: entity schema first, exactly one write path per entity, every unit of work routed to a deterministic automation, an AI agent, or a human decision, every existing tool marked absorb, keep, or kill, and the build sequenced into phases whose completion is proved by a command. Use when scoping an automation or agent build, deciding whether a workflow needs a model at all, consolidating a sprawling tool stack, designing the data model under a workflow, choosing a migration path off an old system, or ordering a build so nothing lands on a moving foundation. NOT FOR: executing a planned multi-file repo change (use suede-graph-flo-xr); coordinating parallel builders with file ownership (use suede-agent-teams); lead lifecycle, scoring, and CRM routing rules (use suede-revops); proving agent output quality against an eval set (use suede-ai-eval); reviewing the finished diff (use suede-code-review).

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Structured planning mode for AI agents working on coding and development tasks. Produces a comprehensive plan BEFORE any code is written or changed, including task decomposition, architecture decisions, risk assessment, and approval gates. Use this skill whenever the user says "/plan", "plan mode", "plan first", "think before coding", "make a plan", or asks the agent to plan before executing. Also trigger when the user describes a complex multi-step development task and would clearly benefit from structured planning before implementation — especially for tasks involving new features, refactors, migrations, infrastructure changes, or multi-file edits. When in doubt, plan. A few minutes of planning prevents hours of rework.

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Invoke the rubber duck reviewer for a second opinion. Use after planning, after complex multi-file implementations, or after writing tests. Produces a focused CRITICAL/WARN/INFO list and a APPROVE/REQUEST_CHANGES verdict.

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Create a structured session handoff when context is running low or work is pausing. Deep context mining, self-validation, multi-file splitting. Captures everything the next session needs.

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Evaluates and scores Claude prompts and system prompts using a six-dimension Scorecard with anchored 1-5 rubrics. Trigger on: "review my prompt," "score this prompt," "rate my prompt," "evaluate this prompt," "improve my prompt," "what's wrong with my prompt." Also trigger on: "why isn't my prompt working," "my prompt produces bad output," "help me fix this prompt," "is this prompt any good." Scorecard covers Objective Clarity, Context Specificity, Reasoning Fit, Output Precision, Behavioral Calibration, and Architectural Efficiency, plus a five-question Output Evaluation Rubric for assessing actual output. Also use when the user pastes a system prompt and asks for feedback. Activate whenever structured quality assessment of a single prompt is the primary need. Do NOT use for project-level audits involving Custom Instructions architecture, knowledge file organization, or multi-file Project structure (use rootnode-project-audit if available).

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Orchestrate complex development with AUTOMATIC parallel subagent execution, continuous dispatch scheduling, dependency analysis, file conflict detection, and IOSM quality gates. Analyzes task dependencies, builds critical path, launches parallel background workers with lock management, monitors progress, auto-spawns from discoveries. Use for multi-file features, parallel implementation streams, automated task decomposition, brownfield refactoring, or when user mentions "parallel agents", "orchestrate", "swarm", "continuous dispatch", "automatic scheduling", "PRD", "quality gates", "decompose work", "Mixed/brownfield".

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Use when implementing a multi-file change, building a feature from a breakdown, or writing a large amount of code. Not for a single settled ticket: use work.

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Plan a feature or task in fast, full, or ultra mode. Ultra creates an indexed multi-file bundle with deeply specified phases for execution by a smaller model. Use for "plan", "new feature", "start feature", "create tasks", or exhaustive implementation planning.

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Get productive with agentic coding assistants — task framing, iterative prompting, file-scoped workflows, review loops, and multi-file refactors. Use when pairing with an AI coding agent on real codebases.

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End-to-end AI website generation pipeline. Claude Opus 4.8 emits Bolt-style <boltArtifact> envelopes (multi-file, plan-first) that customize Vite+React+Tailwind templates from pre-researched business data. Pre-research via APIs, media acquisition, brand extraction, visual inspection via GPT Image 2 vision, R2 upload (per-file content-type by extension), D1 status updates. Supports all business types: SaaS, portfolio, non-profit, restaurant, salon, medical, legal, retail, tech.

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Invoke a Rubber Duck Reviewer subagent to independently critique plans and implementations before proceeding. Use when the agent is about to implement a non-trivial plan (multi-file changes, architectural decisions, security-sensitive logic, database schema changes), after completing a self-contained unit of work (module, endpoint, feature), when stuck or facing repeated failures (same test fails 2+ times, unexpected results), or when the agent wants independent validation of assumptions and design decisions. Triggers on any non-trivial implementation task where independent critique would catch blind spots before they become costly mistakes.

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Install Taskfile (task) and scaffold or audit Taskfile.yml configurations with ecosystem-aware templates. Auto-detects Node.js/pnpm, JVM/Gradle, Python/uv, Docker, and recommends single-file or multi-file (includes) patterns based on project complexity. Use when user runs /devtools:taskfile-setup, mentions "taskfile setup", "setup task runner", "audit taskfile", "scaffold taskfile", "add taskfile", "taskfile.yml", or "developer tasks".

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Create an implementation plan for a feature — a dependency-ordered, actionable task list for the project. Has four modes: fast (a quick single-pass plan), full (a richer plan that can also create a git branch), ultra (a multi-file bundle — a manifest plus one deeply specified file per phase — for execution by a smaller model), and add (extend an existing plan with more tasks). Pick the mode from the user's wording: "full plan" runs full; "quick plan" or "fast plan" runs fast; "ultra plan", "ultraplan" or "ultra-plan" runs ultra; a plain "create a plan" with no qualifier defaults to fast; "add to the plan" or "extend the plan" runs add. Use whenever the user wants to plan a feature or task, e.g. "create a plan", "create a full plan", "create a quick plan", "run an ultra plan for the inventory system", "plan this feature", "add this to the plan", "extend the plan", "add a phase to the plan". Ultra runs only when the user names it — never because the feature looks large.

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Appwrite CLI skill. Use when managing Appwrite projects from the command line. Covers installation, login, project initialization, multi-file project configuration, deploying functions/sites/tables/buckets/teams/webhooks/topics, flag-based list queries, non-interactive CI/CD mode, and generating type-safe SDKs.

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Multi-file hypothesis testing with keep/discard loop, compound baselines, and experiment logging

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Spin up a coordinated multi-agent swarm (hierarchical or mesh topology) to work a complex, multi-file task on a ruOS desktop. Use when a task needs 3+ agents working in parallel with anti-drift coordination; skip for single-file edits.

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Coordinate large-scale codebase migrations and multi-file refactors across hundreds of files. Manage framework upgrades, API renames, and config rewrites using batched PRs, issue tracking, and CI verification.

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