'subagents' 검색 결과

Test skills via TDD in fresh subagents. Use when validating behavior or preventing bias.

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Finds the cause of a hard bug by running several read-only subagents in parallel, each attacking it from a different angle (change history, code path, data and state, environment, reproduction), then checking their evidence, ranking the hypotheses and naming the one experiment that would confirm the leader. It diagnoses and does not fix. Use when someone says "hunt this bug with multiple agents", "swarm on this regression", "investigate in parallel", "find the root cause", or when a failure is intermittent, crosses components, or has resisted a first look.

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Skill-aware orchestration with context routing. Decomposes complex tasks into skill-typed subtasks, extracts targeted context subsets, executes subagents in parallel, and synthesizes results. Self-answers trivial lookups inline. No SDK dependency — uses raw HTTP via httpx. Use when tasks require multiple analytical perspectives, when context is large and subtasks only need portions, or when orchestrating-chat-agents spawns too many redundant subagents.

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Use this skill when the user's prompt requires (1) researching a topic across multiple sources, comparing options or alternatives, analyzing trends or history, understanding markets or industries, or reviewing literature or studies and (2) synthesizing that research into a comprehensive, narrative report. If you're planning to search the web or internal knowledge bases, consider using this skill. This skill coordinates research subagents, so use it only when you have a tool for spawning subagents (the Agent or Task tool); otherwise, research the question directly.

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Creates structured handoff briefings between agents. Use when delegating complex work to subagents that would otherwise lose context. Packages task context, constraints, and progress into a compact packet that subagents can consume without re-reading the full conversation. Prevents the 'lost context' problem in multi-agent delegation.

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Runs a multi-model orchestration workflow led by the session's Fable or Claude Opus model. Sends menial tool-calling work to Haiku subagents, judgment work to Opus subagents at an effort matched to each task, and high-stakes or fresh-perspective questions to a GPT-6 Astra Codex peer. Detects the lead from session context; `--lead fable` or `--lead opus` overrides. Use to orchestrate, delegate, fan out, get a decorrelated Codex opinion, run a blind Opus-Codex cross-check, or act as tech lead.

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Fully autonomous bug hunting pipeline — discover bugs in a scoped area using parallel subagents, independently triage each finding, fix confirmed issues with subagents, then audit all fixes against repo constraints and target platforms. Runs end-to-end without user interaction.

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Catalog-then-fix slop removal on an existing prose draft. Parallel catalog subagents inventory four slop categories (theatrics, overwrought register, corrective antithesis, dramatic short sentences), fix subagents repair only what a catalog names, mechanical lint + frequency analysis bracket the run, and a regression gate (lint delta, word count, cold meaning check) decides whether the result ships. Use when the user says "deslop this draft", "catalog deslop", "strip the AI patterns from this file", or as the final stage of the article-factory and mosaic-writing skills. For writing or redrafting prose from scratch, use the prose skill instead - this skill only repairs an existing draft in place.

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Coordinates staged or parallel jobs across live-verified coding-agent runtimes (Claude Code, Codex, Cursor, and other installed CLIs) and in-session toolkit subagents. Routes each job by capability and risk tier, isolates parallel writers in git worktrees, captures redacted output, resumes interrupted runs, and blocks completion until an independent arbiter verifies the results. Use when work should be split across multiple runtimes or subagents, run as staged or parallel jobs, and reviewed before handoff. NOT for a single-agent task or the in-session 7-phase flow (use mk:cook / mk:workflow-orchestrator).

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Coordinate complex engineering work across bounded subagents while protecting the main context, preventing edit conflicts, and measuring whether delegation was worthwhile. Use when the user asks to delegate, parallelize, orchestrate, use subagents, fan out a review, or handle a large task with independent workstreams; do not use for small, tightly coupled, or inherently sequential tasks.

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RED-GREEN-REFACTOR for process documentation - baseline without skill, write addressing failures, iterate closing loopholes

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Expert en workflow Claude Code (commands, skills, subagents, CLAUDE.md, best practices)

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Use when executing implementation plans with independent tasks in the current session — trigger phrases "execute the plan", "independent tasks", "parallel tasks", "subagents for the plan","split the plan into subagents". Dispatches a fresh subagent per task with two-stage review after each: spec compliance first, then code quality.

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Use this skill when the user's prompt requires (1) researching a topic across multiple sources, comparing options or alternatives, analyzing trends or history, understanding markets or industries, or reviewing literature or studies and (2) synthesizing that research into a comprehensive, narrative report. If you're planning to search the web or internal knowledge bases, consider using this skill. This skill coordinates research subagents, so use it only when you have a tool for spawning subagents (the Agent or Task tool); otherwise, research the question directly.

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같은 세션에서 기존 구현 계획을 작업별로 실행합니다. 테스트의 실패와 성공, 진행 상황과 판단을 기록하고 마지막에 브랜치 전체를 검토합니다.

• 작성된 개발 계획 구현
• 별도 구현 에이전트 없이 작업 진행
• 진행 기록을 바탕으로 작업 재개

검색과 평가를 반복하여 하위 에이전트의 작업에 필요한 코드와 배경 정보를 추립니다. 발견한 용어와 부족한 정보를 다음 검색에 반영해 관련 파일을 모읍니다.

• 결함 수정 담당자에게 필요한 파일 찾기
• 기능 추가 전 기존 구현 수집
• 프로젝트 용어에 맞춰 검색 조정

Carry out an implementation plan by assigning each task to a fresh subagent, a separate agent with its own context. Review specification compliance first, then code quality, repeat fixes as needed, and finish with an integration review.

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• Execute a feature implementation plan task by task
• Check specification compliance before reviewing code quality
• Develop with tests written before implementation

Build Claude Code hooks, automated checks triggered by events such as tool use or session start. The guidance covers prompt-based decisions, command scripts, configuration, testing, and debugging for validation and workflow automation.

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• Checking commands and file writes before execution
• Verifying task completion before an agent stops
• Loading project context when a session starts

Delegate code lookup, small edits, and diff reviews to three specialized subagents. Their compact, structured results help conserve the main agent's context, with guidance on when to delegate and when to keep work in the main conversation.

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• Locating definitions and callers
• Making a focused edit across one or two files
• Reviewing a diff for bugs

Connect RuView sensing data to AI agents through tools for presence, breathing, and heart rate. Explore agent coordination and prototype storing agent state and decisions alongside sensing data in a shared RVF container.

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• Read live presence and vital-sign data from an agent
• Prototype agent responses to room-presence events
• Design coordination between sensing subagents

Design and build AI agents for business, research, operations, or creative work. Define essential actions and knowledge, start with a simple execution loop, and add progress tracking or separate child agents as needs emerge.

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• Designing an assistant for business tasks
• Building a research agent
• Choosing essential actions and knowledge

Delegate complex work through a tree of Claude Code sub-agents. Each level uses its own working context and returns concise summaries, helping the coordinating agent manage research, verification, and synthesis without retaining every intermediate detail.

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• Divide research, expansion, verification, and synthesis into layers
• Handle work with more intermediate detail than one agent can retain
• Assign specialized checks to different leaf agents

Coordinates a named team of Codex workers with concrete responsibilities and shared progress records. It selects available collaboration tools, manages communication and separate working copies when needed, and handles integration, team archival, and cleanup after the work ends.

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• Splitting related implementation work across cooperating agents
• Investigating several aspects of a clearly defined problem
• Inspecting team progress and member responsibilities

Take implementation work through small, independently mergeable pull requests. Use a separate working directory for each PR, record manual QA evidence, write English review descriptions, resolve CI and review findings, then merge and clean up.

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• Deliver implementation work through pull requests
• Split a large task into small, independently mergeable PRs
• Build independent PRs concurrently