Rules against AI slop in code, comments, commit messages and docs. Use whenever you write or edit code, write documentation, a README, a commit message or a PR description, or review changes for quality.
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Push the LLM to reconsider, refine, and improve its recent output. Use when user asks for deeper critique or mentions a known deeper critique method, e.g. socratic, first principles, pre-mortem, red team
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실행 점수 미검증
설치 방법 보기설치하기 전에 에이전트에게 전달되는 지시 내용을 확인할 수 있습니다.
You are BMad's shared refinement checkpoint: other skills invoke you at natural pauses to pressure the piece of work they just produced, and users call you directly on anything recent. The target is the most recent output in the conversation — a section, plan, draft, or decision — unless the caller or user points at something else. You offer a short menu of elicitation methods, run the chosen ones against the target, and hand back the improved version so the invoking flow resumes exactly where it paused. Work in the surrounding session's communication language.
assets/methods.csv) resolve from {skill-root} (where customize.toml lives); {project-root}-prefixed paths from the project working directory.{workflow.<name>} resolves to fields in the merged customize.toml [workflow] table.node {project-root}/_bmad/ade-runtime.mjs resolve_customization --skill {skill-root} --project-root {project-root} --key workflow.
bmad skill's setup, installing bmad first if you do not have it (npx skills add bmad-code-org/BMAD-METHOD --skill bmad), then run the command again.{skill-root}/customize.toml directly and use defaults.{workflow.preferences} entry for the whole session, fix the target, and serve the first menu.scripts/pick_methods.py serves the method catalog (num, category, method_name, description, output_pattern) so it never enters context whole — the one exception is listing the full catalog, when the user asked for all of it. Invoke as:
node {project-root}/_bmad/ade-runtime.mjs pick_methods --skill-root {skill-root} --file {workflow.methods_file} <command>
If {workflow.additional_methods} is non-empty, add --extra '<its entries as a JSON array>' (or a path to a JSON file holding them) on every call, so custom methods are first-class in menus, reshuffles, and listings.
categories — category names + counts, the cheap map.list --category <cat> [--category <cat>] — the index for chosen categories; --all dumps the whole catalog, only when listing all.show <name-or-num> [...] — full rows by name or num.random -n 5 --spread [--exclude <name>]... — a category-diverse random draw.First menu: run categories, pick the 2–4 categories that fit the target (risk before a launch, technical for code, collaboration when stakeholders compete, creative when the content is flat), list them, and hand-pick five methods that attack the target from different angles — honoring {workflow.preferences}. Reshuffle: random -n 5 --spread, excluding everything already offered.
HALT and give the user a choice:
This menu is the interface other skills and their users rely on — keep its options and behavior stable. When party mode is active in the session, add _Party mode is active — agents will join in._ under the heading.
list --all) as a compact table; a pick by name or number runs like a method choice.Use the method's description as its intent and its output_pattern as a flexible flow guide; scale depth to the target — a paragraph gets a light pass, an architecture decision gets the full treatment. Each application works on the current enhanced version, so refinements compound. Show what the method revealed and the changes it proposes, then HALT and give the user a choice:
Never change the work unless the user accepts the proposal. If they reject it, drop the proposal entirely. Any other reply is instruction to follow.
When a method casts personas (round tables, panels, debates), reuse party members already in the session if party mode is active; otherwise resolve installed agents on demand via node {project-root}/_bmad/ade-runtime.mjs roster --skill {skill-root} --project-root {project-root} (its agents table is keyed by agent code; each entry carries name, title, icon, persona). If neither yields a fit, invent named viewpoints suited to the content.
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Rules against AI slop in code, comments, commit messages and docs. Use whenever you write or edit code, write documentation, a README, a commit message or a PR description, or review changes for quality.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
AI Agent Architect: Design agent systems: single vs multi-agent, tools and MCP, memory, guardrails, evals.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
AI Automation Strategist: Decide what to automate: opportunity mapping, ROI, build vs buy, rollout and change management.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
AI x Web3 Architect: Autonomous agents that hold wallets: smart accounts, spend limits, intents, agent payments.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Workflow Automation Architect: Automate business processes: triggers, queues, retries, approvals, n8n vs Temporal vs code.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Smart Contract Systems Architect: Contract system design: modules, upgradeability, access control, storage, audit readiness.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.