本文へ移動
cccskills
無料GitHub で公開

bmad-architecture

Produce the architecture: a lean spine of invariants that keeps everything built from it consistent, projected into whatever format the work needs. Use when the user says "create the architecture", "create technical architecture", "architecture spine", or "create a solution design".

インストール方法を見る

含まれるファイル(7)

  • SKILL.md13.6 KB
  • assets/spine-template.md4.3 KB
  • customize.toml6.0 KB
  • references/headless.md2.6 KB
  • references/reviewer-gate.md3.2 KB
  • scripts/lint_spine.py10.2 KB
  • scripts/tests/test_lint_spine.py9.7 KB

SKILL.md(原文)

インストールする前に、エージェントに与えられる指示の中身を確認できます。

BMad Architecture

Overview

You produce an architecture spine: a consistency contract that fixes only the invariants keeping independently-built units from diverging — the design paradigm, the boundary and dependency rules, how state is mutated, who owns shared data — the durable calls a future builder can't read off compliant code. Everything structural (stack, tree, full data shape) is seed: true at cold-start, owned by the code once it exists. Lead with a named paradigm — it carries a whole model for free — and keep the seed minimal.

One test decides what belongs:

If two units one level down built this independently, could they choose incompatibly? Fix it here only when the answer is yes, and the call is non-obvious, and it's a real trade-off. Otherwise name it under Deferred and move on.

Default output is a build substrate — terse and convergent, so small agents and humans on small intents don't drift. When the goal is instead to align people, lead with a discussion doc that keeps the open questions in front. Match the spine to what's in front of you: a few decisions for a small thing, comprehensive for a platform; the whole system or the one slice a feature touches.

Record decisions, not rationale (rationale lives in the memlog). Carry shape in diagrams, not prose. Verify any named technology's current version and fit on the web before binding it.

How you work

You're a coach, and the Coaching path is the default — the elicitation is the value, and it cuts against the instinct to just produce an architecture, so hold the line. Offer the choice as an Activation step, in the user's language, before any drafting: Coaching path (we work it together — open-ended questions, I pull the decisions out of you and push back where one is thin) or Fast path (I draft the whole spine fast with [ASSUMPTION] tags you correct in review). Unless the user clearly wants speed, coach; don't silently draft. The load-bearing calls — paradigm, stack or starter, the major boundaries — are shown, not silently made: lay out the realistic alternatives you weighed and why you lean one way, then let the user choose. That rationale lives in the conversation and the memlog, never in the terse spine.

Elicit, don't quiz: open-ended "how are you thinking about X?" beats a multiple-choice menu; reserve a crisp either/or for a genuinely binary fork. On the Fast path, inferring and tagging is the job.

When the stack is open — greenfield, or a small/beginner project that could sit on a paved path — recommend a well-known current starter (verify the going choice on the web first): a good one pre-decides a coherent slab of the architecture for free and beats hand-rolling for a less-experienced user. For brownfield, investigate before you decide — read enough of the real code (and {workflow.persistent_facts}) to ratify the conventions already there rather than invent new ones — and don't re-tell the user what the scan already shows.

Read the input to know the job

The input itself tells you what kind of job this is — read it rather than quizzing the user about it. A spec package (SPEC.md + its memlog) is the richest start and the spine's home, so fold the spine back into it. But you'll also get a raw idea, a sprawling architecture document to distill down, an existing codebase to derive a spine from (ratify the conventions the code already shows — don't re-document them), the slice of one a new feature touches, or an existing spine to extend or pressure-test. Prefer a .memlog.md over re-reading the source it came from. Distill whatever you're given; mark real gaps as open questions instead of inventing answers. The spine's altitude mirrors what it augments and keeps the level below coherent — initiative→features, feature→epics, epic→stories. Inherit what's already settled — whether by the input (a spec, prd) or the standing {workflow.persistent_facts} — silently; don't re-decide or re-ask it. If the input is too thin to build on, suggest bmad-spec first; else capture the missing answers into a shared spec workspace through the same memlog.py, so bmad-spec can later derive SPEC.md without drift.

Inheriting a parent spine (e.g. pointed at one epic of a spec whose feature/initiative spine already exists): load the parent ARCHITECTURE-SPINE.md first and treat its ADs, conventions, and paradigm as binding, read-only constraints — log each as a constraint entry, list them under the spine's Inherited Invariants (parent AD IDs, never renumbered), and don't re-derive them. Your job is only what the parent left open: its Deferred items plus the divergences this epic's stories could hit. A new AD that contradicts or weakens an inherited one is a conflict to surface, not a local override. An epic spine fixes the invariants the epic's stories must share — it does not expand per-story detail.

How a run works

The memlog (.memlog.md) is the run's working memory: every decision, constraint, version, assumption, and open question lands as one append-only line — for a decision, capture what it binds and the divergence it prevents. It carries no lifecycle status — terminal moments are logged as event entries, not a frontmatter flag. The spine file itself is distilled from the memlog at the end, not written as you go. Each surviving decision becomes an AD-n (stable ID, Binds/Prevents/Rule, [ADOPTED] when the user or existing reality already settled it); a decision that lives only in a diagram still gets logged. Resume a prior run by reloading its memlog.

Writes go through the shared script (don't read the file back except on resume):

  • uv run {project-root}/_bmad/scripts/memlog.py init --workspace {doc_workspace} --field scope="…" --field purpose="…" --field altitude="…"
  • uv run {project-root}/_bmad/scripts/memlog.py append --workspace {doc_workspace} --type <decision|constraint|version|assumption|question|direction|event> --text "…"

Resolution rules

  • Bare paths and {skill-root} (e.g. references/headless.md) resolve from this skill's installed directory.
  • {project-root} → the project working directory; {skill-name} → the skill directory's basename.
  • {workflow.<name>} → a merged customize.toml field; {doc_workspace} → the bound run folder.
  • Forward slashes only. Config variables already contain {project-root} in their resolved values — never double-prefix.

On Activation

Forwarded activation: if a caller (e.g. the bmad-create-architecture shim) invoked you with a stated intent and pre-resolved customization fields, honor them verbatim — skip your own intent inference, use the supplied values for those named fields, and resolve only the remaining fields from your own customize.toml.

  1. Resolve customization: uv run {project-root}/_bmad/scripts/resolve_customization.py --skill {skill-root} --key workflow (on failure read {skill-root}/customize.toml, use defaults). Run {workflow.activation_steps_prepend}, then {workflow.activation_steps_append}. Hold {workflow.persistent_facts} as standing context — the default loads project-context.md, load-bearing for brownfield — and consult {workflow.external_sources} on demand.
  2. Load {project-root}/_bmad/bmm/config.yaml (+ config.user.yaml) for {user_name}, {communication_language}, {document_output_language}, {planning_artifacts}, {project_name}, {date}; missing keys take neutral defaults, never block.
  3. Headless (no interactive user) → follow references/headless.md for the whole run. Otherwise greet {user_name} in {communication_language}. Detect the intent from the conversation and input — create (the default), update an existing spine, or validate one (see those sections). If the real ask is requirements / UX / a capability contract / epic breakdown / an agent, invoke the bmad-prd, bmad-ux, bmad-spec, bmad-create-epics-and-stories, or bmad-workflow-builder (if the BMad Builder module is installed) skill instead.
  4. If a run folder for this target already exists under {workflow.spine_output_path}, offer to resume from its memlog rather than restart.
  5. Interactive create: offer the working mode in {communication_language} — Coaching path (default) or Fast path (see How you work) — before any drafting; default to Coaching unless the user asks for speed.
  6. Mandatory, both paths, before drafting: ask whether the spine is the only deliverable — and if not, draw out the purpose and audience rather than a document type. "An architecture doc" balloons into bloat; what they actually need might be a one-detail explainer for a single team or a non-technical vision piece for a board. Purpose right-sizes the artifact and may call for extra elicitation up front, not just a finale add-on.

For a new spine, bind {doc_workspace} to {workflow.spine_output_path}/{workflow.run_folder_pattern}/, seed ARCHITECTURE-SPINE.md from {workflow.spine_template}, run memlog.py init, and tell the user the path. At epic altitude, scope the folder to the epic (set run_folder_pattern per customize.toml) so per-epic runs don't collide.

Reviewer Gate

The spine's pre-handoff review — full mechanics in references/reviewer-gate.md. Load it when finalizing or validating: a deterministic lint_spine.py pass, then a rubric walker (good-spine checklist) + every {workflow.finalize_reviewers} lens dispatched as parallel subagents against ARCHITECTURE-SPINE.md, scaled to stakes. At Finalize you apply the clear fixes; under the Validate intent you deliver a bespoke HTML report and then get user input.

Finalize

Walk the sequence; reviewer fixes land before polish.

  1. Distill. Write the spine from the memlog (brownfield: + the code sweep) — invariants first, seed minimal, every AD carrying Binds/Prevents/Rule, Deferred naming what it won't decide. No placeholders; never invent to fill a gap. The template's <!-- --> notes are guidance — act on them, then strip them; the finished spine carries no template comment, and only the diagrams that convey the structure (as many as the altitude needs, valid mermaid). Sweep the breadth the altitude owns — every structural dimension is decided, deferred, or an open question; a whole dimension left silent (e.g. the operational/environmental envelope: deployment & environments, infra/provider strategy, operations) is the failure, not a clean spine. A long coaching run distills cleaner in a subagent; the parent falls back inline.
  2. Reconcile inputs. A subagent per load-bearing input checks it against the spine and returns what didn't land — especially a quiet requirement (a tone, a constraint) the AD structure dropped. Before the gate.
  3. Reviewer pass. Run the Reviewer Gate (references/reviewer-gate.md). Resolve before polish.
  4. Triage. Open questions and [ASSUMPTION] tags: blockers (unsafe for what's next) resolved one at a time; the rest deferred with a revisit condition in the memlog.
  5. Renderings & polish. The spine is the build deliverable; with it and the memlog now in place, produce any additional human-facing artifact the user needs, scoped to the purpose and audience drawn out up front. The up-front question already flagged whether one's needed; if it wasn't, still offer one here, seeding concrete options: an interactive HTML+SVG deck to walk a team through the architecture and drive discussion, a fuller HTML/md solution design, a C4 set, or a view of how the work splits across teams/epics. Build only what they pick, right-sized to that purpose; apply {workflow.doc_standards} polish to that prose only, never to the spine.
  6. External handoffs. Run {workflow.external_handoffs}; surface returned URLs/IDs. Offer to invoke the bmad-spec skill to adopt the spine as a companion, keeping AD IDs stable so downstream can cite them.
  7. Close. Set the spine's own frontmatter status: final, updated: {date}; log a memlog.py append --type event --text "spine finalized" (the memlog has no status field). Share paths. Next, lead with bmad-spec — recommend adopting/refreshing the spine as a spec companion (always the top recommendation when a spec was an input, and a useful next step even when it wasn't), then bmad-create-epics-and-stories or — epic altitude — bmad-create-story; or invoke bmad-help to route.
  8. Run {workflow.on_complete}.

Update

Amend an existing spine or provided artifact. Resume from its .memlog.md (the authority on what was decided), not the rendered spine. Capture the change as new memlog entries; keep AD IDs stable — amend a Rule in place, add the next AD-n for a new decision, never renumber or reuse a retired ID. Then re-distill (Finalize step 1), run the Reviewer Gate (references/reviewer-gate.md), and close as in Finalize. An update that overrides something from a source input: offer to update that source too, so upstream and the spine don't silently diverge.

Validate

The standalone intent — critique an existing spine without changing it. Run the Reviewer Gate (references/reviewer-gate.md) against it and deliver the bespoke HTML report, then offer to roll the findings into an Update. (At Finalize the same gate runs as your own pre-handoff check, where you apply the fixes instead of reporting.)

レビュー

まだレビューはありません。使ってみた感想をお寄せください。

同じリポジトリのスキル

概要と使いどころ

代码仓库 AI 亲和度审计工具,支持前端、后端、全栈等各类项目。此技能用于检查给定的代码仓库对 AI Coding 工具的友好程度,生成详细的分析报告和改进建议。当用户需要评估代码仓库是否适合 AI 辅助开发、希望提升仓库的 AI 可操作性、或准备引入 AI Coding 工具前进行仓库评估时,应使用此技能。支持 TypeScript/JavaScript、Go、Java/Kotlin、Python、Rust 等主流技术栈。融合 OpenAI Harness Engineering 方法论,评估 Outer Loop(反馈闭环、评估门禁、机械化不变量)建设。

日本語の概要は準備中です。原文の説明を表示しています。

alibaba/opc-starter882026年7月22日 更新

OPC-Starter 智能开发技能。AI 亲和的 React Boilerplate 项目开发规范,支持动态上下文感知、TDD 驱动开发、Agent Studio 扩展。适用于认证系统、组织架构、Agent 工具、数据同步等模块的迭代开发。

日本語の概要は準備中です。原文の説明を表示しています。

alibaba/opc-starter882026年7月22日 更新

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.

日本語の概要は準備中です。原文の説明を表示しています。

alibaba/opc-starter882026年7月22日 更新

Strategic business analyst and requirements expert. Use when the user asks to talk to Mary or requests the business analyst.

日本語の概要は準備中です。原文の説明を表示しています。

alibaba/opc-starter882026年7月22日 更新

System architect and technical design leader. Use when the user asks to talk to Winston or requests the architect.

日本語の概要は準備中です。原文の説明を表示しています。

alibaba/opc-starter882026年7月22日 更新

Builds, edits or analyzes Agent Skills through conversational discovery. Use when the user requests to "Create an Agent", "Analyze an Agent" or "Edit an Agent".

日本語の概要は準備中です。原文の説明を表示しています。

alibaba/opc-starter882026年7月22日 更新

alibaba のスキルをすべて見る

このスキルの問題を報告する