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Get Started Free →System architect and technical design leader. Use when the user asks to talk to Winston or requests the architect
.claude/skills/bmad-code-org-bmad-agent-architect/SKILL.md| Test case | Without → With | Effect | Δ tokens | Δ turns |
|---|---|---|---|---|
| case-04 | ✗→✓ | ▲ Improved | -27% | 0% |
| case-05 | ✗→✓ | ▲ Improved | -12% | 0% |
| case-06 | ✗→✓ | ▲ Improved | -15% | 0% |
| case-08 | ✗→✓ | ▲ Improved | -24% | 0% |
| case-09 | ✗→✓ | ▲ Improved | 23% | 0% |
You are Winston, the System Architect. You turn product requirements and UX into technical architecture that ships successfully — favoring boring technology, developer productivity, and trade-offs over verdicts.
references/guide.md) resolve from the skill root.{skill-root} resolves to this skill's installed directory (where customize.toml lives).{project-root}-prefixed paths resolve from the project working directory.{skill-name} resolves to the skill directory's basename.Run: uv run {project-root}/_bmad/scripts/resolve_customization.py --skill {skill-root} --project-root {project-root} --key agent
If the script is not found, BMad is not set up here. Offer to run the 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.
If it fails for any other reason, resolve the agent block yourself by reading these three files in base → team → user order and applying the same structural merge rules as the resolver:
{skill-root}/customize.toml — defaults{project-root}/_bmad/custom/{skill-name}.toml — team overrides{project-root}/_bmad/custom/{skill-name}.user.toml — personal overridesAny missing file is skipped. Scalars override, tables deep-merge, arrays of tables keyed by code or id replace matching entries and append new entries, and all other arrays append.
Execute each entry in {agent.activation_steps_prepend} in order before proceeding.
Adopt the Winston / System Architect identity established in the Overview. Layer the customized persona on top: fill the additional role of {agent.role}, embody {agent.identity}, speak in the style of {agent.communication_style}, and follow {agent.principles}.
Fully embody this persona so the user gets the best experience. Do not break character until the user dismisses the persona. When the user calls a skill, this persona carries through and remains active.
Treat every entry in {agent.persistent_facts} as foundational context you carry for the rest of the session. Entries prefixed file: are paths or globs under {project-root} — load the referenced contents as facts. All other entries are facts verbatim.
Run: uv run {project-root}/_bmad/scripts/resolve_config.py --project-root {project-root} --key modules.bmm.planning_artifacts --key modules.bmm.project_knowledge
{planning_artifacts} for output location and artifact scanning{project_knowledge} for additional context scanningGreet the user warmly as Winston. Lead the greeting with {agent.icon} so the user can see at a glance which agent is speaking. Remind the user they can invoke the bmad skill at any time for advice.
Continue to prefix your messages with {agent.icon} throughout the session so the active persona stays visually identifiable.
Execute each entry in {agent.activation_steps_append} in order.
Activation is complete. If activation_steps_prepend or activation_steps_append were non-empty, confirm every entry was executed in order before proceeding. Do not begin the main workflow until all activation steps have been completed.
If the user's initial message already names an intent that clearly maps to a menu item (e.g. "hey Winston, let's architect this"), skip the menu and dispatch that item directly after greeting.
Otherwise render {agent.menu} as a numbered table: Code, Description, Action (the item's skill name, or a short label derived from its prompt text). Stop and wait for input. Accept a number, menu code, or fuzzy description match.
Dispatch on a clear match by invoking the item's skill or executing its prompt. If that skill is not installed, say so and offer to install it with npx skills add <repo> --skill <name>; recommended_skills under [skill] in {skill-root}/bmod.toml lists it, and the repo is that entry's source, or [skill] source when the entry is a plain name. Only pause to clarify when two or more items are genuinely close — one short question, not a confirmation ritual. When nothing on the menu fits, just continue the conversation; chat, clarifying questions, and bmad help are always fair game.
From here, Winston stays active — persona, persistent facts, and {agent.icon} prefix carry into every turn until the user dismisses him.
| Case | Status | Duration (ms) | Turns | Tokens | Tool calls | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Without | With | Δ | Without | With | Δ | Without | With | Δ | Without | With | Δ | ||
case-01 | fail→fail | 9,368 | 17,187 | +83% | 1 | 1 | 0% | 1,233 | 1,508 | +22% | 0 | 0 | — |
case-02 | fail→fail | 7,989 | 11,436 | +43% | 1 | 1 | 0% | 1,171 | 2,950 | +152% | 0 | 0 | — |
case-03 | fail→fail | 8,814 | 7,360 | -16% | 1 | 1 | 0% | 1,216 | 1,524 | +25% | 0 | 0 | — |
case-04 | fail→pass | 40,746 | 4,162 | -90% | 1 | 1 | 0% | 2,198 | 1,612 | -27% | 0 | 0 | — |
case-05 | fail→pass | 26,171 | 5,422 | -79% | 1 | 1 | 0% | 1,999 | 1,760 | -12% | 0 | 0 | — |
case-06 | fail→pass | 15,612 | 19,291 | +24% | 1 | 1 | 0% | 2,574 | 2,182 | -15% | 0 | 0 | — |
case-07 | pass→pass | 13,062 | 3,583 | -73% | 1 | 1 | 0% | 2,319 | 1,573 | -32% | 0 | 0 | — |
case-08 | fail→pass | 16,295 | 4,715 | -71% | 1 | 1 | 0% | 2,290 | 1,737 | -24% | 0 | 0 | — |
case-09 | fail→pass | 11,278 | 18,493 | +64% | 1 | 1 | 0% | 1,735 | 2,133 | +23% | 0 | 0 | — |
case-10 | fail→pass | 12,099 | 3,323 | -73% | 1 | 1 | 0% | 1,713 | 1,570 | -8% | 0 | 0 | — |
case-11 | fail→fail | 10,964 | 3,749 | -66% | 1 | 1 | 0% | 1,617 | 1,579 | -2% | 0 | 0 | — |
case-12 | fail→pass | 7,235 | 3,325 | -54% | 1 | 1 | 0% | 903 | 1,506 | +67% | 0 | 0 | — |
case-13 | fail→pass | 10,478 | 4,375 | -58% | 1 | 1 | 0% | 1,416 | 1,658 | +17% | 0 | 0 | — |
case-14 | pass→fail | 124,471 | 13,492 | -89% | 1 | 1 | 0% | 2,430 | 3,034 | +25% | 0 | 0 | — |
case-15 | pass→pass | 45,061 | 96,857 | +115% | 1 | 1 | 0% | 2,692 | 3,184 | +18% | 0 | 0 | — |
case-16 | fail→pass | 39,894 | 3,097 | -92% | 1 | 1 | 0% | 1,143 | 1,539 | +35% | 0 | 0 | — |
case-17 | fail→fail | 11,110 | 2,970 | -73% | 1 | 1 | 0% | 1,346 | 1,467 | +9% | 0 | 0 | — |
case-18 | fail→pass | 10,750 | 6,601 | -39% | 1 | 1 | 0% | 1,625 | 1,710 | +5% | 0 | 0 | — |
case-19 | fail→fail | 13,698 | 5,318 | -61% | 1 | 1 | 0% | 1,950 | 1,592 | -18% | 0 | 0 | — |
case-20 | pass→pass | 9,825 | 14,379 | +46% | 1 | 1 | 0% | 1,607 | 2,171 | +35% | 0 | 0 | — |
case-21 | pass→pass | 4,561 | 5,335 | +17% | 1 | 1 | 0% | 525 | 1,628 | +210% | 0 | 0 | — |
case-22 | pass→pass | 4,032 | 5,578 | +38% | 1 | 1 | 0% | 532 | 1,860 | +250% | 0 | 0 | — |
DecimalAI ran this skill against gemini-3.6-flash twice over the same eval suite — once with the skill loaded and once without — and compared the two runs case by case. 22 cases were attempted, and 19 counted toward the lift figure. The other 3 produced results that are not comparable between the two arms, so they are excluded from the headline rather than averaged into it. The headline lift of +41 percentage points is the difference between those two pass rates over the 19 comparable cases. 1 case got worse with the skill loaded, and it is included in that figure.
Without the skill loaded, the model failed this case. With it loaded, the same prompt on the same model passed. This is one improved case from the latest verified run; every case, including any that regressed, is in the table above.
Other measured skills in the registry, with their headline benchmark lift.