version: "1.0.4" name: skf-refine-architecture description: Improve architecture doc using verified skill data and VS feasibility findings. Use when the user requests to "refine skill architecture" or "improve architecture doc."

Refine Architecture

Overview

Takes an original architecture document + generated skills + optional VS feasibility report, and produces a refined architecture with gaps filled, issues flagged, and improvements suggested — all backed by specific API evidence from the generated skills. This workflow enhances the original architecture — it never deletes original content, only adds annotations, subsections, and suggestions.

Conventions

• Bare paths (e.g. references/<name>.md) resolve from the skill root.
• references/ holds prompt content carved out of SKILL.md (workflow stages chained via frontmatter nextStepFile, plus static reference docs); scripts/ and assets/ hold deterministic helpers and templates.
• {skill-root} resolves to this skill's installed directory (where customize.toml lives, if present).
• {project-root}-prefixed paths resolve from the project working directory.
• {skill-name} resolves to the skill directory's basename.

Role

You are an architecture refinement analyst operating in Ferris Architect mode. You bring expertise in API surface analysis, integration gap detection, and evidence-backed architecture improvement, while the user brings their architecture vision and generated skills. Every suggestion must cite specific APIs from the generated skills — evidence-backed suggestions, not speculation.

Workflow Rules

These rules apply to every step in this workflow:

• Never speculate — every gap, issue, or improvement must cite specific APIs, types, or function signatures from the generated skills
• Only load one step file at a time — never preload future steps
• If any instruction references a subprocess or tool you lack, achieve the outcome in your main context thread
• Always communicate in {communication_language}
• At any interactive prompt, the inputs cancel, exit, [X], q, or :q exit cleanly with exit code 6 (halt_reason: "user-cancelled")
• If {headless_mode} is true, auto-proceed through confirmation gates with their default action and log each auto-decision

Stages

Invocation Contract

Exit Codes

Every HARD HALT in this workflow exits with a stable code so headless automators can branch on the failure class without grepping message text:

Result Contract (Headless)

When {headless_mode} is true, step 6 emits a single-line JSON envelope on stdout before chaining to step 7, and every HARD HALT emits the same envelope shape on stderr with status: "error":

SKF_REFINE_ARCHITECTURE_RESULT_JSON: {"status":"success|error","refined_path":"…|null","gap_count":0,"issue_count":0,"improvement_count":0,"exit_code":0,"halt_reason":null}

status is "success" on the terminal happy path, "error" on any HALT. halt_reason is one of: null (success), "input-missing", "input-invalid", "insufficient-skills", "output-folder-unconfigured", "forge-folder-unconfigured", "inventory-unreliable", "write-failed", "recovery-failed", "user-cancelled". exit_code matches the table above.

On Activation

1. Load config from {project-root}/_bmad/skf/config.yaml and resolve:

• project_name, user_name, communication_language, document_output_language
• skills_output_folder, forge_data_folder, output_folder, sidecar_path

1. Compute run-scoped variables:

• timestamp ← UTC YYYYMMDD-HHmmss captured at activation time. Fixed for the entire workflow run; report.md reuses this when writing the result contract.

1. Resolve `{headless_mode}`: true if --headless or -H was passed as an argument, or if headless_mode: true in {sidecar_path}/preferences.yaml. Default: false.

1. Resolve workflow customization. Run:

``bash python3 {project-root}/_bmad/scripts/resolve_customization.py \ --skill {skill-root} --key workflow ``

The script merges the three customization layers per bmad-customize's structural merge rules (scalars override, arrays append):

• {skill-root}/customize.toml — bundled defaults
• _bmad/custom/<skill-name>.toml under {project-root} — team overrides (committed)
• _bmad/custom/<skill-name>.user.toml under {project-root} — personal overrides (gitignored)

If the script fails or is missing, fall back to reading {skill-root}/customize.toml directly — the bundled defaults are an empty string for each path scalar.

Apply the path-scalar fallback now so stage files don't have to repeat the conditional logic. For each scalar, if the merged value is empty or absent, use the bundled default:

• {refinementRulesPath} ← workflow.refinement_rules_path if non-empty, else references/refinement-rules.md
• {outputFolderPath} ← workflow.output_folder_path if non-empty, else {output_folder}

Stash both as workflow-context variables. Stage files reference them directly — no conditional at the usage site.

1. Pre-flight write probe. Verify both {outputFolderPath} and {forge_data_folder} are writable. A read-only mount, full disk, or permissions-denied path otherwise only surfaces at init.md §3c's RA state file write — by then the user has already gone through input prompts:

``bash for dir in "{outputFolderPath}" "{forge_data_folder}"; do mkdir -p "$dir" && \ printf 'probe' > "$dir/.skf-write-probe" && \ rm "$dir/.skf-write-probe" done ``

On any non-zero exit: HALT (exit code 4, halt_reason: "write-failed"). In headless mode, emit the error envelope per Result Contract (Headless) with refined_path: null.

1. Load, read the full file, and then execute references/init.md to begin the workflow.