Automates the architecture pipeline phases in dependency order from investigation to report.

Install

mkdir -p .claude/skills/pipeline-wfukatsu && curl -L -o skill.zip "https://agentskills.codes/api/skills/download/16273" && unzip -o skill.zip -d .claude/skills/pipeline-wfukatsu && rm skill.zip

Installs to .claude/skills/pipeline-wfukatsu

Activation

This is the description your AI agent reads to decide when to run this skill — the better it matches your request, the more reliably it fires.

Automated pipeline that executes all phases in dependency order. /architect:pipeline [target_path]. Supports --skip-*, --resume-from, --rerun-from, --lang flags.
161 charsno explicit “when” trigger
Intermediate

Key capabilities

  • →Execute architectural analysis phases in dependency order
  • →Generate consolidated HTML reports
  • →Handle product handoff detection for existing artifacts
  • →Manage context between phases for long pipelines
  • →Skip or resume execution from specific phases
  • →Support conditional execution of skills based on project conditions

How it works

The pipeline loads a dependency graph, initializes output directories, and executes each skill in order, verifying its output before proceeding. It records progress and accumulates findings between phases.

Inputs & outputs

You give it
A target project path and a skill-dependencies.yaml file
You get back
Reports under reports/ and a completed pipeline-progress.json

When to use pipeline

  • →Running automated architecture analysis
  • →Executing multi-phase design pipelines
  • →Generating system design reports

About this skill

Full Pipeline Execution

Expected Outcome

Complete the core architecture analysis and design pipeline for the target project: investigation through evaluation, redesign, target architecture, data/API design, the 5-perspective review, and the consolidated HTML report. The final deliverables are the reports under reports/ produced by the phases in the dependency manifest.

Available Skills

The pipeline executes the phases defined in @skills/common/skill-dependencies.yaml in dependency order. Skills outside the manifest (infrastructure, security, observability, disaster recovery, implementation specs, test specs, code generation, cost estimation) are a manual extension tier: run them individually after the pipeline completes, or via /architect:start, which can sequence them interactively. They are intentionally not part of the automated run.

Execution Strategy

  1. Load the dependency graph from skill-dependencies.yaml
  2. Initialize output directories with /architect:init-output
  3. Product handoff detection — glob the same set define-requirements ingests: reports/00_core/, reports/01_ux/, reports/02_spec/, reports/03_domain/, reports/04_quality/ and work/traceability.json. Keep the two sets identical — a run that stopped early (--profile=mvp writes only reports/00_core/) is still a handoff. Match files, not directories: /product:init-output creates reports/01_ux/domain-stories/ and reports/02_spec/ui-mocks/ empty, so a directory test passes on any initialized product project. If product artifacts exist, run define-requirements first with them as inputs (the product→architect handoff, @docs/design.md §1); it auto-detects and carries product IDs forward. Otherwise run the standard greenfield/legacy entry.
  4. Execute each skill and verify its output before proceeding to the next
  5. Execute skills with parallel_with in parallel via Task
  6. Enable or disable conditional skills based on the conditions field: ScalarDB/data-layer from scalardb_enabled, and design-graphql directly from GraphQL/hybrid surfaces in canonical reports/03_design/api-style-decisions.json. Before that artifact exists, a legacy options.api_style_graphql is only a compatibility fallback. Invalid canonical JSON is a blocking error and must never be interpreted as REST-only.
  7. Phases the manifest marks optional: true may be skipped without failing the run. Three of them are dialogue-driven (create-domain-story, design-aggregate, design-state-machine) and an automated run has nobody to facilitate with: invoke those with --auto and record what that mode had to assume. analyze-ui and evaluate-ux run with --auto too, and evaluate-ux never with --base-url: an automated run evaluates the UI statically. When the inputs show no evidence for an optional phase — no domain to narrate, no invariant spanning more than one attribute (nothing to make an aggregate of), no aggregate with a lifecycle, no data model to analyze, no presentation layer (the technology stack reports none and no templates or routed views exist), no UI inventory to evaluate — record it skipped with the reason in summary rather than emitting a document derived from nothing. An optional phase that was skipped or never ran does not block its dependents: design-state-machine depends on design-aggregate for ordering, not for existence, and runs from redesign alone when there is no aggregate manifest (the dashboard applies the same rule).
  8. Record progress in work/pipeline-progress.json twice per phase: set status: "in_progress" with plugin: "architect" and started_at before invoking the skill (all of them at once for a parallel group), then completed / failed / skipped with completed_at, outputs and summary once it returns. The pre-write is the only signal that a phase is running while it runs — /architect:report-status renders it, and the token-usage hook attributes cost to whatever is in_progress, using plugin to keep the two pipelines' spend separable under the four phase names both manifests define. The product pipeline writes this same file, so never re-register or reset an entry that is not this manifest's — including under --rerun-from (@skills/common/progress-registry.md § One Registry, Two Pipelines)
  9. Accumulate findings in work/context.md between phases

Command-Line Options

  • --skip-{phase}: Skip the specified phase
  • --resume-from=phase-N: Resume from the specified phase (completed phases are skipped)
  • --rerun-from=phase-N: Reset all phases from the specified phase onward to "pending" and re-execute
  • --analyze-only: Execute analysis phases only
  • --no-scalardb: Skip all ScalarDB-related skills
  • --lang=en|ja: Set the output language (default: en). Stored in pipeline-progress.json options.output_language

Error Handling

  • Missing required prerequisite files: Log the error and automatically skip downstream phases
  • Skill execution failure: Record status: "failed" in pipeline-progress.json
  • Dependency phase failure (status: "failed"): Automatically skip downstream phases

Conditional Dependency Resolution

A phase listed in another phase's depends_on may be marked status: "skipped" because its conditions: did not match the current project (e.g. review-data-integrity when scalardb_enabled is true). When resolving depends_on:

  • Treat conditional skipped dependencies as satisfied (filter them out).
  • Only failed dependencies cascade as downstream skips.
  • This is what enables review-synthesizer to run after exactly one of review-scalardb / review-data-integrity (the other is conditionally skipped).

Context Management

Long pipelines may exceed context window limits. Update work/context.md upon each phase completion and read it at the start of the next phase.

work/context.md structure:
- Investigation results summary
- Domain knowledge extracted from analysis
- Evaluation scores and improvement priorities
- Important decisions made during design
- Open Questions (`OQ-` ID, status, owner) — carried across phases; the phase that needs an answer
  re-asks it and updates the entry in place (@rules/open-questions.md)

Progress Registry

Conforms to the schema defined in @skills/common/progress-registry.md.

Completion Criteria

  1. All phases are either completed or skipped
  2. reports/00_summary/full-report.html has been generated
  3. pipeline-progress.json status is "completed"

Related Skills

SkillRelationship
/architectInteractive version
/architect:init-outputInitialization
/architect:reportFinal report
/product:startUpstream — product reports are detected at step 3 and handed off via define-requirements (@docs/design.md §1)

When not to use it

  • →When needing to run infrastructure, security, or observability skills
  • →When requiring implementation specs or code generation
  • →When cost estimation is the primary goal

Limitations

  • →Does not automatically include infrastructure, security, or observability skills
  • →Does not include implementation specs, test specs, or code generation skills
  • →Does not perform cost estimation

How it compares

This pipeline automates the execution of a predefined sequence of architectural analysis phases, unlike manually running each phase individually.

Compared to similar skills

pipeline side by side with the closest alternatives in the catalog.

SkillInstallsUpdatedSafetyDifficulty
pipeline (this skill)03moNo flagsIntermediate
value-stream-mapping08moNo flagsIntermediate
itil-expert05moNo flagsAdvanced
babysitter:assimilate07moNo flagsAdvanced

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