architect
Skill44 starsChanged 7 months agoApache-2.0View on GitHub
Use when designing a new feature or system, making architecture decisions, writing technical design docs, or structuring project documentation. Triggers on "design", "architecture", "technical design", "ADR", "system decomposition", "how should I structure this", "设计方案", "架构设计", "技术方案", "文档体系", "写 User Story", "写文档". Also use when reviewing existing architecture docs or asking "where should I put this doc?
174 other projects use a version of this.
Adopted by
Most recently taken up by
- Yeachan-Heo/oh-my-claude-sisyphustheir own version, first seen Nov 8, 2026
- caidanw/skillstheir own version, first seen Nov 8, 2026
- pascalorg/editortheir own version, first seen Nov 8, 2026
- Yeachan-Heo/oh-my-claudecodetheir own version, first seen Nov 8, 2026
- naman10parikh/pennytheir own version, first seen Nov 8, 2026
- afawfawffaf/my-skillstheir own version, first seen Nov 8, 2026
Used with
Projects with it also use ecosystem-reference, fractal-delegation and 10 more.
Other files people use alongside this one.
Files found in the same public projects as a version of this one, more often than they turn up anywhere else. Each project counts once, large collections count for less, and this file's own repository is left out.
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ianclearySkillprinciple-explain-the-number
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Other versions174 projects use a version of this.
Word for word · 0
None found.
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None found.
Wrote their own version · 174
- Yeachan-Heo/oh-my-claude-sisyphus★ 41ksame name
- Yeachan-Heo/oh-my-claudecode★ 41ksame name
- pascalorg/editor★ 25ksame name
- backnotprop/pstack★ 3.8ksame name
- agenticnotetaking/arscontexta★ 3.5ksame name
- jsmastery-pro/skills★ 1.4ksame name
- SethGammon/Citadel★ 927same name
- moeru-ai/xsai★ 667same name
- DanMcInerney/architect-loop★ 626same name
- Hainrixz/the-architect★ 562same name
164 more not listed
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
In this repository24 other files it gives its agents.
- clean-cacheSkill
- code-reviewSkill
- code-submitSkill
- dev-workflowSkill
- doc-writingSkill
- embed-ci-setupSkill
- gitlab-ciSkill
- gitlab-mrSkill
- grafanaSkill
- k8s-opsSkill
- local-security-checkSkill
- mock-engineSkill
- multi-worktree-devSkill
- prometheusSkill
- security-compliance-reviewSkill
- sentry-onboardingSkill
- sentrySkill
- sre-agentSkill
- story-craftsmanSkill
- terraform-auditSkill
- testing-strategySkill
- trufflehog-cliSkill
- uat-story-writerSkill
- voc-analysisSkill
The file
Show its rules and text
We split this skill into the rules it gives an agent
22 rules. 0 are common, 17 are distinctive, and 5 are very specific to this project.
0
Common
Most of the 162 edited versions we read keep these.
17
Distinctive
This author's own choices. Worth a look.
5
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Distinctive: line 15
Socratic questioning drives design: Do not propose solutions directly — first identify architectural concerns from User Stories, then …
- Distinctive: line 17
Single file ≤ 400 lines: If exceeded, use overview.md as the entry point and split downward with layered navigation
- Very specific: line 84
After adding new User Story, update the index table in user-stories/README.md
- Distinctive: line 96
After reading Step 1's User Stories, identify the implicit architectural concerns.
- Distinctive: line 118
Do these two pieces of logic change at different frequencies?
- Distinctive: line 119
Do their failures need to be isolated?
- Distinctive: line 120
Do they have clear data ownership?
- Distinctive: line 124
If the downstream is down, should the upstream fail or continue?
- Distinctive: line 128
After this feature launches, how do we know it's successful?
- Distinctive: line 152
Idempotency: Write operations are safe for repeated calls
- Distinctive: line 155
Built-in stubs: Every external dependency has a corresponding Stub/Mock.
- Distinctive: line 165
After gathering sufficient information through questioning:
- Distinctive: line 191
Use relative paths for cross-document references.
- Very specific: line 192
Use <br/> for line breaks in Mermaid diagram nodes — \n is prohibited
- Very specific: line 204
Use make targets as the entry point for operations.
- Distinctive: line 231
After converging through questioning, produce a module design document that must include:
- Distinctive: line 233
Interface contract: Not just API path + request/response, but also error classification and idempotency description
- Very specific: line 241
When exceeding 400 lines, split: keep the overview in {service}/overview.md, move details to {service}/{topic}.md
- Very specific: line 274
Test scenario data is switched via make mock-scenario for controlled, repeatable execution
- Distinctive: line 281
Test scenarios must cover all ACs in the User Stories (verified via traceability matrix: AC → L2 case ID + L3 scenario ID)
- Distinctive: line 282
Built-in stubs are a shift-left strategy: Every external dependency has a corresponding stub.
- Distinctive: line 334
Consolidation timing: After superpowers plan is confirmed and before coding starts — consolidate documents first, then begin coding.
“Common” is measured: kept by at least 6 in 10 of the 162 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
Architect
Architect Skill — drives design decisions through Socratic questioning and produces a complete technical documentation system.
The architect's deliverables are the documentation system itself. Writing overview.md is the act of system decomposition; writing domain-model.md is the act of establishing ubiquitous language. Documentation is not a by-product of design — documentation IS the design.
Core Principles
- Documentation before code: Each step's documentation output serves as input for the next step — no skipping, no reordering
- Socratic questioning drives design: Do not propose solutions directly — first identify architectural concerns from User Stories, then converge design decisions through questioning
- User Stories are purely user-perspective: User Stories should contain only user experience and acceptance criteria — never mix in technical details
- Single file ≤ 400 lines: If exceeded, use overview.md as the entry point and split downward with layered navigation
- Terminology unification:
domain-model.mdimplements DDD Ubiquitous Language — the single source of truth (SSOT) for business term <-> technical term mapping - Superpowers outputs must be consolidated: Plans generated during a session must be written into
docs/before coding begins - Design-first approach: Documentation may describe the target state (design ahead of code is normal); however, implemented features must have corresponding documentation
Overall Workflow (must be executed in order)
1. User Story → Define user experience flows and acceptance criteria (no technical details)
2. Architecture Design → User Story pattern recognition → Socratic questioning → brainstorming divergence
→ Converge using methodology references → Output overview.md + domain-model.md + ADR
3. Dev/Test Env Design → Build feedback loops for AI Agent TDD
4. Module Detail Design→ Module-level pattern recognition → questioning → output ≤400 line module docs
5. Layered Test Plan → Generate L2-L4 plans based on User Stories + tech design + env design
(L2-L4)
6. Parallel TDD Dev → Implement in parallel using agent teams + superpowersDocumentation Directory Structure
All documentation must reside under
docs/in the project root. In the tree below,docs/is the root, and all subdirectories (product/,architecture/, etc.) are children ofdocs/. Absolute paths look like<project-root>/docs/product/prd.md. Do not create standaloneproduct/orarchitecture/directories at the project root.
docs/ # <-- The single root directory for all documentation
├── TODO.md # Documentation review tracking checklist (SSOT)
├── product/ # docs/product/ — Product layer: user perspective
│ ├── prd.md # docs/product/prd.md
│ └── user-stories/
│ ├── README.md # docs/product/user-stories/README.md
│ └── {service-or-module}.md # docs/product/user-stories/{service}.md
├── architecture/ # docs/architecture/ — Architecture layer: system design decisions
│ ├── overview.md # docs/architecture/overview.md (≤400 lines)
│ ├── domain-model.md # docs/architecture/domain-model.md — Ubiquitous Language SSOT
│ ├── tech-stack.md # docs/architecture/tech-stack.md
│ └── {service}/ # docs/architecture/{service}/
│ ├── overview.md # docs/architecture/{service}/overview.md (≤400 lines)
│ └── {topic}.md # docs/architecture/{service}/{topic}.md (≤400 lines)
├── testing/ # docs/testing/ — Testing layer: strategy and test cases
│ ├── strategy.md # docs/testing/strategy.md
│ └── services/{service}/ # docs/testing/services/{service}/
└── deployment/ # docs/deployment/ — Deployment layer: environment operations manual
├── local-dev.md
├── ci.md
└── cd.mdRules
Step 1 — User Stories (docs/product/user-stories/{service}.md)
What to write: User experience flows, Epic breakdown, verifiable acceptance criteria (AC). May include NFRs (non-functional requirements).
Strictly forbidden: Technical implementation details (no class names, API paths, database fields, or protocol details). User Stories are the user's perspective, not a technical specification.
Document structure:
- Split files by service or module (e.g.,
gateway.md,sandbox.md) — one file per service domain - Organize each file by Epic — an Epic is a business-meaningful feature cluster
- ID format:
US-{module-abbreviation}-{number}(e.g.,US-FI-01) - Each User Story: Background (Why) + User Story (Who/What/Goal) + AC (Given/When/Then format)
- NFRs in a separate section with quantifiable metrics (e.g., "p95 response < 2s") — no implementation approach
- Progress markers:
✅ Implemented/⚙️ In Progress/Not Started - After adding new User Story, update the index table in
user-stories/README.md
Companion Skill: story-craftsman (guided interviews to uncover context + standard template generation)
Step 2 — Architecture Design (docs/architecture/)
Step 2 is the architect's core work. Do not jump straight to drawing architecture diagrams after reading the User Stories — first identify the architectural concerns implied in the User Stories, converge design decisions through questioning, then commit them to documentation.
2a. User Story Pattern Recognition
After reading Step 1's User Stories, identify the implicit architectural concerns. Common User Story patterns and their architectural signals:
| Appears in User Stories... | Architecture Signal | Questioning Direction |
| Multiple tenants / OEM customers / white-label | Multi-tenancy isolation | Data isolation level, configuration variance, failure blast radius |
| Real-time / push / streaming / online status | Real-time communication | Latency tolerance, push failure strategy, concurrent connection scale |
| Scheduled / periodic / auto-execution | Scheduling system | Failure compensation vs skip, concurrent trigger mutual exclusion, timezone handling |
| Distributed update / remote management / software upgrade | Offline + eventual consistency | Offline node catch-up, interrupted upgrade recovery, canary + rollback |
| Third-party payment / external API integration | External integration | Failure isolation, retry idempotency, reconciliation mechanism |
| Audit / compliance / operation records | Audit trail | Immutability, retention period, access control |
| Orders / tickets / entity lifecycle | State machine | State definitions, transition rules, concurrent transitions, invalid transition handling |
| Cross-service coordination / multi-step process | Distributed transactions | Eventual vs strong consistency, compensation mechanism, timeout handling |
| Search / reports / data analytics | Read-write separation | Query model vs write model, data sync latency tolerance |
| Any new feature / user behavior change | Observability | How to measure success? What metrics are needed? Event tracking needed? A/B experiment validation needed? |
Not all User Stories will trigger every signal. A simple CRUD feature does not need to be questioned about distributed consistency. Only question what is relevant to the current User Story.
2b. Socratic Questioning
For each identified architectural concern, converge design decisions through questioning rather than giving direct answers. The goal is to have the user (or yourself) explicitly answer the following:
Boundary definition (corresponding to DDD Bounded Context):
- Do these two pieces of logic change at different frequencies?
- Do their failures need to be isolated? (A going down should not affect B)
- Do they have clear data ownership? (Who is the source of truth?)
Integration patterns:
- Does the caller need the result immediately? → Sync vs async
- If the downstream is down, should the upstream fail or continue? → Coupling level
- Does this operation need to be idempotent? (What happens on repeat calls?)
Observability (must question for every feature):
- After this feature launches, how do we know it's successful? → Define core metrics (conversion rate, retention, p95 latency, etc.)
- Are new tracking events needed? → User behavior events (impression/click/conversion funnel)
- Is A/B experiment validation needed? → When the approach is uncertain, use experiment data instead of guessing
- What are the SLA targets? → Quantified targets for availability, response time, error rate
- How do we detect problems? → Alert rules, dashboards, log keywords
Design constraints:
- What is the most critical non-functional requirement? (Latency? Throughput? Consistency? Availability?)
- Which are hard constraints (non-negotiable) and which are soft constraints (trade-offable)?
- What technologies is the team most experienced with? (Tech selection should consider team capability)
2c. Architecture Quality Principles
Designs must be checked against the following principles. These are also the criteria used by code-review to evaluate design quality.
Structural principles:
- High cohesion, low coupling: Clear module boundaries, each module does one thing, changes do not propagate
- Dependency direction: Stable modules do not depend on unstable modules, dependencies flow in one direction
- Vertical slicing: Organized by business domain rather than technical stack layers
- Core module separation: Core business logic is independent of frameworks and infrastructure, reusable across environments
- Ports & Adapters: Business logic is strictly isolated from external dependencies; all I/O is defined through Port interfaces, no direct dependency on concrete implementations
Robustness principles:
- Failure isolation: External dependencies going down have degradation/circuit-breaker/timeout strategies
- Idempotency: Write operations are safe for repeated calls
- Data consistency: Transaction boundaries for cross-table/cross-service operations are correct
- Input validation: User input is validated at system boundaries
- Built-in stubs: Every external dependency has a corresponding Stub/Mock; test environments do not require external services to be online
Evolvability principles:
- Extension points: Interfaces are pre-designed for known future changes
- Interface minimization: APIs expose only necessary information without leaking internal implementation
- Naming is design: Variable, function, and interface names must accurately convey intent; naming is not just about readability — it determines whether an AI Agent can correctly understand semantics
- Every rule has a Why: Documentation, comments, and commit messages explain "why," not just "what"; ADR, AC, and config items all need rationale
2d. Solution Divergence and Convergence
After gathering sufficient information through questioning:
- Invoke
superpowers:brainstormingto diverge and explore possible approaches - Reference methodology decision cards in
references/to evaluate approaches (see this skill's references/ directory) - Converge: Select an approach, record it as an ADR
ADR reasoning chain (must be included — conclusions alone are insufficient):
- Context: What problem is being faced + what constraints exist
- Options: What approaches were considered (at least 2)
- Trade-off: Pros and cons of each approach (not just the pros)
- Decision: What was chosen (or Pending — see below)
- Consequences: What costs were accepted
Pending ADR: When questions remain unanswered or information is insufficient for a decision, a Pending ADR must be created (Decision marked as Pending) rather than skipping it. A Pending ADR records the known Context and Options, and explicitly states "which questions must be answered before a decision can be made." This ensures uncertain decision points are explicitly tracked and not forgotten during subsequent design.
2e. Documentation Output
Output files:
overview.md— Architecture overview (design goals table → Mermaid architecture diagram → component responsibilities table → sub-document navigation table)domain-model.md— Ubiquitous Language SSOT (business term <-> technical term mapping, essentially implementing DDD Ubiquitous Language)- ADR records in overview.md or separate files
Documentation standards:
- Single file ≤ 400 lines — when exceeded, split into sub-documents; overview.md retains only the overview and sub-document navigation table
- Record review time using
|Document Statusat the beginning of the file - All terminology must align with
domain-model.md— consult it before writing; do not invent new concepts - Use relative paths for cross-document references; add a three-column navigation table at the top of subsystem documents (submodule | document | description)
- Use
<br/>for line breaks in Mermaid diagram nodes —\nis prohibited
Companion Skills: doc-writing (HWPR to mark human design decisions, AWOR for expanded detail), superpowers:brainstorming (solution divergence)
Step 3 — Dev/Test Environment Design (docs/deployment/local-dev.md)
What to write: L1/L2/L3 layered environment architecture, multi-worktree port isolation strategy, shared channel switching mechanism, hot-reload configuration. The goal is to build a fast-feedback TDD loop for AI Agents.
Documentation standards:
local-dev.mdhas two sections: User Guide (commands and results, for developers) + Implementation Details (design rationale, for maintainers)- Use
maketargets as the entry point for operations; bare commands are prohibited in documentation
Companion Skills:
multi-worktree-dev(L1/L2/L3 layered design, port hash offset, shared channel exclusive switching, health probing)mock-engine(Mock infrastructure: start/stop mock services, load test data, create test scenarios)
Step 4 — Module Detail Design (docs/architecture/{service}/*.md)
What to write: Internal design of a single service/module — interface contracts, data flows, state machines, key algorithms.
Like Step 2, Step 4 also requires first identifying module-level design concerns, then converging through questioning.
4a. Module-Level Pattern Recognition
| Module Characteristic | Questioning Direction |
| Exposes external APIs | Error classification (which are retryable / which are not), idempotency, versioning strategy |
| Entities with lifecycles | State definitions, transition guard conditions, concurrent transitions, invalid transition handling |
| Depends on external services | Timeout strategy, circuit-breaker thresholds, degradation plan, anti-corruption layer design |
| High-concurrency reads/writes | Lock granularity, optimistic vs pessimistic, cache consistency |
| Complex business rules | Will rules change? Configuration-driven vs hard-coded? How to handle rule conflicts? |
| User-behavior-related features | What tracking events are needed? How is the funnel defined? Is A/B experimentation needed? |
4b. Output After Questioning
After converging through questioning, produce a module design document that must include:
- Interface contract: Not just API path + request/response, but also error classification and idempotency description
- State machine (if applicable): State diagram + guard conditions + concurrency handling strategy
- Dependency direction: Who this module depends on, who depends on it, and whether the direction is correct (stable modules should not depend on unstable modules)
- Data flow: Source → transform → sink, including error/retry paths
- Observability design: Core metric definitions (SLA), new tracking events needed (event tracking), A/B experiment plan (if applicable), alert rules, dashboards
Documentation standards:
- Each file strictly ≤ 400 lines — this is a hard limit, not a suggestion
- When exceeding 400 lines, split: keep the overview in
{service}/overview.md, move details to{service}/{topic}.md - Layered nesting: system overview → service overview → module details; each layer is responsible only for its own granularity
- Each detail document references its parent service overview at the top, forming a navigable document tree
Companion Skill: doc-writing (HWPR/AWOR framework)
Step 5 — Layered Test Plan (docs/testing/)
What to write: A layered testing strategy generated from Step 1 (User Story acceptance criteria) + Step 2 (technical design) + Step 3 (environment design).
Document structure:
docs/testing/
├── strategy.md # Overview (≤400 lines): layer table, layering logic, mock architecture, traceability matrix, CI/CD
└── scenarios/ # AC-level scenario matrices (strategy.md should not contain individual test cases)
├── ep1-<epic>.md # By Epic (product/QA perspective)
├── tech-<module>.md # By technical module (developer perspective)
└── tech-nfr.md # NFR degradation/fault tolerancestrategy.md must include:
- 10-column test layer overview table (layer / case count / test goal / real dependencies / mock dependencies / real infra / mock infra / execution timing / duration / code location)
- Layering logic table (what problem each layer solves + why the layer above is insufficient)
- Mock infrastructure SSOT (directory structure + mock/real switching strategy per layer)
- Requirements traceability matrix (User Story → test case IDs per layer)
- Quality gate table (gate / checkpoint / criteria)
Scenario file AC-level traceability table: Fixed 8-column format AC Scenario | Smoke | L1 | L2-1 | L2-2 | L3-1 | L3-2 | L4, each cell filled with specific test case IDs.
Key principles:
- L3/L4 are black-box tests — test clients interact directly with the user interface; intercepting or mocking internal components at intermediate layers is prohibited
- Test scenario data is switched via
make mock-scenariofor controlled, repeatable execution
Quality standards (also the criteria used by code-review for evaluating tests; see testing-strategy skill for detailed layered strategy):
- Code without E2E tests must not merge to trunk — treated as a defect, not a "to-do"
- Each implemented User Story AC must have L3 E2E test coverage (AC describes user behavior and must be verified end-to-end; L3 uses real dependencies, not stubs)
- Each implemented API handler must have at least L2 integration tests (verifying interface contracts and data correctness)
- State changes, deletions, corrections, and other core flows must have boundary scenario coverage
- Test scenarios must cover all ACs in the User Stories (verified via traceability matrix: AC → L2 case ID + L3 scenario ID)
- Built-in stubs are a shift-left strategy: Every external dependency has a corresponding stub; L1/L2 do not require external services to be online. However, L3 E2E must use real dependencies to verify the complete chain
Companion Skills:
testing-strategy(generate complete layered strategy by project type, includesreferences/engagement-example.mdreal-world example)mock-engine(mock infrastructure management: L1/L2 stub/mock service startup, test scenario data loading)multi-worktree-dev(test parallel safety design — multiple worktrees do not contend for shared channels)
Step 6 — CI/CD Deployment Documentation (docs/deployment/ci.md + cd.md)
What to write: CI pipeline quality gates, CD deployment strategy, K8s resource configuration, Ingress routing, secrets management.
Companion Skills:
| Task | Skill |
Write/review .gitlab-ci.yml | gitlab-ci |
| Full deployment workflow for new apps (CI + K8s + Ingress + Vault + Crossplane) | cicd-developer |
| ArgoCD GitOps sync/rollback/troubleshooting | argocd |
| Set up CICD component stack for new clusters | argocd-deploy |
| View/troubleshoot K8s cluster resources | k8s-ops |
| Image registry Robot Account | harbor |
| Vault secrets management | vault-kv-manager |
| Runner selection and troubleshooting | gitlab-instance-runners |
| Embedded repo CI Pipeline | embed-ci-setup |
| Jenkins pipeline management | jenkins |
Cross-Document Maintenance Rules
| Operation | Must Also Update |
| Add/delete/rename document | docs/TODO.md |
| Add User Story | user-stories/README.md index table |
| Change architecture component responsibilities | architecture/overview.md mapping table |
| Add domain terminology | architecture/domain-model.md |
| Document + code changed together | Put in the same MR (use gitlab-mr skill) |
Superpowers Output Consolidation Rules
superpowers:writing-plans, superpowers:brainstorming, and other skills generate design documents or plans during a session. These documents must be consolidated into the docs/ system — they cannot exist only in session context or temporary files:
| Superpowers Output | Consolidation Target |
| Feature plan / brainstorm conclusions | Corresponding Epic in docs/product/user-stories/{service}.md |
| Overall technical plan / writing-plans output | docs/architecture/overview.md or corresponding service overview |
| Module implementation plan | docs/architecture/{service}/{topic}.md |
| Test plan | docs/testing/strategy.md or services/{service}/ |
| Dev environment design | docs/deployment/local-dev.md |
Consolidation timing: After superpowers plan is confirmed and before coding starts — consolidate documents first, then begin coding.
Documentation Review (docs/TODO.md)
TODO.md tracks all items pending review using three states: [ ] To Do / [/] In Progress / [x] Done
Review focus areas:
- Whether any file exceeds 400 lines (split if so)
- Whether terminology is consistent with
domain-model.md(business term <-> technical term mapping) - Whether User Stories contain technical details
- Whether cross-document reference paths are correct
- Whether User Story status is synchronized with code implementation
- Whether Product / Architecture interpretations of Phase breakdown are aligned
- Whether ADR includes a complete reasoning chain (Context → Options → Trade-off → Decision → Consequences)
Skill Toolchain Quick Reference
| Step | Task | Skill to Use |
| Step 1 | Write User Stories | story-craftsman |
| Step 2 | Architecture design: solution divergence | superpowers:brainstorming |
| Step 2 | Architecture design: write documentation | doc-writing |
| Step 3 | Design dev/test environment layering | multi-worktree-dev |
| Step 4 | Module detail design | doc-writing |
| Step 5 | Generate layered test plan | testing-strategy + multi-worktree-dev |
| Step 6 | CI Pipeline configuration | gitlab-ci / embed-ci-setup / jenkins |
| Step 6 | CD full deployment workflow | cicd-developer |
| Step 6 | K8s / images / secrets | k8s-ops + vault-kv-manager |
| Throughout | Event tracking definition and management | event tracking platform |
| Throughout | A/B experiments / Feature Flags | A/B experiment platform |
| Throughout | SLA metric configuration | sla-metric |
| Throughout | Monitoring dashboards / alerts | grafana + prometheus |
| Throughout | Error monitoring | sentry + sentry-onboarding |
| Throughout | Submit documentation + code together as MR | gitlab-mr |
| Throughout | R&D process orchestration | dev-workflow |
| Throughout | Create or update the Skill itself | superpowers:writing-skills |
Methodology References (references/)
The questioning and solution evaluation in Steps 2/4 can reference the following methodology decision cards. Each card answers only three questions: when to use it, core concepts quick reference, and when NOT to use it.
The AI agent already has sufficient knowledge of these methodologies — the value of the decision cards is helping determine "should I use this for the current scenario."
| Decision Card | Applicable Signals |
references/ddd.md | Confused business terminology, unclear service boundaries, multi-team collaboration |
references/event-driven.md | Async processing, cross-service coordination, state change notifications |
references/hexagonal.md | Multiple external integrations, need for testability, preventing framework lock-in |
references/state-machine.md | Entities with lifecycles, complex state transition rules |
references/integration-patterns.md | Third-party API integration, unreliable external systems |
references/multi-tenant.md | OEM / white-label / multi-tenant scenarios |
Example Comparisons
Bad — Jumping to architecture diagram immediately after reading User Stories
Read User Stories → Directly write overview.md and draw Mermaid diagrams
→ No questioning, service boundaries drawn by intuition, ADR has no reasoning chainGood — Pattern recognition → questioning → brainstorming → convergence
Read User Story → Identify "multi-tenant + distributed update" signals
→ Question: What level of data isolation between tenants? What's the catch-up strategy for offline nodes?
→ Brainstorm 3 approaches
→ Reference DDD + multi-tenant decision cards to evaluate
→ Select approach, write ADR (with complete reasoning chain)
→ Output overview.md + domain-model.mdBad — User Story contains technical details
## US-GW-01 Message Routing
After a user sends a message, the Gateway calls the `resolve_intent()` method through
IntentResolveMiddleware, queries the PostgreSQL workspace table to get the agent_id,
then distributes it to the corresponding Sandbox Pod via Redis Pub/Sub.Problem: AC should describe the results the user sees, not class names, databases, or middleware.
Good — User Story from purely user perspective
## US-GW-01 Message Routing
**Background**: Users need to maintain independent Agent context across different group chats.
**User Story**: As a team member, I want each group chat to have its own Agent context
so that the Agent remembers each group's context independently without cross-contamination.
**AC**:
- Given the user has had conversations in both Group A and Group B
- When the user asks a question in Group A
- Then the Agent responds based only on Group A's history, without mixing in Group B's contentBad — Single file exceeds 400 lines with no splitting
docs/architecture/gateway.md (800 lines, containing all subsystem details)Good — Overview with navigation + layered sub-documents
docs/architecture/gateway/
├── overview.md (≤400 lines, architecture diagram + sub-document navigation table)
├── intent-resolve.md (≤400 lines)
├── thread-lane.md (≤400 lines)
└── feishu-card.md (≤400 lines)Bad — Superpowers output stays in the session
After brainstorming is complete, directly say "ok, let's start coding"
→ Plan exists only in session context, lost in next session, cannot serve as test baselineGood — Consolidate plan into docs/ before coding
Brainstorming complete → Write into docs/architecture/overview.md → commit → start codingDoes it work?
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Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.
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