Route full software-development architecture work from product intent through design, implementation, testing, release, and operations. Use when the user asks for a complete development architecture, wants to know which Spellbook skills to combine, needs an execution path across PRD/spec/API/data/security/performance/release/SRE, or asks to turn an idea or repo into a production-ready engineering plan.
npx skills add https://github.com/majiayu000/spellbook --skill dev-architecture-playbook
Use this as the lifecycle router before starting broad product or architecture work. It chooses the minimum useful skill chain, defines gates, and prevents starting implementation before the required contracts exist.
Classify the request first:
| Request | Primary Skills | Output |
|---|---|---|
| Idea, product direction, or market/user problem | product-discovery, prd-master | Product brief, user stories, success metrics |
| Architecture or module boundaries | architecture-foundation, technical-spec, elegant-architecture | Architecture spec, boundaries, rejected alternatives |
| API, auth, data, or schema contract | api-design, auth-security, database-patterns, data-contract-migrations | Versioned contracts and migration plan |
| UI/product surface | frontend-design, ui-ux-pro-max, ui-design-system, playwright-automation | UX flow, component plan, visual checks |
| Implementation workflow | flowguard, threads, systematic-debugging, comprehensive-testing | Bounded execution, ownership, root-cause debugging, and verification |
| Quality and regression risk | comprehensive-testing, codebase-audit, vibeguard, project-health-auditor | Test matrix and risk list |
| Release and operations | release-engineering, config-secrets-environments, performance-capacity, incident-slo-runbook, observability-sre, devops-excellence | Rollout, config, capacity, SLO, runbook |
Do not treat the architecture as complete until these gates are explicit:
If a gate is irrelevant, state why. Do not silently skip data, security, or rollback gates for production systems.
Use this sequence for greenfield or major refactors:
For existing repos, start with repo-agent-context-audit or codebase-audit before proposing new structure.
Return a compact plan:
goal:
context:
selected_skill_chain:
architecture_gates:
implementation_steps:
verification_commands:
release_and_ops_gates:
open_risks:
Prefer the smallest chain that covers the risk. Too many skills at once usually means the scope needs to be split.
Toolkit for interacting with and testing local web applications using Playwright. Supports verifying frontend functionality, debugging UI behavior, capturing browser screenshots, and viewing browser logs.
Use when implementation is complete, all tests pass, and you need to decide how to integrate the work - guides completion of development work by presenting structured options for merge, PR, or cleanup
Use when implementing any feature or bugfix, before writing implementation code
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes
Use when about to claim work is complete, fixed, or passing, before committing or creating PRs - requires running verification commands and confirming output before making any success claims; evidence before assertions always
Expert guidance for systematic backtesting of trading strategies. Use when developing, testing, stress-testing, or validating quantitative trading strategies. Covers "beating ideas to death" methodology, parameter robustness testing, slippage modeling, bias prevention, and interpreting backtest results. Applicable when user asks about backtesting, strategy validation, robustness testing, avoiding overfitting, or systematic trading development.
Cloud laboratory platform for automated protein testing and validation. Use when designing proteins and needing experimental validation including binding assays, expression testing, thermostability measurements, enzyme activity assays, or protein sequence optimization. Also use for submitting experiments via API, tracking experiment status, downloading results, optimizing protein sequences for better expression using computational tools (NetSolP, SoluProt, SolubleMPNN, ESM), or managing protein design workflows with wet-lab validation.
This skill should be used for time series machine learning tasks including classification, regression, clustering, forecasting, anomaly detection, segmentation, and similarity search. Use when working with temporal data, sequential patterns, or time-indexed observations requiring specialized algorithms beyond standard ML approaches. Particularly suited for univariate and multivariate time series analysis with scikit-learn compatible APIs.
Take majiayu000/dev-architecture-playbook from the repository into ~/.claude/skills for personal
use, or into .claude/skills inside a project.
The agent identifies a skill by the name field in its header. Two skills with the
same name cannot sit side by side — one of them will be ignored.