amadeus

Diagnose and operate the active Intent's GitHub mirror through the guarded lifecycle and repair commands.

Diagnose and operate the active Intent's GitHub mirror through the guarded lifecycle and repair commands.

AI-DLC workflow orchestrator. Start, resume, or manage an AI-driven development lifecycle. Scopes are defined one file per scope under `.codex/scopes/`; run `bun .codex/tools/amadeus-utility.ts help` for the authoritative list and descriptions. Utilities: --status, --doctor, --migrate [path], --stage, --phase, --scope, --depth, --test-strategy, --version, --help, plus the intent and space verbs. Or describe what you want to build and the scope will be auto-detected.

Run a team election through the amadeus-election CLI's typed directive loop. Use when the user or team workflow asks to open, drive, or complete an election. The CLI is the single source of the election protocol: this skill only forwards what each directive names and hands every judgement point to a human. Do not use for ad-hoc polls outside the elections store, and do not answer election-procedure questions from this skill — the CLI's directives are the only procedure.

Run a team election through the amadeus-election CLI's typed directive loop. Use when the user or team workflow asks to open, drive, or complete an election. The CLI is the single source of the election protocol: this skill only forwards what each directive names and hands every judgement point to a human. Do not use for ad-hoc polls outside the elections store, and do not answer election-procedure questions from this skill — the CLI's directives are the only procedure.

Run a team election through the amadeus-election CLI's typed directive loop. Use when the user or team workflow asks to open, drive, or complete an election. The CLI is the single source of the election protocol: this skill only forwards what each directive names and hands every judgement point to a human. Do not use for ad-hoc polls outside the elections store, and do not answer election-procedure questions from this skill — the CLI's directives are the only procedure.

AI-DLC workflow orchestrator. Start, resume, or manage an AI-driven development lifecycle. Scopes are defined one file per scope under `.claude/scopes/`; run `bun .claude/tools/amadeus-utility.ts help` for the authoritative list and descriptions. Utilities: --status, --doctor, --migrate [path], --stage, --phase, --scope, --depth, --test-strategy, --version, --help, plus the intent and space verbs. Or describe what you want to build and the scope will be auto-detected.

AI-DLC workflow orchestrator. Start, resume, or manage an AI-driven development lifecycle. Scopes are defined one file per scope under `.kiro/scopes/`; run `bun .kiro/tools/amadeus-utility.ts help` for the authoritative list and descriptions. Utilities: --status, --doctor, --migrate [path], --stage, --phase, --scope, --depth, --test-strategy, --version, --help, plus the intent and space verbs. Or describe what you want to build and the scope will be auto-detected.

AI-DLC workflow orchestrator. Start, resume, or manage an AI-driven development lifecycle. Scopes are defined one file per scope under `.kiro/scopes/`; run `bun .kiro/tools/amadeus-utility.ts help` for the authoritative list and descriptions. Utilities: --status, --doctor, --migrate [path], --stage, --phase, --scope, --depth, --test-strategy, --version, --help, plus the intent and space verbs. Or describe what you want to build and the scope will be auto-detected.

Read-only grilling interview. Relentlessly interviews you about a plan, design, or file — one question at a time, each with a recommended answer — until you and the agent reach a shared understanding. Facts are looked up in the codebase; only decisions are put to you. Use when you want to stress-test a plan or design before building. Never advances the workflow stage pointer, never emits audit events, never writes files unless you explicitly ask for the summary to be saved.

Generate a comprehensive handover document at workflow close so the team can own, operate, and continue the system without re-running the workflow. Stage/phase/learning counts come from `amadeus-runtime.ts summary`; prose comes from the artefacts. Writes OUTCOMES.md but never mutates workflow state or emits audit events.

Print a structured session narrative for stakeholders who weren't in the room. Numbers (stage counts, phase rollup, duration) come from `amadeus-runtime.ts summary`; prose comes from the audit trail and artefacts. Renders to the terminal only — writes no file, never mutates workflow state, never emits audit events.

Read-only session cost view. Prints deterministic aggregates for the current workflow — duration, stage outcomes, memory entries, sensor firings, learnings captured — sourced entirely from `amadeus-runtime.ts summary`. Never mutates workflow state, never emits audit events, never writes files.

Analyze and plan synchronization of this Amadeus repository with official awslabs/aidlc-workflows v2 tags. Use when the user explicitly invokes this skill or clearly asks to compare, follow, port, adopt, or sync upstream AI-DLC v2 changes into Amadeus. Produce an evidence-backed ADOPT/ADAPT/SKIP plan and hand the approved report to a new Amadeus Intent. Do not use for migrating user workspaces from aidlc to amadeus, ordinary framework feature work, generic release/version synchronization, or casual upstream questions.

Analyze and plan synchronization of this Amadeus repository with official awslabs/aidlc-workflows v2 tags. Use when the user explicitly invokes this skill or clearly asks to compare, follow, port, adopt, or sync upstream AI-DLC v2 changes into Amadeus. Produce an evidence-backed ADOPT/ADAPT/SKIP plan and hand the approved report to a new Amadeus Intent. Do not use for migrating user workspaces from aidlc to amadeus, ordinary framework feature work, generic release/version synchronization, or casual upstream questions.

Use when a TypeScript project adopts the class-free, functional domain modeling style: type-alias contracts instead of interface, factory functions with closure state instead of class, companion objects via type+namespace declaration merging, branded types with smart constructors, and discriminated-union Result/error values instead of exception class hierarchies. Trigger for class-free TypeScript, companion object pattern, branded types, smart constructors, or Result-based error handling design.

Use when designing or reviewing domain-model accessors that expose internal state for persistence, serialization, tests, or framework integration. Applies the breachEncapsulationOf naming pattern so unavoidable getters are visibly treated as encapsulation breaches, not casual domain APIs. Trigger for getter naming conventions, persistence-only getters, serialization accessors, Tell Don't Ask pressure, or requests to prevent getter misuse.

Use only when the user explicitly asks for Clean Architecture design, implementation, or review. Applies a domain, use case, interface adapter, and infrastructure layer model, with persistence and RPC adapters outside the domain and use-case rules. Do not trigger for generic architecture advice, hexagonal architecture, onion architecture, or ordinary design review unless Clean Architecture is named.

Use when CQRS changes aggregate boundaries or state shape. Helps reduce oversized command aggregates by moving read concerns to read models, keeping only command-decision state in aggregates, and using events for state transitions. Trigger for large aggregates, heavy command updates, aggregates containing query-only data, or boundary redesign during CQRS adoption.

Use when explaining why CQRS often needs event sourcing or durable events for reliable command-to-query synchronization. Covers calculated value sync, database trigger limits, polling scalability, double commits, and making events the source of truth. Trigger for CQRS synchronization, read-model update strategy, CQRS without ES, or double-commit concerns.

Use when evaluating whether CQRS is worth adopting, especially tradeoffs among consistency, availability, scalability, operational complexity, and event sourcing. Trigger for read/write separation decisions, eventual consistency concerns, CQRS architecture review, or choosing between a unified model and CQRS.

Use for DDD aggregate design, implementation, refactoring, or review. Covers aggregate boundaries, aggregate roots, true invariants, immutable updates, ID references, eventual consistency, domain events, and Evans/Vernon aggregate rules. Trigger for aggregate boundary questions, aggregate roots, entity design inside aggregates, large aggregates, mutable aggregate code, public fields, direct child mutation, or cross-aggregate coordination.

Use when reviewing or designing transaction boundaries that touch DDD aggregates. Detects the anti-pattern of updating multiple aggregates in one transaction and replaces it with one-aggregate transactions plus eventual consistency, domain events, sagas, or process managers. Trigger for cross-aggregate transactions, `@Transactional` use cases, one transaction one aggregate, or aggregate consistency coordination.

Use when a use case wants to check another aggregate's state before changing the current aggregate. Helps separate true invariants from policies, detect Saga misuse, reason about CQRS/Event Sourcing lookup limits, and decide whether inconsistent data is acceptable. Trigger for cross-aggregate validation, checking another aggregate, command-side read-model access, reverse lookup constraints, or Saga-based validation.

Use for choosing and applying DDD building blocks: value objects, entities, aggregates, domain services, repositories, factories, and domain events. Trigger for domain modeling, entity versus value object decisions, aggregate boundaries, domain service placement, or implementing a domain model from requirements.

Use when analyzing existing non-DDD or legacy code to propose DDD domain models with aggregates, local entities, value objects, domain services, invariants, and pseudocode. Trigger for extracting a domain model from code, redesigning legacy code with DDD, finding aggregates, or proposing domain boundaries from an existing implementation.

Use when planning a DDD implementation flow that starts from the domain model and tests before infrastructure. Covers test-first domain modeling, in-memory repositories, use cases, and delaying persistence/framework choices. Trigger for starting from the domain model, TDD with DDD, in-memory repository design, use-case tests, or DDD development process.

Use when replacing raw primitive values with validated domain primitives or value objects so invalid domain states cannot be represented. Covers always-valid construction, smart constructors, parse-don't-validate, and avoiding primitive obsession. Trigger for domain primitive design, validated IDs, email/money/range types, always-valid models, or preventing invalid states.

Use when designing DDD module boundaries, package layout, bounded-context internals, or language-specific module organization. Helps keep domain concepts cohesive while exposing narrow APIs and hiding implementation details. Trigger for DDD modules, package-by-domain, bounded context internals, module visibility, or organizing aggregates and value objects.

Use when designing or reviewing repositories in DDD. Treats repositories as collection-like access to aggregate roots, not generic DAO layers, and separates query/read-model concerns from command persistence. Trigger for repository interfaces, aggregate persistence, save/load semantics, query placement, ORM leakage, or repository anti-patterns.

Use when deciding where repository interfaces and implementations belong in layered, Clean Architecture, or DDD projects. Emphasizes that aggregates should not depend on repositories and that application/use-case layers own repository orchestration. Trigger for repository-in-domain questions, repository package placement, or aggregates calling repositories.

Use when deciding whether a primitive value should become a domain-specific type or value object. Balances primitive obsession against value-object obsession using risk, invariants, behavior, and cost. Trigger for wrapping strings/ints/UUIDs, value object decisions, too many tiny types, or whether a primitive is good enough.

Use when clarifying software abnormal-state terminology such as error, defect, fault, failure, bug, incident, and exception. Helps choose handling, testing, and mitigation strategies from precise classification. Trigger for error terminology, fault versus failure, defect versus bug, abnormal-state design, failure analysis, or test classification.

Use when designing or reviewing error handling across domain logic, application services, and infrastructure. Uses recoverability to choose typed errors, Result/Either, exceptions, retries, and logging. Trigger for improving error handling, Result types, exception design, recoverable errors, domain errors, or error-handling refactors.

Use when wrapping collections in a domain-specific class to centralize collection rules, invariants, and behavior. Trigger for scattered list logic, collection wrappers, raw Order lists becoming `Orders`, enforcing collection invariants, or reviewing collection-heavy domain code.

Use when deciding whether similar code should be deduplicated. Prioritizes shared intent and change reason over textual similarity, avoiding harmful DRY abstractions when code looks alike but changes for different reasons. Trigger for duplicate code, DRY decisions, merging functions, common helpers, or refactoring similar implementations.

Use when reviewing or refactoring object coupling caused by train-wreck call chains and knowledge of nested internals. Applies the Law of Demeter / Principle of Least Knowledge to move behavior closer to the owning object. Trigger for chained calls, dot chains, train wrecks, high coupling, Feature Envy, or reducing object navigation.

Use when redesigning package or module structure for messy codebases, large modules, dependency problems, or new project structure. Applies information hiding, change reasons, dependency direction, and release boundaries. Trigger for package structure review, module dependencies, file placement, circular dependency cleanup, or module hierarchy design.

Use when replacing validation that discards information with parsing that returns a typed, validated value. Helps enforce invariants through the type system and reduce shotgun parsing. Trigger for validation refactors, type-safe inputs, invalid-state prevention, reducing `Maybe`/nullable checks, or converting validators into constructors/parsers.

Use only for Scala 3 implementations of CQRS/Event Sourcing with Apache Pekko. Covers aggregate actors, PersistenceEffector-style command handling, domain-model separation, typed state transitions, event design, Protocol Buffers serialization, ZIO use cases, and read-model updaters. Do not trigger for non-Scala stacks or conceptual CQRS questions without Pekko/Scala implementation work.