Questions

Overview

Batch all pending questions, ambiguities, and decisions into structured AskUserQuestion tool calls instead of asking them inline as text. Forces use of the native multi-question UI for a faster, cleaner Q&A experience.

When to Use

• User invokes /questions
• You have 2+ unresolved questions about a task
• Before starting significant work where assumptions would be risky
• End-of-conversation sweep to surface anything still unclear

When NOT to Use

• You have exactly 1 simple yes/no question (just ask inline)
• The answer is obvious from context or code

Core Pattern

Step 1: Identify ALL Unanswered Questions

Scan your current context for:

• Ambiguous requirements — things the user said that could mean multiple things
• Missing information — details you need but weren't provided
• Decision points — choices where there are valid alternatives
• Assumptions you're making — things you're guessing at instead of knowing

Be thorough. Don't stop at the first 2 questions. Dig for everything that's unclear.

Step 2: Structure Into AskUserQuestion Calls

The tool supports 1-4 questions per call, each with 2-4 options (plus auto "Other").

Rules:

• Every question MUST go through AskUserQuestion — never ask questions as plain text when this skill is active
• Group related questions into the same call (max 4 per call)
• If you have >4 questions, use multiple sequential AskUserQuestion calls
• Each option needs a clear label (1-5 words) and a description explaining implications
• Put your recommended option first with "(Recommended)" suffix
• Use multiSelect: true when choices aren't mutually exclusive
• Use header as a short category tag (max 12 chars): "Scope", "Approach", "Priority", "Style", etc.

Step 3: Wait and Incorporate

After the user answers:

• Acknowledge their choices briefly (don't parrot them back)
• If answers reveal NEW questions, batch those into another AskUserQuestion call
• Once all questions are resolved, proceed with the task

Example

User says: "Add a caching layer to the API"

BAD (inline text):

"What kind of cache do you want? Redis? In-memory? Also, should I cache all endpoints or just the slow ones? And what about cache invalidation?"

GOOD (structured):

AskUserQuestion(questions: [
  {
    question: "What caching backend should we use?",
    header: "Backend",
    options: [
      { label: "Redis (Recommended)", description: "Distributed, persistent, works across instances" },
      { label: "In-memory (Map)", description: "Fastest, but lost on restart and per-instance only" },
      { label: "SQLite", description: "Persistent, single-node, no extra infra" }
    ],
    multiSelect: false
  },
  {
    question: "Which endpoints should be cached?",
    header: "Scope",
    options: [
      { label: "Slow endpoints only (Recommended)", description: "Cache responses >200ms, minimal risk" },
      { label: "All GET endpoints", description: "Broad caching, higher invalidation complexity" },
      { label: "Specific endpoints", description: "You'll tell me which ones" }
    ],
    multiSelect: false
  },
  {
    question: "How should cache invalidation work?",
    header: "Invalidation",
    options: [
      { label: "TTL-based (Recommended)", description: "Entries expire after a set time, simple and predictable" },
      { label: "Event-driven", description: "Invalidate on mutations, more complex but always fresh" },
      { label: "Manual only", description: "Cache until explicitly cleared" }
    ],
    multiSelect: false
  }
])

Quick Reference

Common Mistakes

Improve Codebase Architecture

Surface architectural friction and propose deepening opportunities — refactors that turn shallow modules into deep ones. The aim is testability and AI-navigability.

Glossary

Use these terms exactly in every suggestion. Consistent language is the point — don't drift into "component," "service," "API," or "boundary." Full definitions in LANGUAGE.md.

• Module — anything with an interface and an implementation (function, class, package, slice).
• Interface — everything a caller must know to use the module: types, invariants, error modes, ordering, config. Not just the type signature.
• Implementation — the code inside.
• Depth — leverage at the interface: a lot of behaviour behind a small interface. Deep = high leverage. Shallow = interface nearly as complex as the implementation.
• Seam — where an interface lives; a place behaviour can be altered without editing in place. (Use this, not "boundary.")
• Adapter — a concrete thing satisfying an interface at a seam.
• Leverage — what callers get from depth.
• Locality — what maintainers get from depth: change, bugs, knowledge concentrated in one place.

Key principles (see LANGUAGE.md for the full list):

• Deletion test: imagine deleting the module. If complexity vanishes, it was a pass-through. If complexity reappears across N callers, it was earning its keep.
• The interface is the test surface.
• One adapter = hypothetical seam. Two adapters = real seam.

This skill is informed by the project's domain model. The domain language gives names to good seams; ADRs record decisions the skill should not re-litigate.

Process

1. Explore

Read the project's domain glossary and any ADRs in the area you're touching first.

Then use the Agent tool with subagent_type=Explore to walk the codebase. Don't follow rigid heuristics — explore organically and note where you experience friction:

• Where does understanding one concept require bouncing between many small modules?
• Where are modules shallow — interface nearly as complex as the implementation?
• Where have pure functions been extracted just for testability, but the real bugs hide in how they're called (no locality)?
• Where do tightly-coupled modules leak across their seams?
• Which parts of the codebase are untested, or hard to test through their current interface?

Apply the deletion test to anything you suspect is shallow: would deleting it concentrate complexity, or just move it? A "yes, concentrates" is the signal you want.

2. Present candidates

Present a numbered list of deepening opportunities. For each candidate:

• Files — which files/modules are involved
• Problem — why the current architecture is causing friction
• Solution — plain English description of what would change
• Benefits — explained in terms of locality and leverage, and also in how tests would improve

Use CONTEXT.md vocabulary for the domain, and LANGUAGE.md vocabulary for the architecture. If CONTEXT.md defines "Order," talk about "the Order intake module" — not "the FooBarHandler," and not "the Order service."

ADR conflicts: if a candidate contradicts an existing ADR, only surface it when the friction is real enough to warrant revisiting the ADR. Mark it clearly (e.g. "contradicts ADR-0007 — but worth reopening because…"). Don't list every theoretical refactor an ADR forbids.

Do NOT propose interfaces yet. Ask the user: "Which of these would you like to explore?"

3. Grilling loop

Once the user picks a candidate, drop into a grilling conversation. Walk the design tree with them — constraints, dependencies, the shape of the deepened module, what sits behind the seam, what tests survive.

Side effects happen inline as decisions crystallize:

• Naming a deepened module after a concept not in CONTEXT.md? Add the term to CONTEXT.md — same discipline as /domain-model (see CONTEXT-FORMAT.md). Create the file lazily if it doesn't exist.
• Sharpening a fuzzy term during the conversation? Update CONTEXT.md right there.
• User rejects the candidate with a load-bearing reason? Offer an ADR, framed as: "Want me to record this as an ADR so future architecture reviews don't re-suggest it?" Only offer when the reason would actually be needed by a future explorer to avoid re-suggesting the same thing — skip ephemeral reasons ("not worth it right now") and self-evident ones. See ADR-FORMAT.md.
• Want to explore alternative interfaces for the deepened module? See INTERFACE-DESIGN.md.

Language

Shared vocabulary for every suggestion this skill makes. Use these terms exactly — don't substitute "component," "service," "API," or "boundary." Consistent language is the whole point.

Terms

Module Anything with an interface and an implementation. Deliberately scale-agnostic — applies equally to a function, class, package, or tier-spanning slice. Avoid: unit, component, service.

Interface Everything a caller must know to use the module correctly. Includes the type signature, but also invariants, ordering constraints, error modes, required configuration, and performance characteristics. Avoid: API, signature (too narrow — those refer only to the type-level surface).

Implementation What's inside a module — its body of code. Distinct from Adapter: a thing can be a small adapter with a large implementation (a Postgres repo) or a large adapter with a small implementation (an in-memory fake). Reach for "adapter" when the seam is the topic; "implementation" otherwise.

Depth Leverage at the interface — the amount of behaviour a caller (or test) can exercise per unit of interface they have to learn. A module is deep when a large amount of behaviour sits behind a small interface. A module is shallow when the interface is nearly as complex as the implementation.

Seam (from Michael Feathers) A place where you can alter behaviour without editing in that place. The location at which a module's interface lives. Choosing where to put the seam is its own design decision, distinct from what goes behind it. Avoid: boundary (overloaded with DDD's bounded context).

Adapter A concrete thing that satisfies an interface at a seam. Describes role (what slot it fills), not substance (what's inside).

Leverage What callers get from depth. More capability per unit of interface they have to learn. One implementation pays back across N call sites and M tests.

Locality What maintainers get from depth. Change, bugs, knowledge, and verification concentrate at one place rather than spreading across callers. Fix once, fixed everywhere.

Principles

• Depth is a property of the interface, not the implementation. A deep module can be internally composed of small, mockable, swappable parts — they just aren't part of the interface. A module can have internal seams (private to its implementation, used by its own tests) as well as the external seam at its interface.
• The deletion test. Imagine deleting the module. If complexity vanishes, the module wasn't hiding anything (it was a pass-through). If complexity reappears across N callers, the module was earning its keep.
• The interface is the test surface. Callers and tests cross the same seam. If you want to test past the interface, the module is probably the wrong shape.
• One adapter means a hypothetical seam. Two adapters means a real one. Don't introduce a seam unless something actually varies across it.

Relationships

• A Module has exactly one Interface (the surface it presents to callers and tests).
• Depth is a property of a Module, measured against its Interface.
• A Seam is where a Module's Interface lives.
• An Adapter sits at a Seam and satisfies the Interface.
• Depth produces Leverage for callers and Locality for maintainers.

Rejected framings

• Depth as ratio of implementation-lines to interface-lines (Ousterhout): rewards padding the implementation. We use depth-as-leverage instead.
• "Interface" as the TypeScript interface keyword or a class's public methods: too narrow — interface here includes every fact a caller must know.
• "Boundary": overloaded with DDD's bounded context. Say seam or interface.

Deepening

How to deepen a cluster of shallow modules safely, given its dependencies. Assumes the vocabulary in LANGUAGE.md — module, interface, seam, adapter.

Dependency categories

When assessing a candidate for deepening, classify its dependencies. The category determines how the deepened module is tested across its seam.

1. In-process

Pure computation, in-memory state, no I/O. Always deepenable — merge the modules and test through the new interface directly. No adapter needed.

2. Local-substitutable

Dependencies that have local test stand-ins (PGLite for Postgres, in-memory filesystem). Deepenable if the stand-in exists. The deepened module is tested with the stand-in running in the test suite. The seam is internal; no port at the module's external interface.

3. Remote but owned (Ports & Adapters)

Your own services across a network boundary (microservices, internal APIs). Define a port (interface) at the seam. The deep module owns the logic; the transport is injected as an adapter. Tests use an in-memory adapter. Production uses an HTTP/gRPC/queue adapter.

Recommendation shape: "Define a port at the seam, implement an HTTP adapter for production and an in-memory adapter for testing, so the logic sits in one deep module even though it's deployed across a network."

4. True external (Mock)

Third-party services (Stripe, Twilio, etc.) you don't control. The deepened module takes the external dependency as an injected port; tests provide a mock adapter.

Seam discipline

• One adapter means a hypothetical seam. Two adapters means a real one. Don't introduce a port unless at least two adapters are justified (typically production + test). A single-adapter seam is just indirection.
• Internal seams vs external seams. A deep module can have internal seams (private to its implementation, used by its own tests) as well as the external seam at its interface. Don't expose internal seams through the interface just because tests use them.

Testing strategy: replace, don't layer

• Old unit tests on shallow modules become waste once tests at the deepened module's interface exist — delete them.
• Write new tests at the deepened module's interface. The interface is the test surface.
• Tests assert on observable outcomes through the interface, not internal state.
• Tests should survive internal refactors — they describe behaviour, not implementation. If a test has to change when the implementation changes, it's testing past the interface.

Interface Design

When the user wants to explore alternative interfaces for a chosen deepening candidate, use this parallel sub-agent pattern. Based on "Design It Twice" (Ousterhout) — your first idea is unlikely to be the best.

Uses the vocabulary in LANGUAGE.md — module, interface, seam, adapter, leverage.

Process

1. Frame the problem space

Before spawning sub-agents, write a user-facing explanation of the problem space for the chosen candidate:

• The constraints any new interface would need to satisfy
• The dependencies it would rely on, and which category they fall into (see DEEPENING.md)
• A rough illustrative code sketch to ground the constraints — not a proposal, just a way to make the constraints concrete

Show this to the user, then immediately proceed to Step 2. The user reads and thinks while the sub-agents work in parallel.

2. Spawn sub-agents

Spawn 3+ sub-agents in parallel using the Agent tool. Each must produce a radically different interface for the deepened module.

Prompt each sub-agent with a separate technical brief (file paths, coupling details, dependency category from DEEPENING.md, what sits behind the seam). The brief is independent of the user-facing problem-space explanation in Step 1. Give each agent a different design constraint:

• Agent 1: "Minimize the interface — aim for 1–3 entry points max. Maximise leverage per entry point."
• Agent 2: "Maximise flexibility — support many use cases and extension."
• Agent 3: "Optimise for the most common caller — make the default case trivial."
• Agent 4 (if applicable): "Design around ports & adapters for cross-seam dependencies."

Include both LANGUAGE.md vocabulary and CONTEXT.md vocabulary in the brief so each sub-agent names things consistently with the architecture language and the project's domain language.

Each sub-agent outputs:

1. Interface (types, methods, params — plus invariants, ordering, error modes)
2. Usage example showing how callers use it
3. What the implementation hides behind the seam
4. Dependency strategy and adapters (see DEEPENING.md)
5. Trade-offs — where leverage is high, where it's thin

3. Present and compare

Present designs sequentially so the user can absorb each one, then compare them in prose. Contrast by depth (leverage at the interface), locality (where change concentrates), and seam placement.

After comparing, give your own recommendation: which design you think is strongest and why. If elements from different designs would combine well, propose a hybrid. Be opinionated — the user wants a strong read, not a menu.