pstack: add architect-only interface depth guidance

pstack/.cursor-plugin/plugin.json

@@ -1,7 +1,7 @@
 {
 	"name": "pstack",
 	"displayName": "pstack",
-	"version": "0.11.12",
+	"version": "0.11.13",
 	"description": "if you want to go fast, go deep first. pstack helps you write less, but higher quality code. rigorous agent workflows you can parallelize with confidence.",
 	"author": {
 		"name": "Lauren Tan"

pstack/skills/architect/SKILL.md

@@ -32,7 +32,11 @@ Run the **arena** skill with the design-sketch task and the Phase A grounding ar
 
 Use your configured architect runners (defaults `claude-fable-5-thinking-max`, `gpt-5.6-sol-max`, `grok-4.5-fast-xhigh`, `claude-opus-5-thinking-xhigh`).
 
-This is the **exhaust-the-design-space** principle skill made concrete. Whole-shape alternatives, not point fixes inside one shape.
+Design it twice. Require at least two structurally distinct candidates before synthesis, even when the first looks sufficient. This is the **exhaust-the-design-space** principle skill made concrete. Whole-shape alternatives, not point fixes inside one shape.
+
+Screen every candidate against [`references/design-red-flags.md`](references/design-red-flags.md) before synthesis. Reject or revise shallow modules, information leakage, temporal decomposition, and pass-through methods.
+
+Compare viable candidates on interface depth. Prefer the design that hides more complexity behind a smaller, simpler public surface. A rich interface can keep call chains short by concentrating capability instead of scattering it across layers.
 
 Arena returns one synthesized design package. The synthesis decision populates the rationale's "Synthesis decision" section.
 

pstack/skills/architect/references/design-red-flags.md

@@ -0,0 +1,33 @@
+# Design red flags
+
+Screen every candidate before synthesis. A red flag is a reason to revise or reject the shape.
+
+## Shallow module
+
+A shallow module exposes a large interface while hiding little complexity. Judge depth by the capability and policy hidden behind the public surface relative to the size of that surface. Prefer a simple interface backed by substantial behavior.
+
+Do not confuse a deep module with a deep call chain. A deep call chain scatters understanding across layers. A deep module concentrates capability behind one interface.
+
+Look for these signs:
+
+- Callers coordinate several methods to complete one operation.
+- Public options expose internal stages or implementation choices.
+- Learning the interface does not save the caller from learning the implementation.
+
+## Information leakage
+
+Information leakage makes multiple modules depend on the same internal decision. A representation, policy, or protocol detail appears in more than one place, so changing it requires coordinated edits.
+
+Public re-exports of transport or wire types are leakage. Parse external data into domain types behind the interface. Keep storage schemas, framework objects, and protocol details private.
+
+## Temporal decomposition
+
+Temporal decomposition organizes modules by execution order instead of the knowledge they own. Separate load, validate, transform, and save stages often repeat one representation and its invariants across several boundaries.
+
+Group code around domain knowledge and ownership. Methods that run at different times can still belong to one module when they protect the same decisions.
+
+## Pass-through method
+
+A pass-through method forwards the same arguments to another method with the same shape. It adds a layer without hiding complexity.
+
+Remove it or move responsibility to the module that can complete the operation. Keep a forwarding boundary only when it adds policy, adaptation, or a distinct abstraction.

pstack/skills/architect/references/rationale-template.md

@@ -12,7 +12,7 @@ The prose that ships alongside the type sketch. One page. Sentence-case headings
 
 ## Shape
 
-*The recommended architecture. Data structures first; then how data flows through the signatures. Name the load-bearing decisions: which invariants are encoded in types, where validation lives, what the system deliberately does not do. Cite the principle behind each decision (e.g., `per boundary-discipline`); don't restate it.*
+*The recommended architecture. Data structures first; then how data flows through the signatures. Name the load-bearing decisions. State which invariants are encoded in types, where validation lives, and what the system deliberately does not do. Judge interface depth explicitly. State what complexity the public surface hides, what remains exposed to callers, and why the interface is no larger than needed. Cite the principle behind each decision (e.g., `per boundary-discipline`); don't restate it.*
 
 ## Synthesis decision
 
@@ -24,7 +24,7 @@ The prose that ships alongside the type sketch. One page. Sentence-case headings
 
 ## Alternatives considered
 
-*Required. Name at least one concrete alternative shape, with one line on why it lost. Two or three when the design space had real contenders; one is fine when the constraints forced the answer, with the conclusion phrased as "this was the only viable shape because..." Avoid listing flavors of the same shape. Distinct from "Synthesis decision": this section covers design alternatives the chosen shape considered and rejected, not other runner candidates.*
+*Required. Name at least one concrete alternative shape, with one line on why it lost. Judge each alternative on interface depth, not implementation simplicity alone. Name the complexity it exposes to callers and the complexity it hides. Two or three alternatives belong here when the design space had real contenders. One is fine when the constraints forced the answer, with the conclusion phrased as "this was the only viable shape because..." Avoid listing flavors of the same shape. This section covers design alternatives the chosen shape considered and rejected, not other runner candidates.*
 
 ## Open questions and risks
 

pstack/skills/architect/references/runner-prompt.md

@@ -8,6 +8,7 @@ Apply the following discipline. The orchestrator compares candidates on these ax
 
 - Caller's usage first. Write the README-style usage and two or three real call sites before the types, then derive the type sketch from them. The usage is the spec; the two must agree, so reconcile the sketch to the usage, not the reverse.
 - Data structures first. Get the core types right and the code becomes obvious. Trace each dominant access pattern through the proposed structure; if the answer is "we'll add a map / index / cache later," the structure is wrong.
+- Interface depth. Compare the capability hidden behind the public surface relative to the size of that surface. Prefer a simple interface that pulls complexity into the callee, even when the implementation becomes less simple. Do not put transport or wire types on the public surface; parse into domain types behind the interface.
 - Shared state: if two actors might both write, ask "what happens?" If the answer isn't "nothing," default to per-actor state with a merge at the read boundary, per the **separate-before-serializing-shared-state** principle skill.
 - Make boundaries visible. `not implemented` errors for bodies, `// TODO` pseudocode for tricky logic, doc comments stating intent and invariants. A reader should trace data from input to output by reading types and signatures alone.
 - Encode invariants in types: hard-to-misuse types > runtime checks > prose comments, per the **encode-lessons-in-structure** principle skill.

pstack/skills/principle-boundary-discipline/SKILL.md

@@ -13,12 +13,14 @@ Place validation, type narrowing, and error handling at system boundaries. Trust
 **The pattern:**
 - **At boundaries** (CLI args, config files, external APIs, network protocols): validate, return errors, handle defensively.
 - **Inside the system:** typed data, error propagation, no re-validation. Trust the types.
+- **Across the boundary.** Expose domain concepts, not the boundary's private representation. Keep general-purpose mechanism inside and special-purpose policy at the edge.
 
 **Applications:**
 
 Validation and error handling:
 - Validate config at parse time (the boundary), not inside business logic
-- Store raw data at boundaries; parse lazily at use-site
+- Parse raw data into domain types at the boundary
+- Do not re-export transport, storage, framework, or wire types through the public surface
 - No redundant nil checks deep in call chains if the boundary already validated
 
 Code organization:

pstack/skills/principle-exhaust-the-design-space/SKILL.md

@@ -8,7 +8,7 @@ disable-model-invocation: true
 
 When a novel interaction or architectural decision has no established precedent, explore several concrete alternatives before implementation. Building the wrong thing costs more than exploring three options.
 
-**The rule:** When the right answer is not obvious, build 2-3 competing prototypes or sketches. Compare them side by side. Only then commit.
+**The rule.** When the right answer is not obvious, build 2-3 competing prototypes or sketches. Compare them side by side. Only then commit. Design it twice is this rule by another name. A second flavor of the first shape does not count.
 
 **When it applies:**
 - Novel UI interactions (no prior art in the codebase)

pstack/skills/principle-foundational-thinking/SKILL.md

@@ -16,4 +16,6 @@ At code level, DRY the structure, not every line. Types and data models should c
 
 **Scaffold first.** If something helps every later phase, do it first. Ask "does every subsequent phase benefit from this existing?" CI, linting, test infrastructure, and shared types are scaffold. Sequence for option value: setup before features, tests before fixes. Keep commits small and single-purpose.
 
+Each increment should land a coherent abstraction or deepen one that exists. Do not spread a new capability across callers as special-case coordination.
+
 Subtraction comes before scaffolding: remove dead weight first, then lay foundations.

pstack/skills/principle-laziness-protocol/SKILL.md

@@ -9,9 +9,10 @@ disable-model-invocation: true
 Writing code is cheap for you, which makes over-engineering easy. Counter it by borrowing a human maintainer's fatigue. Aim for the most result with the least code and complexity.
 
 - **Prefer deletion.** When asked to refactor or improve, look for removals before additions.
-- **Maintain a flat hierarchy.** Avoid deep abstractions. If answering a question requires tracing through more than 3 files or layers, flatten it.
+- **Maintain a flat call hierarchy.** Avoid deep call chains. A rich interface that hides substantial work is not a deep call chain. If answering a question requires tracing through more than 3 files or layers, flatten it.
 - **Consolidate decisions.** Do not repeat the same choice in several places. Put it behind one source of truth and pass the result as a simple flag.
 - **Minimize the diff.** Make the smallest change that solves the problem. Fewer lines beat "elegant" boilerplate.
 - **Question the threading.** If a task asks you to pass a new signal through types, schemas, pipelines, or similar layers, stop and look for a more direct path.
+- **Sweat the small leaks.** Remove tiny pass-throughs, representation leaks, and duplicated choices before they spread. Small leaks compound into permanent coordination costs.
 
 **Prime directive:** If a human developer would find the code exhausting to maintain, it is a bad solution. Be lazy. Stay simple.

pstack/skills/principle-minimize-reader-load/SKILL.md

@@ -14,6 +14,8 @@ Maintainability is the work a reader must do to understand code. Track two axes:
 
 **The pattern:**
 - **Collapse layers** that do not earn their keep: wrappers with one caller, adapters with no second implementation, indirection introduced for a future that never came. Inline them.
+- **Make adjacent layers change the abstraction.** A layer that repeats the same methods and arguments adds reader load without compression. Collapse pass-through layers.
+- **Demand interface compression.** A broad interface that hides little complexity makes readers learn both the surface and the implementation. Prefer boundaries that hide meaningful decisions.
 - **Shrink state scope:** prefer pure functions (returns over mutations), locals over fields, fields over module state, and module state over globals. Derive instead of sync.
 - **Name the invariant at the boundary,** not in every consumer, so the reader learns it once.
 - Before adding a layer or a piece of state, ask: does this reduce reader load somewhere else by at least as much?

pstack/skills/principle-model-the-domain/SKILL.md

@@ -10,16 +10,17 @@ Encode the real domain in a data structure instead of scattering it across condi
 
 **Why:** Scattered booleans, repeated shape assumptions, and branching spread across files are accidental complexity. A structure that matches the domain makes invalid states unrepresentable and deletes branches. Choosing it at write time is cheap; recovering it later reads as a refactor and gets deferred.
 
-**Pattern — reach for:**
+**Reach for structures like these:**
 
 - A state machine instead of scattered booleans, phases, or lifecycle checks.
 - A typed object/model instead of loose parameters or repeated shape assumptions.
 - A map, registry, lookup table, or discriminated union instead of branching spread across files.
 - A reducer or command/event model instead of ad hoc state mutations.
+- A module organized around one body of domain knowledge instead of a sequence such as load, validate, transform, and save. Execution order is not ownership.
 - A small module boundary that gathers repeated behavior, ownership, or invariants.
 - A queue, cache, index, graph/tree, or normalized collection where the data access pattern calls for it.
 - Any other structure that fits. The list above covers the common cases only. When none fits, work out what the code must never allow and how the data gets read, then find the structure that encodes exactly that.
 
 Do not force an abstraction. Prefer boring code if the current shape is already clear, local, and unlikely to grow. Be skeptical of an abstraction that adds indirection without removing branches, duplicated rules, invalid states, or lifecycle risk.
 
-The tell that you skipped this: a new feature that grows an existing if/else chain by one more branch, or a second boolean that must stay in sync with the first.
+The tell that you skipped this is a new feature that grows an existing if/else chain by one more branch, or a second boolean that must stay in sync with the first. Temporal decomposition is another tell. Phase-named modules repeat the same domain rules across steps.

pstack/skills/principle-subtract-before-you-add/SKILL.md

@@ -10,6 +10,8 @@ When evolving a system, remove complexity first, then build. Deletion gives you
 
 **Why:** Adding to a complex system compounds complexity. Removing first cuts the surface area, reveals the essential structure, and usually makes the next design obvious. Default to subtraction.
 
+Make simplification a continual investment. Leave the design slightly simpler and more capable behind the same or smaller surface than you found it.
+
 **The pattern:**
 - Sequence removal before construction
 - Cut before you polish (get to the minimum before investing in quality)