Architect

Architect

Design before implementing. Sketch types, function signatures, class shapes, and module boundaries with not implemented bodies and pseudocode. Synthesize across multiple model perspectives, then fill in code against the chosen sketch. If implementation proves the sketch wrong, throw it out and redesign.

Start

Open a todolist with one entry per phase before starting. Autonomous mode without checkpoints needs the list to show phase position and keep phases from silently disappearing.

1. Ground 2. Sketch 3. Agree 4. Implement 5. Scrap

Phase A: Ground the problem

Build a real mental model of every system the new code touches. Run the how skill over the relevant subsystems. Critique mode if existing structure is the constraint or the design must push back on it.

Naming a file isn't grounding. Produce the traced model how prescribes. If the design redefines ownership or layering, also run the why skill on the existing shape so the rationale becomes a constraint, not a guess.

Skip Phase A only when the work is genuinely greenfield with no surrounding system to integrate.

Phase B: Sketch

Run the arena skill with the design-sketch task and the Phase A grounding artifacts. Pass references/runner-prompt.md as each runner's prompt. Each candidate produces a design package shaped per references/rationale-template.md: the caller's usage written first, then the type sketch, function signatures, module map, and prose rationale derived from it.

Use your configured architect runners (defaults claude-opus-4-8-thinking-xhigh, gpt-5.5-high-fast, composer-2.5-fast).

This is the exhaust-the-design-space principle skill made concrete. Whole-shape alternatives, not point fixes inside one shape.

Arena returns one synthesized design package. The synthesis decision populates the rationale's "Synthesis decision" section.

Phase C: Agree (opt-in)

Default: proceed directly to implementation with the synthesized design. No human checkpoint.

Opt in to a checkpoint when the invoker explicitly asks: "/architect with checkpoint," "stop and show me before implementing," or similar. Then surface the synthesized design and pause for sign-off.

The synthesis can ship as its own commit either way. That's the "scaffold first" mode of the foundational-thinking principle skill; subsequent commits read as filling in bodies against a stable contract. Planned and scoped breakage during fill-in is fine, per the outcome-oriented-execution principle skill. For adversarial pressure on the design before implementing, run the interrogate skill on the synthesized sketch.

If the human pushes back on the shape (in a checkpoint or after the fact), treat that as Phase A evidence. Re-ground and re-run Phase B before writing more code.

Phase D: Implement against the sketch

Replace not implemented bodies with code, pseudocode with logic. The synthesized sketch is the contract.

Deviations from the sketch are signal worth surfacing, not friction to absorb silently. If a function needs a parameter the sketch didn't anticipate, ask whether the sketch was wrong, the requirement was missed, or the implementation is overreaching. Surface it; don't bolt it on.

Phase E: Scrap when the architecture is wrong

If implementation keeps producing friction the sketch can't absorb, throw the sketch out. Don't bolt fixes onto a wrong design, per the redesign-from-first-principles and fix-root-causes principle skills.

The signal is a pattern, not single instances. Tells:

• The same shape of workaround appearing repeatedly across unrelated code.
• Multiple unrelated edge cases that all need special-case branches.
• Types that need escape hatches (any, casts, optional fields always set in practice) to compile.
• The "we need a lock" reflex when the sketch said the state wasn't shared.
• Callers having to know the abstraction's internal rules to use it.
• Two or more independent Phase D deviations of the same shape across the implementation. Surfacing deviations is Phase D's job; a repeated pattern of them is Phase E's trigger.

Use judgment. A few edge cases don't condemn an architecture. Some problems are legitimately complex; complexity in the data is not complexity in the design. The rewrite signal is repeated friction of the same shape, not single hard cases.

When you scrap:

1. Re-run the how skill over what's been built. The implementation lessons enter the new design as inputs, not vibes. 2. Redesign as if the new constraints had been day-one assumptions, per redesign-from-first-principles. 3. Subtract before adding, per the subtract-before-you-add principle skill. The new sketch should be smaller than the old one before it grows. 4. Return to Phase B and re-run arena.

Outputs

The caller's usage is written first and the type sketch derived from it. One file with new types and signatures for small changes; module map plus type definitions for larger work. The rationale ships alongside, shaped per references/rationale-template.md, including the usage sketch and the synthesis decision.

Rationale template

The prose that ships alongside the type sketch. One page. Sentence-case headings, no boilerplate. Replace the italic notes with actual content.

Problem

One paragraph. What we're trying to do, and what about the existing system or constraints makes the shape non-obvious. If [Phase A](../SKILL.md#phase-a-ground-the-problem) surfaced constraints the design must honor (existing types to interop with, callers we can't break, invariants that crossed our boundary), name them here so the reader sees the same constraints you saw.

Usage (caller's view)

Write this first, before the type sketch. Show the README or quickstart the consumer reads, plus two or three realistic call sites in their own code. What they import, what they call, what comes back. The type sketch in [Shape](#shape) is derived from this. The two must agree; when they diverge, reconcile the sketch to the usage, not the reverse. The caller's experience is the spec. The types serve it.

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.

Synthesis decision

Filled in by [arena](../../arena/SKILL.md). Records which candidate became the base and why, what was adapted from each of the others, and what was rejected and why.

Tradeoffs accepted

One bullet per tradeoff the chosen shape makes. Form: "we accept X in exchange for Y." Name anything a future reader might mistake for an oversight, including things that look like premature optimization or premature simplification.

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.

Open questions and risks

Things you noticed during the sketch that the human needs to weigh in on, and risks worth flagging before implementation starts. Phrase as questions, not assertions, so the human's answer is the resolution rather than a comment.

Next implementation step

The first thing to build against the sketch. One sentence. What you'd start writing immediately after synthesis (or after Phase D sign-off, if a checkpoint was opted into).

Architect runner prompt

The orchestrator passes this file through to every parallel candidate runner during Phase B and fills in the variable inputs around it: the task, the Phase A grounding artifacts, the isolated working directory, and the path to write outputs. The working directory is a git worktree when available, otherwise a per-runner subdirectory under the sketch dir; what matters is independence between candidates.

You are producing one candidate design in architect's parallel exploration. Read the architect skill in full first; that's the workflow you're inside. Output a candidate design package: type sketch, function signatures, module map, and prose rationale shaped per `rationale-template.md`.

Apply the following discipline. The orchestrator compares candidates on these axes to pick a base.

• 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.
• 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.
• Validate at boundaries, trust types inside, per the boundary-discipline principle skill. Business logic as pure functions; the shell stays thin.
• Single source of truth per invariant. Derive instead of sync.
• Idempotent state transitions where applicable, per the make-operations-idempotent principle skill. Ask what happens if the operation runs twice or crashes halfway.
• Short call chains. If tracing the flow needs more than three files, flatten the hierarchy, per the laziness-protocol and minimize-reader-load principle skills.

You are one of several runners, each on a different model. Produce the best design your model can make; don't hedge against the others. Differences between candidates are the signal used to pick a base and graft. Converging on a safe-looking middle defeats the exploration.