Design Dialogue Skill

Standard workflow only. If

task_complexity

simple

Activate this skill when beginning Phase 1 of Maestro orchestration. Use the plan mode tool from

get_runtime_context

enter_plan_mode

type: 'yesno'

type: 'choice'

User confirmation sequence: Phase 1 entry may trigger a Plan Mode confirmation when

enter_plan_mode

Design Depth Gate

Before asking any design questions, present the user with a depth selector to control the level of reasoning rigour applied throughout the design phase. Use

ask_user

type: 'choice'

Modes:

• Quick — Current reasoning behavior. One question per topic, pros/cons on approaches, standard design sections. No enrichment steps, no decision matrix, no reasoning annotations. Choose this when you already have clarity and want to move fast. (The depth selector prompt itself is the only new conversational step — once Quick is selected, all subsequent behavior matches pre-change behavior exactly.)
• Standard (Recommended) — Adds assumption surfacing after each answer and a decision matrix during approach evaluation. Design sections gain rationale annotations tying decisions to project context. The default for most work.
• Deep — Full treatment. Follow-up probing into implications, assumption surfacing with confirmation, trade-off narration on each choice, decision matrix with scoring, rationale annotations, per-decision alternatives, and full requirement traceability. Choose this for high-stakes or ambiguous tasks.

Depth propagation: Remember the user's chosen depth mode and apply it consistently to all subsequent steps in this skill. The depth mode is not re-prompted — it is set once and carried forward. If the user's answer to the depth prompt is ambiguous, default to Standard.

Depth vs. complexity: Depth and complexity guidance (simple/medium/complex) are orthogonal. Complexity controls which sections appear and word count per section. Depth controls reasoning richness within each section. They compose independently — a user may select Deep depth on a Simple complexity task or Quick depth on a Complex task. Both are valid choices.

Frontmatter: Record the chosen depth in the design document frontmatter as

design_depth: quick | standard | deep

task_complexity: simple | medium | complex

design_depth

First-Turn Contract: On the first turn, Maestro presents the complexity classification result (classified per the complexity classification section in the orchestrator) and the depth selector with a complexity-informed recommendation. For

simple

medium

complex

Repository Grounding Protocol

Before you start narrowing the architecture for work that touches an existing codebase, decide whether the task is already grounded.

Use the built-in

codebase_investigator

• The request targets an existing project or subsystem
• The current architecture, impacted modules, or integration seams are unclear
• You need concrete validation commands, conventions, or ownership boundaries before presenting approaches

Ask the investigator for:

• The current architecture slice relevant to the task
• The most likely impacted modules and files
• Existing naming, layering, and testing conventions to preserve
• Integration points and dependency edges the design must respect
• Validation commands already used by the repo
• Parallelization or file-conflict risks that should shape the later implementation plan

Skip

codebase_investigator

Use the investigator's output to:

• Tailor follow-up questions to the actual codebase
• Avoid proposing approaches that conflict with existing boundaries
• Cite concrete modules/files when explaining trade-offs

Question Framework

Principles

• Ask one question at a time — never batch multiple questions
• Prefer multiple choice format with 2-4 options over open-ended questions
• For every choice presented, include brief pros and cons so the user can make an informed decision — never present bare options without trade-off context
• Lead with your recommended option and explain the rationale
• Wait for user response before proceeding to next question
• Adapt follow-up questions based on previous answers

Required Coverage Areas

Ask questions in this order to progressively narrow the design space:

1. Problem Scope & Boundaries

   • What specific problem are we solving?
   • What is explicitly out of scope?
   • What are the expected inputs and outputs?

2. Technical Constraints & Limitations

   • Existing technology stack and infrastructure
   • Compatibility requirements with existing systems
   • Performance budgets (latency, throughput, resource limits)
   • Team expertise and familiarity

3. Technology Preferences

   • Language and framework preferences
   • Database and storage requirements
   • Third-party service dependencies
   • Build and deployment toolchain

4. Quality Requirements

   • Performance targets (response time, concurrent users)
   • Security requirements (authentication, authorization, data protection)
   • Scalability expectations (growth projections, peak loads)
   • Reliability requirements (uptime, disaster recovery)

5. Deployment Context

   • Target environment (cloud provider, on-premise, hybrid)
   • CI/CD pipeline requirements
   • Monitoring and observability needs
   • Operational constraints (team size, on-call, maintenance windows)

Coverage Scaling by Complexity

Scale question coverage based on

task_complexity

• simple: Ask questions from Area 1 (Problem Scope & Boundaries) only. Skip Areas 2-5.
• medium: Ask questions from Areas 1-3 (Scope, Constraints, Tech Preferences). Skip Areas 4-5.
• complex: Ask questions from all 5 areas (current behavior).

Question Format

Prompt the user for a choice using the user-prompt tool from runtime context. Use

type: 'choice'

Enrichment Protocol

After the user answers each question, apply depth-gated enrichment steps before advancing to the next topic:

Quick mode: No enrichment steps. Accept the answer and proceed to the next question. Current behavior preserved.

Standard mode: After each user answer, state the assumptions you are making based on their response in 1-2 sentences, then ask the user to confirm or correct before proceeding. Example flow: question → answer → "Based on your answer, I'm assuming X and Y — correct?" → confirmation → next question.

Deep mode: After each user answer: (a) state and confirm assumptions as in Standard mode, (b) narrate the trade-offs of the choice in 1-2 sentences ("That choice means we gain A but give up B"), (c) if the answer has non-obvious implications (e.g., a technology choice that constrains future scaling options or creates a vendor lock-in dependency), ask one follow-up probing question before moving to the next topic. Cap at one follow-up per question.

Adaptive elision: If the user's answer is concrete, specific, and requires no inference (e.g., "What language?" → "TypeScript, same as the rest of the repo"), the assumption surfacing and trade-off narration steps may be skipped even in Deep mode. Only apply enrichment when there are genuine assumptions to surface or trade-offs to narrate. Do not elide when the answer implies unstated architectural trade-offs even if the answer itself is short (e.g., "REST" implies choices about state management, versioning, and contract evolution that are worth surfacing).

Approach Presentation

When to Present Approaches

Present 2-3 architectural approaches after gathering sufficient requirements (typically after covering scope, constraints, and technology preferences).

If

codebase_investigator

Approach Format

For each approach, provide:

### Approach [N]: [Descriptive Name]

**Summary**: [2-3 sentence overview]

**Architecture**:
[Component diagram or description showing key components and their relationships]

**Pros**:
- [Concrete advantage with context]
- [Another advantage]

**Cons**:
- [Concrete disadvantage with context]
- [Another disadvantage]

**Best When**: [Specific conditions where this approach excels]

**Risk Level**: Low | Medium | High

Presentation Rules

• Always lead with your recommended approach
• Explain why the recommended approach best fits the gathered requirements
• Highlight the key differentiator between approaches
• After presenting all approaches, explicitly ask the user to choose
• Accept user's choice without pushback, even if it differs from your recommendation

Recommendation Philosophy

• Always identify the ideal long-term solution — the approach that is architecturally sound, maintainable, and future-proof. Present it clearly so the user understands what "right" looks like.
• When the long-term solution requires large-scale changes that are disproportionate to the task at hand, also present a pragmatic alternative that accomplishes the goal without major disruption. Be explicit about the trade-off: "The ideal solution is X (because...), but a pragmatic path is Y (because the scope of X is disproportionate to the current need)."
• Never default to the quick fix without surfacing the long-term option. The user should always know what they're trading away. But equally, never recommend a large-scale refactor when the task can be accomplished safely with a targeted change.
• Label each approach honestly: which is the long-term investment, which is the pragmatic path, and which (if any) is a stopgap that will create debt.

Decision Matrix

In Standard and Deep modes, after presenting the 2-3 approaches with narrative pros/cons, also present a decision matrix that scores each approach against the gathered requirements. In Quick mode, skip the matrix.

Criteria derivation: Derive 3-6 scoring criteria from the requirements and constraints gathered during the question phase. Use the user's stated priorities to assign weights (sum to 100%). If the user has not explicitly stated priorities, infer relative weights from the emphasis given during the question phase; equal weighting is acceptable as a last resort. If fewer than 3 meaningful criteria emerge, skip the matrix and use narrative-only recommendation.

Scoring scale: Score each approach on each criterion using a 1-5 scale: 1=poor fit, 3=adequate, 5=strong fit. Include a brief justification (1 sentence) in each cell.

Matrix format:

Tie-breaking: If approaches score within 1 point of each other in weighted totals, present the near-tie explicitly and use narrative judgment to break the tie, citing the single most decisive factor. Do not present a matrix-driven recommendation as definitive when the scores don't clearly differentiate.

Non-differentiating criteria: Criteria that score identically across all approaches may be noted but should be excluded from the matrix to keep it focused on differentiating factors. If removing non-differentiating criteria leaves fewer than 2 rows, skip the matrix and use narrative-only recommendation.

Design Convergence Protocol

Section-by-Section Presentation

Present the design document in sections, validating each before proceeding. Scale the number of sections to the task's complexity, but always present at least the minimum set.

Minimum sections (always required, regardless of task complexity):

1. Problem Statement
2. Approach (Selected Approach, Alternatives Considered)
3. Risk Assessment

Full presentation order (use for medium-to-complex tasks; matches

templates/design-document.md

1. Problem Statement
2. Requirements (Functional, Non-Functional, Constraints)
3. Approach (Selected Approach, Alternatives Considered, Decision Matrix)
4. Architecture (Component Diagram, Data Flow, Key Interfaces)
5. Agent Team
6. Risk Assessment
7. Success Criteria

Complexity guidance:

• Simple (static sites, single-file scripts, config changes): present the 3 minimum sections. Keep each to 100-150 words.
• Medium (multi-component features, API endpoints, integrations): present sections 1-3 and 6, plus up to 1 other section that surfaces meaningful trade-offs (cap at 5 total). 150-250 words each.
• Complex (new subsystems, cross-cutting refactors, multi-service architectures): present all 7 sections at 200-300 words each.

Never skip Problem Statement, Approach, or Risk Assessment. If you believe other sections add no value for the task, omit them — but state which sections you are skipping and why before presenting the first section.

Validation Format

After each section, prompt the user for approval using the user-prompt tool from runtime context with

type: 'yesno'

Revision Protocol

• If user requests changes, revise the section and re-present
• Re-present revised content inside the next approval prompt as well; never ask for approval on a section summary the user cannot see in the prompt
• Track which sections are approved vs pending
• Do not proceed to the next section until current section is approved
• If a later section reveals issues with an earlier section, flag the conflict and propose resolution

Section Reasoning Guide

Apply depth-gated reasoning enrichment to design section content during the convergence phase:

Traces To

Quick mode: No reasoning annotations. Present sections as-is — current behavior preserved.

Rationale annotations (Standard + Deep): For each key design decision within a section, include an inline explanation of why it was chosen, tied to specific project context from the question phase. A key decision is one that, if changed, would require reworking other parts of the design — routine or cosmetic choices (naming, formatting) are not key. Format:

[decision] — *[rationale referencing specific requirements, constraints, or user-stated preferences]*

Per-decision alternatives (Deep only): For key sub-decisions (choices within a section that affect the design's shape), briefly note what was considered and rejected. Format:

[decision] *(considered: [alternative A] — rejected because [reason]; [alternative B] — rejected because [reason])*

Requirement traceability (Deep only): Tag each key decision with

Traces To: REQ-N

Uniform application: Apply the chosen depth mode's reasoning rules uniformly to every section in the convergence phase. Do not selectively skip reasoning on some sections unless the adaptive elision rule applies (the decision is self-evident and requires no justification).

Design Document Generation

Output Location

The write path depends on whether your runtime provides a Plan Mode surface (check

get_runtime_context

• Plan Mode active: Some runtimes restrict writes to a temporary staging directory during Plan Mode. Write the design document there. After

  exit_plan_mode

  approval in Phase 2, copy it to the permanent location.
• Plan Mode not active or not available: Write directly to the permanent location. If your runtime does not provide Plan Mode, track design progress using the plan-update mechanism from runtime context and use the user-prompt tool from runtime context for section approvals and final signoff.

Permanent location:

<state_dir>/plans/YYYY-MM-DD-<topic-slug>-design.md

<state_dir>

MAESTRO_STATE_DIR

docs/maestro

Where:

• YYYY-MM-DD

  is the current date

• <topic-slug>

  is a lowercase, hyphenated summary of the task (e.g.,

  user-auth-system

  ,

  data-pipeline-refactor

  )

Document Structure

Use the

design-document

get_skill_content

design_depth

Completion Criteria

The design document is complete when:

• All sections have been presented and approved by the user
• The agent team composition matches the task requirements
• Phase dependencies are clearly mapped
• Success criteria are measurable and specific
• The user has given explicit final approval of the complete document

Post-Generation

After writing the design document:

1. Confirm the file path to the user
2. Summarize key decisions made during the dialogue
3. Ask if the user is ready to proceed to implementation planning (Phase 2)