deep-interview

Phase 0: Preflight Context Intake

1. Parse {{ARGUMENTS}} and derive a short task slug.
2. Attempt to load the latest relevant context snapshot from .omx/context/{slug}-*.md.
3. Check whether the provided initial context or loaded snapshot is too large for safe prompt use. If it is oversized, the first interview round must ask for a concise prompt-safe summary instead of scoring ambiguity or continuing to downstream handoff.
4. If no snapshot exists, create a minimum context snapshot with:
   • Task statement
   • Desired outcome
   • Stated solution (what the user asked for)
   • Probable intent hypothesis (why they likely want it)
   • Known facts/evidence
   • Constraints
   • Unknowns/open questions
   • Decision-boundary unknowns
   • Likely codebase touchpoints
   • Relevant repo docs/rules/context inspected
   • Terminology or doc/code conflicts found
   • Prompt-safe initial-context summary status (not_needed, needed, or recorded)
5. For brownfield tasks, inspect the applicable documentation/rule surface before the first user-facing round. Prefer exact, nearby sources over broad scans:
   • governing AGENTS.md files and template/runtime instruction surfaces that apply to the touched paths
   • README/getting-started docs and relevant docs under docs/, especially contracts, plans, ADR-like records, and workflow docs
   • existing .omx/context/ snapshots, .omx/specs/, and planning artifacts relevant to the slug
   • project-local glossary/context files such as CONTEXT.md, CONTEXT-MAP.md, or context-specific docs when they exist
6. Save snapshot to .omx/context/{slug}-{timestamp}.md (UTC YYYYMMDDTHHMMSSZ) and reference it in mode state.

Phase 1: Initialize

1. Parse {{ARGUMENTS}} and depth profile (--quick|--standard|--deep).
2. Detect project context:
   • Run explore to classify brownfield (existing codebase target) vs greenfield.
   • For brownfield, collect relevant codebase context before questioning.
3. Initialize state via omx state write --input '{"mode":"deep-interview","active":true}' --json:

{
  "active": true,
  "current_phase": "deep-interview",
  "state": {
    "interview_id": "<uuid>",
    "profile": "quick|standard|deep",
    "type": "greenfield|brownfield",
    "initial_idea": "<user input>",
    "rounds": [],
    "current_ambiguity": 1.0,
    "threshold": 0.3,
    "max_rounds": 5,
    "challenge_modes_used": [],
    "codebase_context": null,
    "current_stage": "intent-first",
    "current_focus": "intent",
    "context_snapshot_path": ".omx/context/<slug>-<timestamp>.md"
  }
}

4. Announce kickoff with profile, threshold, and current ambiguity.

Phase 2: Socratic Interview Loop

Repeat until ambiguity <= threshold, the pressure pass is complete, the readiness gates are explicit, the user exits with warning, or max rounds are reached. This is a stop condition: below threshold, do not open a new ordinary interview branch.

2a) Generate next question

If the initial context is oversized and no prompt-safe summary has been recorded yet, the next question must be only a summary request. Do not score ambiguity, do not run readiness gates, and do not hand off to $ultragoal, $ralplan, $autopilot, $ralph, or $team until that summary answer is captured.

Use:

• Original idea
• Prior Q&A rounds
• Current dimension scores
• Brownfield context (if any)
• Doc/context grounding notes, including existing terminology, governing rules, and any doc/code mismatch
• Activated challenge mode injection (Phase 3)

Target the lowest-scoring dimension, but respect stage priority:

• Stage 1 — Intent-first: Intent, Outcome, Scope, Non-goals, Decision Boundaries
• Stage 2 — Feasibility: Constraints, Success Criteria
• Stage 3 — Brownfield grounding: Context Clarity (brownfield only)

Follow-up pressure ladder after each answer:

1. Ask for a concrete example, counterexample, or evidence signal behind the latest claim
2. Probe the hidden assumption, dependency, or belief that makes the claim true
3. Force a boundary or tradeoff: what would you explicitly not do, defer, or reject?
4. Challenge fuzzy or conflicting terms against the repo's documented language and current code behavior
5. Stress-test the boundary with one concrete scenario or edge case when a relationship or handoff remains ambiguous
6. If the answer still describes symptoms, reframe toward essence / root cause before moving on

Prefer staying on the same thread for multiple rounds when it has the highest leverage. Breadth without pressure is not progress.

Maintain a Breadth Ledger across independent ambiguity tracks: scope, constraints, outputs, verification, brownfield integration, and any user-mentioned deliverable tracks. The ledger is a guard, not a mandatory rotation rule: stay deep on the current thread until it has been pressure-tested, then zoom out only when another material track remains unresolved and would change execution.

Maintain a Docs/Terminology Ledger for brownfield interviews:

• repo docs/rules/context sources inspected, with path references
• canonical terms already used by the repo and terms to avoid or disambiguate
• user terms that conflict with docs or current code behavior
• doc/code mismatches that require a human decision before implementation
• optional durable-doc follow-ups that are safe to propose but not auto-apply

Detailed dimensions:

• Intent Clarity — why the user wants this
• Outcome Clarity — what end state they want
• Scope Clarity — how far the change should go
• Constraint Clarity — technical or business limits that must hold
• Success Criteria Clarity — how completion will be judged
• Context Clarity — existing codebase understanding (brownfield only)

Non-goals and Decision Boundaries are mandatory readiness gates. Ask about them early and keep revisiting them until they are explicit.

2b) Ask the question

Use the surface-appropriate structured questioning path for every interview round. In attached-tmux sessions, use OMX-owned structured questioning via omx question (this is the required structured-question equivalent and required AskUserQuestion equivalent for deep-interview). Outside tmux, use native structured input when available; otherwise ask exactly one concise plain-text question and wait for the answer. Present:

Round {n} | Target: {weakest_dimension} | Ambiguity: {score}%

{question}

omx question payload guidance for interview rounds:

• Deep-interview is Socratic: ask one focused round at a time. Do not use batch questions[] to combine multiple interview rounds, even though omx question supports batch forms for other workflows.
• Use canonical type values instead of authoring raw multi_select flags by hand. type: "single-answerable" is the default for one-path decisions; type: "multi-answerable" is the canonical shape for bounded multi-select rounds. The runtime will keep multi_select aligned with type.
• Use single-answerable when exactly one answer should drive the next branch, the options are mutually exclusive, or selecting more than one answer would blur the decision boundary. Typical cases: handoff lane selection, choosing the primary failure mode, or confirming which of several competing interpretations is correct.
• Use multi-answerable when multiple options may all be true at once and you need to capture a bounded set of coexisting constraints, non-goals, risks, or acceptance checks in one round. Typical cases: selecting all out-of-scope items, all success metrics that must hold, or all deployment constraints that apply together.
• If one selected option would immediately require a follow-up question to disambiguate the others, prefer a single-answerable round now and ask the follow-up next. Do not hide a branching interview tree inside one overloaded multi-select prompt.
• Keep interview options bounded and concrete. If the valid answers are already known, set allow_other: false; only leave allow_other: true when the interview genuinely needs one user-supplied option that cannot be enumerated in advance.
• Read answers structurally from the primary answers[] array. For a normal single-round interview response, use answers[0].answer as the source of truth; the top-level answer field is a legacy single-question projection/fallback only.
• For single-answerable, expect one decisive selection in the value field of answers[0].answer plus its selected-values metadata. For multi-answerable, treat the selected-values field inside answers[0].answer as the source of truth for all chosen constraints/non-goals and preserve the full set in the transcript/spec. In legacy single-question projections, this is equivalent to: For multi-answerable, treat answer.selected_values as the source of truth.

Canonical bounded single-choice payload:

{
  "question": "Which execution lane should own this once the interview is complete?",
  "type": "single-answerable",
  "options": [
    {
      "label": "Plan first",
      "value": "ralplan",
      "description": "Need architecture and test-shape review before execution"
    },
    {
      "label": "Execute directly",
      "value": "autopilot",
      "description": "Requirements are already explicit enough for planning plus execution"
    },
    {
      "label": "Refine further",
      "value": "refine",
      "description": "Clarification is still needed before any handoff"
    }
  ],
  "allow_other": false,
  "other_label": "Other",
  "source": "deep-interview"
}

Canonical bounded multi-select payload:

{
  "question": "Which non-goals must stay out of scope for the first pass?",
  "type": "multi-answerable",
  "options": [
    {
      "label": "No UI redesign",
      "value": "no-ui-redesign",
      "description": "Keep layout and styling unchanged"
    },
    {
      "label": "No new dependencies",
      "value": "no-new-dependencies",
      "description": "Work within the existing toolchain"
    },
    {
      "label": "No API contract changes",
      "value": "no-api-contract-changes",
      "description": "Preserve external request and response shapes"
    }
  ],
  "allow_other": false,
  "other_label": "Other",
  "source": "deep-interview"
}

Canonical answer-shape reminders:

{
  "answer": {
    "kind": "option",
    "value": "ralplan",
    "selected_labels": ["Plan first"],
    "selected_values": ["ralplan"]
  }
}

{
  "answer": {
    "kind": "multi",
    "value": ["no-new-dependencies", "no-api-contract-changes"],
    "selected_labels": ["No new dependencies", "No API contract changes"],
    "selected_values": ["no-new-dependencies", "no-api-contract-changes"]
  }
}

2c) Score ambiguity

Score each weighted dimension in [0.0, 1.0] with justification + gap.

Greenfield: ambiguity = 1 - (intent × 0.30 + outcome × 0.25 + scope × 0.20 + constraints × 0.15 + success × 0.10)

Brownfield: ambiguity = 1 - (intent × 0.25 + outcome × 0.20 + scope × 0.20 + constraints × 0.15 + success × 0.10 + context × 0.10)

Readiness gate:

• Non-goals must be explicit
• Decision Boundaries must be explicit
• A pressure pass must be complete: at least one earlier answer has been revisited with an evidence, assumption, or tradeoff follow-up
• A practical closure audit must pass: another question would change execution materially, not merely polish wording or chase a narrow edge case
• If either gate is unresolved, or the pressure pass is incomplete, continue below threshold only with a final closure question that names the unresolved gate and would materially change execution.
• Treat a low ambiguity score as permission to audit closure, not permission to keep drilling indefinitely. If remaining uncertainty would not change implementation, crystallize the spec instead of opening a new branch.
• If ambiguity is <= 0.10, another user-facing question is allowed only as that final closure question; otherwise crystallize immediately.

2d) Report progress

Show weighted breakdown table, readiness-gate status (Non-goals, Decision Boundaries), and the next focus dimension.

2e) Persist state

Append round result and updated scores via omx state write --input '<json>' --json; use state_write only when explicit MCP compatibility is enabled.

2f) Round controls

• Do not offer early exit before the first explicit assumption probe and one persistent follow-up have happened
• Apply a Dialectic Rhythm Guard: track consecutive non-user fact discoveries and confirmation-style answers ([from-code][auto-confirmed], [from-code], or [from-research]). After 3 consecutive non-user or confirmation answers, the next material user-facing round must solicit direct human judgment ([from-user]) unless the closure audit says the interview is ready to crystallize.
• Round 4+: allow explicit early exit with risk warning
• Soft warning at profile midpoint (e.g., round 3/6/10 depending on profile)
• Hard cap at profile max_rounds; never treat this cap as a desired interview length or quota

Phase 3: Challenge Modes (assumption stress tests)

Use each mode once when applicable. These are normal escalation tools, not rare rescue moves:

• Contrarian (round 2+ or immediately when an answer rests on an untested assumption): challenge core assumptions
• Terminologist (brownfield, whenever a key term is fuzzy, overloaded, or conflicts with repo docs/code): force a canonical meaning against existing project language before implementation
• Simplifier (round 4+ or when scope expands faster than outcome clarity): probe minimal viable scope
• Ontologist (round 5+ and ambiguity > 0.25, or when the user keeps describing symptoms): ask for essence-level reframing

Track used modes in state to prevent repetition.

Phase 4: Crystallize Artifacts

When threshold is met (or user exits with warning / hard cap):

1. Write interview transcript summary to:
   • .omx/interviews/{slug}-{timestamp}.md
     (kept for ralph PRD compatibility)
2. Write execution-ready spec to:
   • .omx/specs/deep-interview-{slug}.md

Spec should include:

• Metadata (profile, rounds, final ambiguity, threshold, context type)
• Context snapshot reference/path (for ralplan/team reuse)
• Prompt-safe initial-context summary when oversized context was provided, plus references to any full source documents
• Clarity breakdown table
• Intent (why the user wants this)
• Desired Outcome
• In-Scope
• Out-of-Scope / Non-goals
• Decision Boundaries (what OMX may decide without confirmation)
• Constraints
• Testable acceptance criteria
• Assumptions exposed + resolutions
• Pressure-pass findings (which answer was revisited, and what changed)
• Brownfield evidence vs inference notes for any repository-grounded confirmation questions
• Docs/Terminology Ledger with inspected repo docs/rules/context, term conflicts, and any doc/code mismatch decisions
• Scenario/edge-case pressure findings that materially shaped scope or acceptance criteria
• Optional durable documentation recommendations, explicitly marked opt-in and public-safe; do not include raw private transcript dumps
• Technical context findings
• Full or condensed transcript

Autoresearch specialization

When the clarified task is specifically about $autoresearch, or the skill is invoked with --autoresearch, keep the interview domain-specific and emit skill-consumable artifacts without skipping clarification.

• Accepted seed inputs: topic, evaluator, keep-policy, slug, existing mission draft text, and prior evaluator examples/templates
• Required interview focus: mission clarity, evaluator readiness, keep policy, slug/session naming, and whether the draft is ready to launch now or should refine further
• Canonical artifact path: .omx/specs/deep-interview-autoresearch-{slug}.md
• Launch artifact bundle: .omx/specs/autoresearch-{slug}/mission.md, .omx/specs/autoresearch-{slug}/sandbox.md, and .omx/specs/autoresearch-{slug}/result.json
• Launch artifact directory: .omx/specs/autoresearch-{slug}/
• Required artifact sections:
  • Mission Draft
  • Evaluator Draft
  • Launch Readiness
  • Seed Inputs
  • Confirmation Bridge
• Required launch artifacts under .omx/specs/autoresearch-{slug}/:
  • mission.md
  • sandbox.md
  • result.json
• Launch-readiness rule: mark the draft as not launch-ready while the evaluator command still contains placeholder markers such as <...>, TODO, TBD, REPLACE_ME, CHANGEME, or your-command-here
• Structured result contract: result.json should point to the draft + mission/sandbox artifacts and carry the finalized topic, evaluatorCommand, keepPolicy, slug, launchReady, and blockedReasons fields so $autoresearch can consume it directly
• Confirmation bridge: after artifact generation, offer at least refine further and launch; do not run direct CLI launch or detached/split tmux launch, and only hand off to $autoresearch after explicit confirmation
• Handoff rule: downstream execution must preserve the clarified mission intent, evaluator expectations, decision boundaries, and launch-readiness status from this artifact rather than bypassing the draft review step

Phase 5: Execution Bridge

Present execution options after artifact generation using explicit handoff contracts. Treat the deep-interview spec as the current requirements source of truth and preserve intent, non-goals, decision boundaries, acceptance criteria, docs/terminology grounding, and any residual-risk warnings across the handoff.

Optional execution contract foundation

When an Autopilot/deep-interview handoff explicitly requires a stride contract, emit it as structured data rather than prose. This is a validation foundation, not a broadness-inference feature: do not infer stride from task length, phase labels, snapshots, or freeform wording.

Canonical location under Autopilot state:

{
  "handoff_artifacts": {
    "deep_interview": {
      "execution_contract_required": true,
      "execution_contract": {
        "version": 1,
        "execution_stride": "task",
        "source": "deep-interview",
        "selected_by": "user",
        "allow_task_shrink": true,
        "completion_unit": "One focused task",
        "stop_condition": "Stop after that task is implemented and verified",
        "acceptance_coverage_scope": "task",
        "shrink_policy": "allowed"
      }
    }
  }
}

Stride meanings:

• task: conservative, small-step execution; allow_task_shrink:true, acceptance_coverage_scope:"task", shrink_policy:"allowed".
• deliverable: finish the named deliverable before stopping; allow_task_shrink:false, acceptance_coverage_scope:"deliverable", shrink_policy:"ask_before_shrink".
• milestone: finish the larger approved milestone unless blocked; allow_task_shrink:false, acceptance_coverage_scope:"milestone", shrink_policy:"deny_unless_blocked".

Only set execution_contract_required:true when the selected downstream workflow needs this explicit stride/stop-condition guard. New artifacts must write the canonical snake_case schema shown above under handoff_artifacts.deep_interview; runtime readers may accept legacy camelCase field/marker aliases and direct/nested execution_contract locations only as compatibility input. If execution_contract_required is absent or false, downstream Autopilot compatibility behavior is unchanged.

Goal-mode follow-ups

Include these product-facing suggestions when they fit the clarified spec, without removing the existing $ultragoal, $ralplan, $autopilot, $ralph, and $team handoff options:

• $ultragoal — default goal-mode follow-up for implementation or general goal-oriented follow-up specs that should be converted into durable Codex/OMX goals with sequential completion tracking.
• $autoresearch-goal — use when the clarified context is a research project: a research question, reference/literature gathering, evaluator-backed analysis, or professor/critic-style deliverable.
• $performance-goal — use when the clarified context is an optimization or performance project with measurable speed, latency, throughput, memory, benchmark, or evaluator criteria.

Recommend $ultragoal as the default durable goal-mode follow-up because it supersedes Ralph for goal tracking. Preserve $team for coordinated parallel implementation and keep $ralph only as an explicit fallback for persistent single-owner execution/verification when the user specifically selects it.

1. $ultragoal (Default durable execution follow-up)

• Input Artifact: .omx/specs/deep-interview-{slug}.md (optionally accompanied by the transcript/context snapshot for traceability)
• Invocation: $ultragoal create-goals --brief-file <spec-path> followed by $ultragoal complete-goals in the active execution lane
• Consumer Behavior: Convert the clarified spec into durable goal-mode work. Preserve intent, non-goals, decision boundaries, acceptance criteria, docs/terminology grounding, scenario-pressure findings, and residual-risk warnings as binding story constraints.
• Skipped / Already-Satisfied Stages: Requirement interview, ambiguity clarification, doc/context preflight, and early intent-boundary elicitation
• Expected Output: .omx/ultragoal/brief.md, .omx/ultragoal/goals.json, .omx/ultragoal/ledger.jsonl, implementation evidence, verification evidence, and final cleanup/review-gate evidence
• Best When: The clarified spec is execution-ready or the user explicitly wants durable goal tracking as the next step
• Next Recommended Step: Run the Ultragoal completion loop; launch $team only inside an active Ultragoal story when parallel lanes are warranted, and use $ralph only as an explicit fallback when the user asks for that legacy persistence mode

2. $ralplan (Recommended when architecture/test-shape review is still needed)

• Input Artifact: .omx/specs/deep-interview-{slug}.md (optionally accompanied by the transcript/context snapshot for traceability)
• Invocation: $plan --consensus --direct <spec-path>
• Consumer Behavior: Treat the deep-interview spec as the requirements source of truth. Do not repeat the interview by default; refine architecture/feasibility around the clarified intent and boundaries instead.
• Skipped / Already-Satisfied Stages: Requirements discovery, ambiguity clarification, and early intent-boundary elicitation
• Expected Output: Canonical planning artifacts under .omx/plans/, especially prd-*.md and test-spec-*.md
• Best When: Requirements are clear enough to stop interviewing, but architectural validation / consensus planning is still desirable
• Next Recommended Step: Use the approved planning artifacts with $ultragoal as the default durable goal-mode follow-up (optionally with $team for parallel lanes); choose $autoresearch-goal for research validation or $performance-goal for measurable optimization, and use $ralph only as an explicit fallback when a narrow single-owner persistence loop is requested

3. $autopilot

• Input Artifact: .omx/specs/deep-interview-{slug}.md
• Invocation: $autopilot <spec-path>
• Consumer Behavior: Use the deep-interview spec as the clarified execution brief. Preserve intent, non-goals, decision boundaries, and acceptance criteria as binding context for planning/execution.
• Skipped / Already-Satisfied Stages: Initial requirement discovery and ambiguity reduction
• Expected Output: Planning/execution progress, QA evidence, and validation artifacts produced by autopilot
• Best When: The clarified spec is already strong enough for direct planning + execution without an additional consensus gate
• Next Recommended Step: Continue through autopilot's execution/QA/validation flow; if coordination-heavy execution emerges, prefer $team under a leader-owned $ultragoal ledger, using $ralph only as an explicit fallback when a narrow single-owner persistence loop is requested

4. $ralph (Explicit fallback only)

• Input Artifact: .omx/specs/deep-interview-{slug}.md
• Invocation: $ralph <spec-path>
• Consumer Behavior: Use the spec's acceptance criteria and boundary constraints as the persistence target. Do not reopen requirements discovery unless the user explicitly asks to refine further.
• Skipped / Already-Satisfied Stages: Requirement interview, ambiguity clarification, and initial scope-definition work
• Expected Output: Iterative execution progress and verification evidence tracked against the clarified criteria
• Best When: The user explicitly asks for Ralph's persistent sequential completion pressure; otherwise use $ultragoal for durable goal tracking and completion checkpoints
• Next Recommended Step: If this explicit fallback is selected, continue Ralph's persistence loop; if work expands into coordination-heavy lanes, hand off to $team under $ultragoal checkpointing rather than promoting Ralph as the next default

5. $team

• Input Artifact: .omx/specs/deep-interview-{slug}.md
• Invocation: $team <spec-path>
• Consumer Behavior: Treat the spec as shared execution context for coordinated parallel work. Preserve the clarified intent, non-goals, decision boundaries, and acceptance criteria as common lane constraints.
• Skipped / Already-Satisfied Stages: Requirement clarification and early ambiguity reduction
• Expected Output: Coordinated multi-agent execution against the shared spec, with evidence that can later feed Ultragoal checkpoints by default, or an explicit Ralph verification pass only when requested
• Best When: The task is large, multi-lane, or blocker-sensitive enough to justify coordinated parallel execution instead of a single persistent loop
• Next Recommended Step: Follow the team verification path when the coordinated execution phase finishes; checkpoint completion through $ultragoal by default, escalating to a separate Ralph loop only when the user explicitly asks for that persistent verification/fix owner

6. Refine further

• Input Artifact: Existing transcript, context snapshot, and current spec draft
• Invocation: Continue the interview loop
• Consumer Behavior: Re-enter questioning to resolve the highest-leverage remaining uncertainty
• Skipped / Already-Satisfied Stages: None beyond already-captured context
• Expected Output: A lower-ambiguity spec with tighter boundaries and fewer unresolved assumptions
• Best When: Residual ambiguity is still too high, the user wants stronger clarity, or the above-threshold / early-exit warning indicates too much risk to proceed cleanly
• Next Recommended Step: Return to one of the execution handoff contracts above once the spec is sufficiently clarified

Residual-Risk Rule: If the interview ended via early exit, hard-cap completion, or above-threshold proceed-with-warning, explicitly preserve that residual-risk state in the handoff so the downstream skill knows it inherited a partially clarified brief.

IMPORTANT: Deep-interview is a requirements mode. On handoff, invoke the selected skill using the contract above. Do NOT implement directly inside deep-interview.