deep-interview

name	deep-interview
description	Socratic deep interview with mathematical ambiguity gating before execution
argument-hint	[--quick|--standard|--deep] [--autoresearch] <idea or vague description>

Deep Interview is an intent-first Socratic clarification loop before planning or implementation. It turns vague ideas into execution-ready specifications by asking targeted questions about why the user wants a change, how far it should go, what should stay out of scope, and what OMX may decide without confirmation.

<Use_When>

• The request is broad, ambiguous, or missing concrete acceptance criteria
• The user says "deep interview", "interview me", "ask me everything", "don't assume", or "ouroboros"
• The user wants to avoid misaligned implementation from underspecified requirements
• You need a requirements artifact before handing off to ralplan, autopilot, ralph, or team </Use_When>

<Do_Not_Use_When>

• The request already has concrete file/symbol targets and clear acceptance criteria
• The user explicitly asks to skip planning/interview and execute immediately
• The user asks for lightweight brainstorming only (use plan instead)
• A complete PRD/plan already exists and execution should start </Do_Not_Use_When>

<Why_This_Exists> Execution quality is usually bottlenecked by intent clarity, not just missing implementation detail. A single expansion pass often misses why the user wants a change, where the scope should stop, which tradeoffs are unacceptable, and which decisions still require user approval. This workflow applies Socratic pressure + quantitative ambiguity scoring so orchestration modes begin with an explicit, testable, intent-aligned spec. </Why_This_Exists>

<Depth_Profiles>

• Quick (--quick): fast pre-PRD pass; target threshold <= 0.30; max rounds 5
• Standard (--standard, default): full requirement interview; target threshold <= 0.20; max rounds 12
• Deep (--deep): high-rigor exploration; target threshold <= 0.15; max rounds 20
• Autoresearch (--autoresearch): same interview rigor as Standard, but specialized for $autoresearch mission readiness and .omx/specs/ artifact handoff

Profile max rounds is a hard cap, not a target. Do not continue only to reach a numbered round count. Extra Socratic rigor does not override the active threshold unless the profile/config changes.

If no flag is provided, use Standard.

<Mode_Flags>

• --autoresearch: switch the interview into autoresearch-intake mode for $autoresearch handoff. In this mode, the interview should converge on a validator-ready research mission, write canonical artifacts under .omx/specs/, and preserve the explicit refine further vs launch boundary for downstream skill intake. </Mode_Flags> </Depth_Profiles>

<Execution_Policy>

• Ask ONE question per round (never batch multiple interview rounds into one questions[] form)
• Ask about intent and boundaries before implementation detail
• Target the weakest clarity dimension each round after applying the stage-priority rules below
• Treat every answer as a claim to pressure-test before moving on: the next question should usually demand evidence or examples, expose a hidden assumption, force a tradeoff or boundary, or reframe root cause vs symptom
• Do not rotate to a new clarity dimension just for coverage when the current answer is still vague; stay on the same thread until one layer deeper, one assumption clearer, or one boundary tighter
• Before crystallizing, complete at least one explicit pressure pass that revisits an earlier answer with a deeper, assumption-focused, or tradeoff-focused follow-up
• Gather codebase facts via explore before asking user about internals
• omx explore is deprecated. Use normal repository inspection tools/subagents for simple read-only brownfield fact gathering; use omx sparkshell only for explicit shell-native read-only evidence, and keep ambiguous or non-shell-only investigation on the richer normal path.
• Always run a preflight context intake before the first interview question
• If initial context is oversized or would exceed the prompt budget, do not paste or forward the raw payload into interview prompts; request and record a prompt-safe initial-context summary first
• The oversized initial-context summary gate is blocking: wait for the concise summary before ambiguity scoring, crystallizing artifacts, or any downstream execution handoff
• The summary must preserve goals, constraints, success criteria, non-goals, decision boundaries, and references to any full source documents so downstream consumers receive a prompt-safe but faithful context
• Keep total prompt payloads within a safe budget by summarizing or trimming retained history; preserve newest/highest-signal answers and never let raw oversized context crowd out the current question
• Reduce user effort: ask only the highest-leverage unresolved question, and never ask the user for codebase facts that can be discovered directly
• For brownfield work, prefer evidence-backed confirmation questions such as "I found X in Y. Should this change follow that pattern?"
• Route facts before judgment in the Ouroboros style: before presenting a user-facing interview round, classify whether the needed information is a discoverable fact, a fact needing confirmation, or a human decision. The interview is with the human for judgment, not for facts the agent can inspect.
• When unresolved ambiguity depends on current external best practices, official/upstream guidance, standards, or version-aware behavior, use $best-practice-research as the bounded evidence wrapper before crystallizing requirements or handing off to planning/execution.
• Use these transcript/spec labels only; never use them as omx question source values, and never replace the runtime source: "deep-interview" contract for user-facing deep-interview questions:
  • [from-code][auto-confirmed] — exact, high-confidence codebase facts from manifests/configs or direct source evidence, with no prescription attached.
  • [from-code] — codebase findings that are useful but inferred, pattern-based, or low/medium confidence and therefore need a confirmation-style user-facing round before being treated as settled.
  • [from-research] — externally sourced facts such as API limits, compatibility, or public documentation; facts only, not decisions.
  • [from-user] — goals, preferences, business logic, scope, non-goals, acceptance criteria, tradeoffs, and any decision-bearing interpretation.
• Treat [from-code][auto-confirmed] and other non-user fact discoveries as context/transcript updates, not interview rounds: do not call omx question, do not create a pending deep-interview question obligation, and do not increment the user-facing round number for facts the agent can safely establish.
• Auto-confirm only descriptive facts. If a finding implies what the new feature should do, which pattern it should follow, which tradeoff to accept, or what should stay in/out of scope, route the entire decision-bearing question to the user as [from-user] even when code or research facts are available.
• In attached-tmux Codex CLI, deep-interview uses omx question as the required OMX-owned structured questioning path for every interview round
• When invoking omx question through attached-tmux Bash/tool paths, preserve the leader-pane return target by prefixing the command with OMX_QUESTION_RETURN_PANE=$TMUX_PANE (or a concrete %pane value)
• If you launch omx question in a background terminal, immediately wait for that background terminal to finish and read its JSON answer before scoring ambiguity, asking another round, or handing off
• Treat answers[] as the primary omx question success contract. For a single interview round, read answers[0].answer; use legacy top-level answer only as a compatibility fallback when needed.
• If the current runtime is outside tmux and cannot render omx question, use the native structured question tool when available; otherwise ask exactly one concise plain-text question and wait for the answer
• Re-score ambiguity after each answer and show progress transparently
• Once ambiguity is at or below the active profile threshold, stop ordinary questioning. Run the practical closure audit: crystallize/handoff when readiness gates pass; otherwise ask only the final closure question needed to satisfy a named gate.
• Treat max_rounds as a stop cap, not evidence that more rounds are needed.
• Do not hand off to execution while ambiguity remains above threshold unless user explicitly opts to proceed with warning
• Do not crystallize or hand off while Non-goals or Decision Boundaries remain unresolved, even if the weighted ambiguity threshold is met
• Treat early exit as a safety valve, not the default success path
• Persist mode state for resume safety with CLI-first state commands (omx state write/read --input '<json>' --json); use state_write / state_read only when explicit MCP compatibility is enabled </Execution_Policy>

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
   • Prompt-safe initial-context summary status (not_needed, needed, or recorded)
5. 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 $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)
• 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. 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.

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
• 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
• 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, and any residual-risk warnings across the handoff.

Goal-mode follow-ups

Include these product-facing suggestions when they fit the clarified spec, without removing the existing $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. $ralplan (Recommended)

• 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

2. $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

3. $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

4. $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

5. 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.

<Tool_Usage>

• Use explore for codebase fact gathering
• Use omx question as the OMX-native structured user-input tool for each interview round when an attached tmux renderer is available
• From attached-tmux Bash/tool paths, call it as OMX_QUESTION_RETURN_PANE=$TMUX_PANE omx question ... unless an explicit %pane return target is already known
• If the current runtime is outside tmux and cannot render omx question, use native structured input when available; otherwise ask exactly one concise plain-text question and wait for the answer
• After omx question returns JSON, prefer answers[0].answer / answers[]; use legacy answer only as a fallback for older records
• Use omx state write/read --input '<json>' --json for resumable mode state; state_write / state_read are explicit MCP compatibility fallbacks only
• If the interview cannot ask a required omx question round, persist the blocker as terminal state with active: false and current_phase: "blocked"; do not write a terminal blocked phase with active: true
• Read/write context snapshots under .omx/context/
• Record whether the oversized-context summary gate is not needed, pending, or satisfied before any scoring or handoff step
• Save transcript/spec artifacts under .omx/interviews/ and .omx/specs/ </Tool_Usage>

<Escalation_And_Stop_Conditions>

• User says stop/cancel/abort -> persist state and stop
• Ambiguity stalls for 3 rounds (+/- 0.05) -> force Ontologist mode once
• Max rounds reached -> proceed with explicit residual-risk warning
• All dimensions >= 0.9 -> allow early crystallization even before max rounds </Escalation_And_Stop_Conditions>

<Final_Checklist>

• Preflight context snapshot exists under .omx/context/{slug}-{timestamp}.md
• Oversized initial context, if present, has a prompt-safe summary recorded before ambiguity scoring or downstream handoff
• Ambiguity score shown each round
• Intent-first stage priority used before implementation detail
• Weakest-dimension targeting used within the active stage
• At least one explicit assumption probe happened before crystallization
• At least one persistent follow-up / pressure pass deepened a prior answer
• Challenge modes triggered at thresholds (when applicable)
• Transcript written to .omx/interviews/{slug}-{timestamp}.md
• Spec written to .omx/specs/deep-interview-{slug}.md
• Brownfield questions use evidence-backed confirmation when applicable
• Handoff options provided ($ralplan, $autopilot, $ralph, $team) plus context-sensitive goal-mode suggestions ($ultragoal, $autoresearch-goal, $performance-goal) when applicable
• No direct implementation performed in this mode </Final_Checklist>

## Suggested Config (optional)

Deep-interview reads runtime defaults from the first existing config source in this order:

1. Repository-local .omx/config.toml
2. Repository-root omx.toml
3. User-global ~/.omx/config.toml

This section is currently a deep-interview-specific runtime override surface, not a general replacement for Codex config.toml or .omx-config.json model/env routing. Malformed config files are ignored fail-soft so $deep-interview activation can continue with built-in defaults. Explicit --quick, --standard, or --deep invocation flags override defaultProfile.

[omx.deepInterview]
defaultProfile = "standard"
quickThreshold = 0.30
standardThreshold = 0.20
deepThreshold = 0.15
quickMaxRounds = 5
standardMaxRounds = 12
deepMaxRounds = 20
enableChallengeModes = true

Resume

If interrupted, rerun $deep-interview. Resume from persisted mode state via omx state read --input '{"mode":"deep-interview"}' --json.

Recommended 3-Stage Pipeline

deep-interview -> ralplan -> autopilot

• Stage 1 (deep-interview): clarity gate
• Stage 2 (ralplan): feasibility + architecture gate
• Stage 3 (autopilot): execution + QA + validation gate