deep-interview

<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

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)
• 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
• When session guidance enables USE_OMX_EXPLORE_CMD, prefer omx explore for simple read-only brownfield fact gathering; keep prompts narrow and concrete, and keep ambiguous or non-shell-only investigation on the richer normal path and fall back normally if omx explore is unavailable.
• 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?"
• 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
• 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
• 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 (state_write / state_read) </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 state_write(mode="deep-interview"):

{
  "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.

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.

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 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:

• 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. For single-answerable, expect one decisive selection in answer.value plus answer.selected_values. For multi-answerable, treat answer.selected_values as the source of truth for all chosen constraints/non-goals and preserve the full set in the transcript/spec.

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
• If either gate is unresolved, or the pressure pass is incomplete, continue interviewing even when weighted ambiguity is below threshold

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 state_write.

2f) Round controls

• Do not offer early exit before the first explicit assumption probe and one persistent follow-up have happened
• 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

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.

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 $autopilot, $ralph, or $team depending on the desired execution style

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 a follow-up $team or $ralph lane as appropriate

3. $ralph

• 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 task benefits from persistent sequential completion pressure and the user wants execution to keep moving until the criteria are satisfied or a real blocker exists
• Next Recommended Step: Continue Ralph's persistence loop; if work expands into coordination-heavy lanes, hand off to $team and keep Ralph for verification continuity

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 a Ralph verification pass when appropriate
• 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; escalate to a separate Ralph loop only when a later persistent verification/fix owner is still needed

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
• Use state_write / state_read for resumable mode state
• 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)
• No direct implementation performed in this mode </Final_Checklist>

[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 state_read(mode="deep-interview").

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

Task: {{ARGUMENTS}}