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 OMQ 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 omq autoresearch launch readiness and .omq/specs/ mission/sandbox artifact handoff

If no flag is provided, use Standard.

<Mode_Flags>

• --autoresearch: switch the interview into autoresearch-intake mode for omq autoresearch handoff. In this mode, the interview should converge on a launch-ready research mission, write canonical artifacts under .omq/specs/, and preserve the explicit refine further vs launch boundary for downstream CLI 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_OMQ_EXPLORE_CMD, prefer omq 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 omq explore is unavailable.
• Always run a preflight context intake before the first interview 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 Qwen Code, prefer request_user_input when available; if unavailable, fall back to concise plain-text one-question turns
• 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 .omq/context/{slug}-*.md.
3. 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
4. Save snapshot to .omq/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": ".omq/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

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 structured user-input tooling available in the runtime (AskUserQuestion / equivalent) and present:

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

{question}

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

Spec should include:

• Metadata (profile, rounds, final ambiguity, threshold, context type)
• Context snapshot reference/path (for ralplan/team reuse)
• Clarity breakdown table
• Intent (why the user wants this)
• Desired Outcome
• In-Scope
• Out-of-Scope / Non-goals
• Decision Boundaries (what OMQ 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 omq autoresearch, or the skill is invoked with --autoresearch, keep the interview domain-specific and emit launch-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: .omq/specs/deep-interview-autoresearch-{slug}.md
• Launch artifact bundle: .omq/specs/autoresearch-{slug}/mission.md, .omq/specs/autoresearch-{slug}/sandbox.md, and .omq/specs/autoresearch-{slug}/result.json
• Launch artifact directory: .omq/specs/autoresearch-{slug}/
• Required artifact sections:
  • Mission Draft
  • Evaluator Draft
  • Launch Readiness
  • Seed Inputs
  • Confirmation Bridge
• Required launch artifacts under .omq/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 omq autoresearch can consume it directly
• Confirmation bridge: after artifact generation, offer at least refine further and launch; do not launch detached tmux until the user explicitly confirms launch
• 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: .omq/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 .omq/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: .omq/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: .omq/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: .omq/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 request_user_input / structured user-input tool for each interview round when available
• If structured question tools are unavailable, use plain-text single-question rounds and keep the same stage order
• Use state_write / state_read for resumable mode state
• Read/write context snapshots under .omq/context/
• Save transcript/spec artifacts under .omq/interviews/ and .omq/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 .omq/context/{slug}-{timestamp}.md
• 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 .omq/interviews/{slug}-{timestamp}.md
• Spec written to .omq/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>

## Suggested Config (optional)

[omq.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}}