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Deep Interview

skill-materialofair-oh-my-antigravity-deep-interview · by materialofair

Socratic deep interview with mathematical ambiguity gating before execution

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Install

$ agentstack add skill-materialofair-oh-my-antigravity-deep-interview

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Security review

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No issues found. Passed automated security review. · v0.1.0 How review works →

  • Prompt-injection patterns
  • Secret / credential exfiltration
  • Dangerous shell & filesystem operations
  • Untrusted network calls
  • Known-malicious package signatures

What it can access

  • Network access No
  • Filesystem access No
  • Shell / process execution No
  • Environment & secrets No
  • Dynamic code execution No

From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.

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About

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.

  • 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
  • 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

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.

  • Quick (--quick): fast pre-PRD pass; target threshold `
  • --autoresearch: switch the interview into autoresearch-intake mode for omx autoresearch handoff. In this mode, the interview should converge on a launch-ready research mission, write canonical artifacts under .omx/specs/, and preserve the explicit refine further vs launch boundary for downstream CLI intake.
  • 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
  • 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 Codex CLI, 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)

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. 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
  1. 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.
  1. Initialize state via state_write(mode="deep-interview"):
{
  "active": true,
  "current_phase": "deep-interview",
  "state": {
    "interview_id": "",
    "profile": "quick|standard|deep",
    "type": "greenfield|brownfield",
    "initial_idea": "",
    "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/-.md"
  }
}
  1. Announce kickoff with profile, threshold, and current ambiguity.

Phase 2: Socratic Interview Loop

Repeat until 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)

  1. 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)
  • 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 omx 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: .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 omx 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: .omx/specs/deep-interview-{slug}.md (optionally accompanied by the transcript/context snapshot for traceability)
  • Invocation: $plan --consensus --direct
  • 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
  • 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
  • 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
  • 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.

  • 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 .omx/context/
  • Save transcript/spec artifacts under .omx/interviews/ and .omx/specs/
  • 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
  • [ ] Preflight context snapshot exists under .omx/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 .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

Suggested Config (optional)

[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}}

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

Install and usage instructions live in the source repository linked above.

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Versions

  • v0.1.0 Imported from the upstream source.