Socratic deep interview with mathematical ambiguity gating before explicit execution approval
SkillScore55Maintained
Automatic
◆Product Management pack
Last verified 8/10/2026
What it changes
Passed 7 of 13 test cases with the skill, and 2 of 13 without it.
Without skill18%
With skill55%
Checks it passed that the model alone missed
The calculated ambiguity percentage is 35%.
The calculated ambiguity percentage is 22%.
The calculated ontology stability ratio is 1.0 (100%).
and 10 more in the full report
9 fixed3 passed either way9 still failing1 broke
Pass-rate lift
+36 pp
Tokens
+661%
Agent turns
0%
Response time
-38%
Model gemini-3.6-flashMeasured 8/10/2026v112 of 22 cases passed with skill · 13 comparable
Tokens, turns and time describe resource use, not a dollar price.
See it in action
One of 9 test cases the skill fixed. Same model, same prompt, with and without the skill.
1 of 9
Prompt
Calculate the exact overall ambiguity percentage for a greenfield feature where the current dimension scores are Goal Clarity = 0.80, Constraint Clarity = 0.50, and Success Criteria Clarity = 0.60.
What was checked, without and with the skill
Checked
Without skill
With skill
The calculated ambiguity percentage is 35%.
Missed
Passed
case-10 · gemini-3.6-flash · 8/10/2026 · answers are capped and redacted
What's inside
The instructions your model reads when the skill loads.
SKILL.md792 linessingle file
<Use_When>
User has a vague idea and wants thorough requirements gathering before execution
User says "deep interview", "interview me", "ask me everything", "don't assume", "make sure you understand"
User says "ouroboros", "socratic", "I have a vague idea", "not sure exactly what I want"
User wants to avoid "that's not what I meant" outcomes from autonomous execution
Task is complex enough that jumping to code would waste cycles on scope discovery
User wants mathematically-validated clarity before committing to execution
</Use_When>
<Do_Not_Use_When>
User has a detailed, specific request with file paths, function names, or acceptance criteria -- execute directly
User wants to explore options or brainstorm -- use omc-plan skill instead
User wants a quick fix or single change -- delegate to executor or ralph
User says "just do it" or "skip the questions" without an explicit execution path -- respect their intent by ending interview and writing a pending approval spec, not by mutating files or delegating execution
User already has a PRD or plan file and explicitly asks to execute it -- use the requested execution skill with that plan
</Do_Not_Use_When>
<Why_This_Exists>
AI can build anything. The hard part is knowing what to build. OMC's autopilot Phase 0 expands ideas into specs via analyst + architect, but this single-pass approach struggles with genuinely vague inputs. It asks "what do you want?" instead of "what are you assuming?" Deep Interview applies Socratic methodology to iteratively expose assumptions and mathematically gate readiness, ensuring the AI has genuine clarity before spending execution cycles.
Inspired by the Ouroboros project which demonstrated that specification quality is the primary bottleneck in AI-assisted development.
</Why_This_Exists>
<Execution_Policy>
Ask ONE question at a time -- never batch multiple questions
Target the WEAKEST clarity dimension with each question
Before Round 1 ambiguity scoring, run a one-time Round 0 topology enumeration gate that confirms the top-level component list and locks it into state
Make weakest-dimension targeting explicit every round: name the weakest dimension, state its score/gap, and explain why the next question is aimed there
Gather codebase facts via explore agent BEFORE asking the user about them
For brownfield confirmation questions, cite the repo evidence that triggered the question (file path, symbol, or pattern) instead of asking the user to rediscover it
Score ambiguity after every answer -- display the score transparently
When the locked topology has multiple active components, score and target each component explicitly so depth-first clarity on one component cannot hide ambiguity in siblings
Keep prompt payloads budgeted: summarize or trim oversized initial context/history before composing question, scoring, spec, or handoff prompts
If the user's initial context is oversized, create a concise prompt-safe summary first and wait for that summary before ambiguity scoring, question generation, or downstream execution handoff
Do not proceed to execution until ambiguity ≤ the resolved threshold for this run and the user explicitly approves a scoped execution path
Allow early exit with a clear warning if ambiguity is still high