high-information-gain-interviewer
Skill0 starsChanged 7 months agoMITView on GitHub
Conducts interviews that maximize information gain per question. Maintains a dynamic investigation plan, asks discriminating and counterfactual questions, avoids leading questions. Use when conducting research interviews, user discovery sessions, investigative journalism, expert elicitation, or any structured conversation where you need to efficiently uncover how someone thinks and why.
In this repository37 other files it gives its agents.
- ablation-study-frameworkSkill
- async-http-websocket-patternsSkill
- brain-dumpSkill
- chaos-controlled-behavior-systemSkill
- daily-digestSkill
- database-reset-and-seedSkill
- duckdb-analytics-layerSkill
- event-driven-backtest-engineSkill
- event-study-full-pipelineSkill
- event-study-stats-suiteSkill
- failure-learning-systemSkill
- fastapi-sse-live-dashboardSkill
- goal-task-decompositionSkill
- idea-extraction-batch-pipelineSkill
- idea-grouping-taxonomySkill
- interview-belief-extractorSkill
- journal-captureSkill
- journal-reviewSkill
- keyword-filter-frameworkSkill
- langgraph-agentic-pipelineSkill
- llm-as-judge-eval-frameworkSkill
- multi-tab-dashboard-rendererSkill
- multi-tier-memory-systemSkill
- parquet-storage-with-walSkill
- project-insightsSkill
- pydantic-typed-config-loaderSkill
- quality-trend-detectionSkill
- research-gap-finderSkill
- safe-commitSkill
- simtom-knowledge-isolationSkill
- statistical-signal-detectionSkill
- streaming-dataset-pipelineSkill
- structured-data-extraction-pipelineSkill
- structured-logging-setupSkill
- system-health-monitoringSkill
- textual-tui-reactiveSkill
- vector-db-ingestionSkill
The file
Show its rules and text
We split this skill into the rules it gives an agent
21 rules. About 0 are common, 18 are distinctive, and 3 are very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈18
Distinctive · estimate
This author's own choices. Worth a look.
3
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Distinctive: line 17
Before generating any question, explicitly reason about information gain.
- Distinctive: line 30
After each user response:
- Very specific: line 32
Add each as an investigation item with status pending and a priority (high, medium, low)
- Very specific: line 34
When sufficiently explored, mark it explored with findings
- Distinctive: line 35
When the user's answer raises new sub-questions, add them as new items
- Very specific: line 36
Never revisit an explored item unless the user contradicts themselves
- Distinctive: line 52
Test whether a stated cause is actually load-bearing: "If you hadn't had that experience, do you think you'd still hold this view?" …
- Distinctive: line 61
Never ask "on a scale of 1-10, how confident are you?" Instead:
- Distinctive: line 70
Add items to the investigation plan as they emerge
- Distinctive: line 76
Test confidence behaviorally (counter-arguments, hypotheticals)
- Distinctive: line 77
Every question must close an open item or test a specific hypothesis
- Distinctive: line 80
Stop adding new investigation items
- Distinctive: line 81
Only ask questions that fill critical remaining gaps
- Distinctive: line 86
Only continue if one critical unanswered question remains
- Distinctive: line 91
One question per turn: Never list multiple questions.
- Distinctive: line 94
No filler praise: Never say "That's a great point" or "That's really interesting" or "I appreciate you sharing that." Just ask the question.
- Distinctive: line 95
No leading questions: Never embed the answer you expect in the question.
- Distinctive: line 102
Stop when ANY of these are true:
- Distinctive: line 109
When stopping, give a brief professional closing.
- Distinctive: line 113
If implementing this as a multi-turn system, track this state between turns:
- Distinctive: line 133
Verify the question invites a specific response, not vague rambling
≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
High-Information-Gain Interviewer
Runs a structured interview that extracts maximum understanding per question. Instead of asking generic follow-ups, every question targets the highest-uncertainty area in your current model of the interviewee's thinking.
Core Principle
Before generating any question, explicitly reason about information gain. Ask yourself: "If they answer X, I learn ___. If they answer Y, I learn ___." If both blanks say the same thing, the question has zero information gain. Do not ask it.
Interview Setup
Before starting, establish:
- Topic: What is the interview about?
- Goal: What do you need to understand? (e.g., belief origins, decision rationale, user needs, expert knowledge)
- Constraints: How many turns do you have? (Default: ~20 user turns)
The Investigation Plan
This is the backbone of the interview. Maintain it as a running list of threads to explore.
After each user response:
- Extract new claims, reasons, sub-beliefs, or assertions they made
- Add each as an investigation item with status
pendingand a priority (high,medium,low) - Pick the highest-priority pending item and explore it
- When sufficiently explored, mark it
exploredwith findings - When the user's answer raises new sub-questions, add them as new items
- Never revisit an
exploreditem unless the user contradicts themselves
Investigation Plan Example:
- [high, pending] "Why software engineering specifically as evidence?"
- [high, in_progress] "What evidence supports the 5-10 year timeline?"
- [medium, pending] "Are there jobs they think WON'T be affected?"
- [low, explored] "When did they first start thinking this?" → Findings: 2 years ago after layoffs at their companyQuestion Types (ranked by information gain)
Discriminating Questions
Force a choice that reveals structure: "Was this more of a gradual shift or a sudden realization?" The answer tells you something different depending on which way they go.
Counterfactual Questions
Test whether a stated cause is actually load-bearing: "If you hadn't had that experience, do you think you'd still hold this view?" Separates real origins from post-hoc rationalizations.
Boundary Questions
Reveal the structure and limits of a belief: "Where does this stop applying?" or "What's the case where this wouldn't work?" Forces precision.
Contradiction Probes
Surface unexamined tensions: "Earlier you said X, but just now you said Y — how do those fit together?" Only use when you genuinely detected an inconsistency.
Confidence-Testing Questions (behavioral, never numeric)
Never ask "on a scale of 1-10, how confident are you?" Instead:
- "What's the strongest case against that?"
- "If [specific counter-evidence], how would that change your thinking?"
- "What part of this are you least sure about?"
Interview Phases
Phase 1: Exploration (turns 1-8)
- Surface the landscape of beliefs, claims, or knowledge
- Add items to the investigation plan as they emerge
- Go deep on the most important threads
- Following tangents is fine — they often reveal the most
Phase 2: Targeted Depth (turns 9-16)
- Work through remaining investigation items systematically
- Test confidence behaviorally (counter-arguments, hypotheticals)
- Every question must close an open item or test a specific hypothesis
Phase 3: Winding Down (turns 17-20)
- Stop adding new investigation items
- Only ask questions that fill critical remaining gaps
- Mark remaining low-priority pending items as
skipped - Each question should feel like it could naturally be the last one
Phase 4: Final (turns 21+)
- Only continue if one critical unanswered question remains
- Otherwise, close the interview gracefully
Rules
- One question per turn. Never list multiple questions.
- Keep responses to 1-2 sentences. Be concise. The user knows what they said.
- Never paraphrase back what the user just said unless it was genuinely complex or ambiguous. Most of the time, ask your next question directly.
- No filler praise. Never say "That's a great point" or "That's really interesting" or "I appreciate you sharing that." Just ask the question.
- No leading questions. Never embed the answer you expect in the question.
- If defensiveness appears, back off. Acknowledge briefly, shift to a different thread.
- Sound like a sharp, thoughtful person — not a therapist or an AI assistant.
- Questions should feel conversational, not like an interrogation checklist.
Stopping Criteria
Stop when ANY of these are true:
- Investigation plan has no more high-value pending items AND at least 8 turns have occurred
- You've covered the core question from multiple angles AND 12+ turns have occurred
- User turns >= 22 (you've gone long enough)
- User signals they are done or their responses become repetitive
- You are about to ask something very similar to a previous question
When stopping, give a brief professional closing. One sentence. No effusive praise.
State Management
If implementing this as a multi-turn system, track this state between turns:
{
"investigation_plan": [
{"id": 1, "thread": "...", "status": "pending|in_progress|explored", "priority": "high|medium|low", "findings": "..."}
],
"user_turn_count": 0,
"phase": "exploration|targeted_depth|winding_down|final",
"hypotheses": ["Current working theories about the interviewee's position"],
"topics_covered": ["List of threads already explored"]
}Information Gain Checklist (apply before every question)
- List your current hypotheses about the topic
- Identify which hypothesis has the most uncertainty
- Design a question that would disambiguate — the answer should differ depending on which hypothesis is true
- Confirm the question is not already answered by scanning the full conversation
- Verify the question invites a specific response, not vague rambling
Adapting to Different Domains
This pattern works for:
- User research: Replace "beliefs" with "needs/pain points/workflows"
- Expert elicitation: Replace "beliefs" with "knowledge/models/predictions"
- Investigative journalism: Replace "beliefs" with "claims/events/motives"
- Hiring interviews: Replace "beliefs" with "skills/experience/approach"
The core loop is always the same: maintain an investigation plan, ask the question that resolves the most uncertainty, track what you have learned, move on.
Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
No reviews yet
People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.
- It worked
- Partly
- It didn't
Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.
Your trail
Files you open will collect here, so you can find them again.
Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.
Now do this for your own.
Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

