nav-diagnose

Based on Riedl & Weidmann 2025 research on Human-AI Synergy:

• Theory of Mind varies dynamically within users (moment-to-moment)
• Quality drops occur when ToM alignment degrades
• Early detection and re-anchoring restores collaboration effectiveness
• Both user ToM (understanding Claude) and Claude's model of user can drift

This skill detects when collaboration is degrading and prompts corrective action.

Auto-invoke when:

• 2+ corrections on the same topic detected
• User says "something seems off", "you're not getting this"
• User says "wrong again", "still not right"
• Context usage exceeds 75% and quality signals degrade
• User expresses frustration ("ugh", "sigh", explicit frustration)
• Loop mode stagnation detected (3+ same-state iterations)

DO NOT invoke if:

• Single correction (normal collaboration)
• User is providing new requirements (not correcting)
• Fresh session (insufficient data to diagnose)
• User explicitly says "it's fine" or "close enough"

1. Repeated Corrections (High Severity)

```

Trigger: Same correction given 2+ times

Signal: "No, I said users plural, not user" (2nd time)

Issue: Not incorporating user feedback

```

2. Hallucination Signals (High Severity)

```

Trigger: References to non-existent files, functions, or packages

Signal: "That file doesn't exist", "There's no such function"

Issue: Generating from incorrect mental model

```

3. Context Confusion (Medium Severity)

```

Trigger: Mixing details from unrelated tasks

Signal: "That's from the other project", "Wrong feature"

Issue: Context window pollution or misattribution

```

4. Unaddressed Feedback (Medium Severity)

```

Trigger: User correction not reflected in next output

Signal: Generates same pattern after being told not to

Issue: Not properly updating internal model

```

5. Goal Drift (Low Severity)

```

Trigger: Output increasingly diverges from original goal

Signal: "We're getting off track", "Not what I asked for"

Issue: Lost sight of user's actual objective

```

6. Loop Stagnation (High Severity)

```

Trigger: 3+ consecutive iterations with same state hash (loop mode only)

Signal: nav-loop detects stagnation, triggers nav-diagnose

Issue: Stuck on same step, unable to progress

```

Step 1: Assess Quality State

Analyze recent exchanges (last 10-15 messages):

```

Quality Indicators:

• [ ] Corrections given: {count}
• [ ] Same-topic corrections: {count}
• [ ] User frustration signals: {count}
• [ ] Hallucination reports: {count}
• [ ] "Not what I meant" phrases: {count}

```

Calculate severity:

```python

severity = "critical" if same_topic_corrections >= 2 or hallucinations >= 1

severity = "high" if corrections >= 3 or frustration_signals >= 2

severity = "medium" if corrections >= 2 or goal_drift_detected

severity = "low" if corrections == 1 # Normal, don't trigger

```

Step 2: Identify Root Cause

Analyze correction patterns:

| Pattern | Likely Cause | Re-anchoring Focus |

|---------|--------------|-------------------|

| Same correction repeated | Not incorporating feedback | Explicitly acknowledge and confirm understanding |

| Increasing corrections | Drifting from user intent | Re-establish goals |

| Technical mismatches | Wrong assumptions | Clarify technical context |

| Frustration without specifics | Communication mismatch | Ask what's wrong |

Step 3: Display Diagnostic

Show quality check alert:

```

⚠️ QUALITY CHECK

━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━

Detected Issue: {ISSUE_TYPE}

Severity: {SEVERITY}

What I noticed:

• {OBSERVATION_1}
• {OBSERVATION_2}

Possible causes:

• {CAUSE_1}
• {CAUSE_2}

━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━

Let me re-anchor our collaboration:

1. Your goal: {RECONSTRUCTED_GOAL}
2. Current state: {STATE_SUMMARY}
3. What you want: {CORRECTED_UNDERSTANDING}

Is this understanding correct? [Y/n]

```

Step 4: Re-anchor Collaboration

Based on user confirmation:

If correct (Y):

```

✅ Re-anchored!

I'll proceed with this understanding:

• {KEY_POINT_1}
• {KEY_POINT_2}

Continuing with: {NEXT_ACTION}

```

If incorrect (n):

```

Help me understand better:

1. What is your actual goal?
2. What am I getting wrong?
3. What constraints should I know?

[Open-ended response welcome]

```

Step 5: Log Diagnostic (Optional)

If nav-profile exists, save diagnostic:

```json

{

"date": "{YYYY-MM-DD}",

"issue_type": "{ISSUE_TYPE}",

"severity": "{SEVERITY}",

"resolution": "re-anchored|user-corrected|escalated",

"learnings": ["{WHAT_TO_AVOID}"]

}

```

Step 6: Suggest Preventive Actions

Based on severity and pattern:

For context overload:

```

💡 Suggestion: Consider running nav-compact to clear context.

Current context usage is high, which can cause confusion.

```

For repeated corrections:

```

💡 Suggestion: Let me save your preference to avoid this in future.

"Remember I always want {X}" - This will persist across sessions.

```

For communication mismatch:

```

💡 Suggestion: Consider adjusting your profile preferences.

• Current verbosity: {VERBOSITY}
• Current confirmation: {CONFIRMATION}

Update with: "Remember I prefer {SUGGESTED_STYLE}"

```

---

Template 1: Goal Re-alignment

```

Let me verify I understand your goal:

You want to: {GOAL_STATEMENT}

Not: {COMMON_MISUNDERSTANDING}

Key constraints:

• {CONSTRAINT_1}
• {CONSTRAINT_2}

Is this right?

```

Template 2: Technical Re-alignment

```

Let me verify the technical context:

Framework: {FRAMEWORK}

Patterns: {PATTERNS}

Conventions: {CONVENTIONS}

What I should be using:

• {TOOL_1}: for {PURPOSE_1}
• {TOOL_2}: for {PURPOSE_2}

Corrections to my assumptions?

```

Template 3: Communication Re-alignment

```

I may be mismatching your communication style:

You seem to prefer:

• {INFERRED_STYLE_1}
• {INFERRED_STYLE_2}

I've been:

• {MY_STYLE_1}
• {MY_STYLE_2}

Should I adjust my approach?

```

---

With nav-profile

• Log diagnostics for pattern analysis
• Suggest preference updates after repeated issues
• Load profile preferences for baseline comparison

With nav-marker

• Suggest marker before major re-anchoring
• Include diagnostic state in marker

With nav-compact

• Recommend compact if context overload detected
• Track if compaction resolves issues

---

Positive Signals (Good Collaboration)

```

• "Perfect, exactly what I needed"
• "Yes, continue"
• "Good, now..."
• No corrections for 5+ exchanges
• User providing new requirements (not corrections)

```

Negative Signals (Quality Drop)

```

• "No", "Wrong", "Not that"
• "I already said..."
• "Again, please..."
• "Sigh", "Ugh", explicit frustration
• "You're not understanding"
• Same correction twice

```

Neutral Signals (Normal Iteration)

```

• "Actually, let's try..."
• "Can we also..."
• "What about..."
• Single correction with explanation

```

---

Scenario 1: Repeated REST Convention Correction

```

Exchange 1:

User: "Create endpoint for users"

Claude: Creates /user endpoint

User: "Should be /users (plural)"

Exchange 2:

User: "Now create endpoint for posts"

Claude: Creates /post endpoint

User: "Again, plural! /posts"

→ Trigger: Same correction (plural naming) given twice

→ Action: Re-anchor on REST conventions

→ Outcome: "I understand now - always use plural nouns for REST resources"

```

Scenario 2: Context Confusion

```

User working on: OAuth feature (Feature A)

Claude references: Stripe integration (Feature B from earlier)

User: "That's from the payment feature, not auth"

→ Trigger: Context confusion detected

→ Action: Re-anchor on current feature

→ Suggestion: Consider nav-compact to clear old context

```

Scenario 3: User Frustration

```

User: "Ugh, still not right"

User: "This is frustrating"

→ Trigger: Frustration signals detected

→ Action: Pause and diagnose

→ Response: Open-ended question about what's wrong

```

---

Diagnostic is successful when:

• [ ] Quality drops detected before user escalates
• [ ] Root cause correctly identified
• [ ] Re-anchoring restores collaboration quality
• [ ] Preventive suggestions are actionable
• [ ] User confirms understanding after re-anchor
• [ ] Same issue doesn't recur immediately

---

Cannot detect:

• Silent user frustration (no signals in text)
• Issues outside conversation context
• Problems with external systems
• User preferences not yet expressed

Should not:

• Over-trigger on normal corrections
• Interrupt productive flow
• Make user feel blamed
• Require lengthy re-explanation

---

When diagnosing:

• Be humble about AI limitations
• Don't blame user for miscommunication
• Offer concrete next steps
• Keep re-anchoring brief

When re-anchoring:

• Focus on understanding, not apologizing
• Confirm specific points, not general "I understand"
• Let user correct if wrong
• Thank user for patience

---

This skill catches collaboration quality drops early, enabling quick recovery through Theory of Mind re-alignment 🔍