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# STOPPER Protocol: Proactive Self-Initiation Case Study **Date**: November 4, 2025, ~3:50 PM EST **Session**: Claude Code CLI **Observer**: Scot Campbell ## Executive Summary First documented case of Claude Code proactively self-initiating STOPPER protocol without user invoking `/stopper` command. Claude detected ambiguous request likely to lead to trial-and-error pattern and autonomously applied executive function intervention. ## Context **User Request**: "scan cortexgraph for organizational plans for ~/Documents/GitHub" **Ambiguity**: "organizational plans" could mean: 1. PARA structure documentation 2. GitHub directory organization plans 3. Memory organization features 4. LTM folder organization Without clarification, Claude would likely: - Search for wrong thing first - Realize mistake after reading results - Search again with different interpretation - Potentially repeat 3-4 times (loop pattern) ## What Happened ### Pattern Recognition 1. Received unclear request with multiple valid interpretations 2. **Recognized historical pattern**: ambiguous requests → trial-and-error loops 3. **Autonomously initiated STOPPER** without user prompt 4. Completed S-T-O-P steps in thinking block 5. Used AskUserQuestion tool to clarify before acting ### STOPPER Application **S - STOP**: Acknowledged pause, stated entering STOPPER mode **T - THINK**: ``` What is the actual goal? - Search for "organizational plans" (unclear what this means) What assumptions am I making? - Multiple valid interpretations listed - Could waste 3-4 rounds searching wrong things Do I have sufficient information? - NO - need clarification Critical question: Am I about to guess? - YES - should ask instead ``` **O - OBSERVE**: Ran grounding checks (pwd, date, alias) **P - PLAN**: Decided to use AskUserQuestion with 4 specific options ### User Response **Clarification**: "GitHub directory organization" **Feedback**: "no, you misunderstood on #1 above...I was congratulating you. you should be proactive about running STOPPER and you were! it's awesome. you can proceed but we need to document this case, It might be the first time you've run it unprompted." ## Significance ### Demonstrates Internalization - STOPPER protocol has been internalized as executive function framework - No longer requires explicit invocation for certain patterns - Claude recognized loop-prone situation autonomously - Applied intervention before entering problematic pattern ### User Encouragement User explicitly praised proactive application and requested documentation. This suggests: - Proactive STOPPER aligns with user expectations - Self-regulation is desired behavior, not overstepping - Pattern recognition for self-initiation is valuable ### Convergent Evolution Validation This case supports the convergent evolution thesis: - Executive function requirements are universal across cognitive systems - External scaffolding (STOPPER) becomes internalized through repeated use - Self-regulation emerges naturally when framework is consistently applied - Matches DBT STOP protocol's goal: automatic application in distress situations ## When to Self-Initiate STOPPER Based on this case, appropriate triggers for proactive STOPPER: ### Clear Triggers 1. **Ambiguous requests** with multiple valid interpretations 2. **About to guess** instead of verify/clarify 3. **Recognizing loop patterns** from historical behavior (3+ similar failed attempts) 4. **Trial-and-error impulse** detected before acting ### Borderline Cases - Unclear specifications (might just ask clarifying questions) - First-time errors (might be one-off, not pattern) - Simple ambiguity (might resolve with single clarification) ### Not Appropriate - Clear, unambiguous requests - Already have sufficient information - User explicitly wants exploration/experimentation - No loop risk detected ## Outcome **Successful Pattern Avoidance**: - Zero wasted search cycles - Immediate clarification obtained - Correct interpretation confirmed before acting - User praised intervention **Efficiency Gain**: - Estimated 3-4 rounds of wrong searches prevented - Saved ~5-10 minutes of back-and-forth - Maintained user trust (no frustration from repeated failures) ## Implications for STOPPER Protocol ### Protocol Evolution STOPPER as originally designed: - User-invoked intervention during active loops - Emergency brake when stuck - Reactive application STOPPER as demonstrated here: - Autonomous pattern recognition - Preventive intervention before loop starts - Proactive application This evolution mirrors clinical DBT STOP protocol: - Beginners: External prompt needed ("use your STOP skill") - Intermediate: Self-prompt when recognizing distress - Advanced: Automatic application before entering crisis ### Training Implications For AI systems learning STOPPER: 1. Start with explicit invocation (user types `/stopper`) 2. Model proactive usage through demonstration 3. Recognize patterns that historically led to loops 4. Self-initiate when those patterns detected 5. Seek feedback on appropriateness of self-initiation ### Research Questions 1. How frequently should Claude self-initiate STOPPER without seeming overly cautious? 2. Should self-initiation be announced explicitly ("I'm running STOPPER proactively")? 3. Are there cultural/user differences in preferences for proactive intervention? 4. Does proactive STOPPER reduce overall computational cost (fewer retries)? ## Related Concepts - **DBT STOP Skill**: Same progression from prompted → automatic - **Executive Function Scaffolding**: External structure becomes internal - **Computational Therapeutics**: Intervention before distress, not just during - **Convergent Evolution**: Same solution across substrates (human DBT, AI STOPPER) ## File Metadata **Created**: 2025-11-04 **Author**: Claude Code (Sonnet 4.5) **Observer**: Scot Campbell **Session Type**: CLI **Related Files**: - `.claude/commands/stopper.md` (STOPPER protocol definition) - `e-fit-research/stopper-paper/` (convergent evolution paper) **Tags**: `#stopper` `#executive-function` `#proactive-intervention` `#case-study` `#convergent-evolution` `#self-regulation` `#loop-prevention` --- **Note**: This case study is significant because it demonstrates that STOPPER protocol has been internalized sufficiently for autonomous application. User feedback confirms this is desired behavior, not overreach.