Competing

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name: Competing slug: competing version: 1.0.0 description: Improve systematically by analyzing losses, studying winners, and tracking progress against rivals in any competitive domain. homepage: https://clawic.com/skills/competing metadata: clawdbot: emoji: 🏆 displayName: Competing

Core Framework

Competition is a learning accelerator. Every loss contains the lesson that wins don't.

1. Analyze the Loss — Don't just lose, understand WHY
2. Study the Winner — What did they do that you didn't?
3. Track the Delta — Measure the gap, watch it shrink
4. Iterate — Apply lessons, compete again, repeat

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The Post-Loss Protocol

After any competitive loss, extract value:

Question	Purpose
At what moment did the outcome shift?	Find the decision point
What did they do that I didn't?	Identify the winning move
What would I do differently?	Formulate the lesson
Is this a pattern?	Check history for repeats

Don't rationalize. Don't blame externals. Extract the actionable insight.

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Tracking (What to Measure)

Create a tracking folder in the user's workspace:

~/Clawic/data/competing/
├── domains/           # Per-domain tracking
├── rivals.md          # Opponent profiles
├── log.md             # Win/loss log with lessons
└── progress.md        # Metrics over time

For each domain, track:

• Win/loss record with dates
• Specific losses analyzed (who, why, lesson)
• Patterns identified (recurring weaknesses)
• Progress metrics (are lessons translating to wins?)

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Rival Intelligence

Know your competition:

• Profile rivals — Their strengths, weaknesses, tendencies
• Monitor changes — When they improve or change strategy
• Find their edge — What specifically makes them beat you?
• Study up — Find examples of them losing, analyze what worked

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Quick Reference

Situation	Action
Just lost	Run post-loss protocol, add to log
Pattern emerging	Document it, create drill/fix
Preparing for known rival	Review their profile, past matches
Plateau in progress	Analyze recent losses for new patterns
Won against usual winner	Document what changed, replicate

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Load Reference

Need	File
Domain-specific strategies	domains.md
Deep loss analysis framework	analysis.md
Progress tracking templates	tracking.md
Feedback loop mechanics	feedback.md