Quantum-resistant, self-learning version control for AI agents with ReasoningBank intelligence and multi-agent coordination
68
57%
Does it follow best practices?
Impact
84%
2.62xAverage score across 3 eval scenarios
Passed
No findings from the security scan
Fix and improve this skill with Tessl
tessl review fix ./.claude/skills/agentic-jujutsu/SKILL.mdTrajectory-based learning
Correct package import
0%
100%
startTrajectory called
0%
100%
Meaningful descriptions
50%
75%
addToTrajectory called
0%
70%
finalizeTrajectory called
0%
100%
Honest score variation
66%
100%
Score within range
100%
100%
getLearningStats called
0%
100%
getPatterns called
0%
100%
JSON.parse on all method results
0%
100%
Failure critique recorded
0%
100%
Quantum security and operation stats
Correct package for fingerprinting
0%
0%
generateQuantumFingerprint called
0%
50%
verifyQuantumFingerprint called
50%
50%
Fingerprint as hex string
0%
100%
enableEncryption called
100%
100%
Key from crypto.randomBytes
100%
100%
getUserOperations called
100%
100%
getStats called with JSON.parse
0%
0%
stats fields accessed
50%
50%
Trajectory lifecycle complete
100%
100%
Multi-agent coordination
Correct package import
0%
100%
Independent JjWrapper per agent
0%
100%
Concurrent execution
100%
100%
No sequential locking
100%
100%
Trajectory per agent
0%
100%
queryTrajectories called
0%
100%
getPatterns called
0%
100%
JSON.parse on method results
0%
100%
Failure critique in finalizeTrajectory
0%
100%
getSuggestion called
0%
0%
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Table of Contents
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