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SkillsMP は kimasplund/clawdbot-skills-pack から 13 件の skill を収集しています。skill を開くとソースと詳細を確認できます。
収集済み skill 13 件中 13 件を表示しています。
Self-improving agent architecture using ChromaDB for continuous learning, self-evaluation, and improvement storage. Agents maintain separate memory collections for learned patterns, performance metrics, and self-assessments without modifying their static .md…
原文の言語: 英語
Guide for manually creating custom skills from scratch with templates and validation. Use when designing NEW skills with specific requirements. For auto-generating skills from existing git repos, use /generate-skills instead.
原文の言語: 英語
Display QAVR (Q-Value Augmented Vector Retrieval) system status including mode, interaction counts, top memories by Q-value, and configuration.
原文の言語: 英語
Enables continuous self-improvement through learning from failures, user corrections, and capability gaps. Integrates with QAVR for learned memory ranking.
原文の言語: 英語
Stress-test solutions using the STRIKE framework. Systematically attack proposals to find weaknesses before deployment.
原文の言語: 英語
Exhaustive solution space exploration. Use when you need ALL viable options (not just the best), solution space is unknown, or you can't afford to miss alternatives.
原文の言語: 英語
Diagnostic reasoning for finding root causes. Generates multiple hypotheses, designs tests to eliminate each, and converges on the true cause through evidence.
原文の言語: 英語
Meta-orchestrator that selects optimal reasoning patterns based on problem characteristics. Analyzes 11 dimensions and recommends ToT, BoT, SRC, HE, AR, DR, AT, RTR, or NDF patterns.
原文の言語: 英語
Systematic evaluation methodology for finding THE best solution among known options. Explores multiple reasoning paths, scores branches, and prunes low-confidence paths.
原文の言語: 英語
Periodic "sleep-like" memory optimization. Detects patterns, resolves conflicts, applies decay, and transfers knowledge across contexts.
原文の言語: 英語
Q-Value Augmented Vector Retrieval for learned memory ranking. Tracks which memories are most useful over time and prioritizes them in retrieval.
原文の言語: 英語
Pre-implementation validation requiring ≥90% confidence before coding. Prevents wrong-direction work by assessing duplicates, architecture alignment, and root cause understanding.
原文の言語: 英語
Security assessment using STRIDE threat modeling, OWASP Top 10, and CVSS scoring. Use for security reviews, threat modeling, and secure coding guidance.
原文の言語: 英語