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Visão por repositório de 15 skills coletadas em 1 repositórios do GitHub.

skills coletadas
15
repositórios
1
atualizado
2026-05-05
mapa de repositórios

Onde as skills estão

Principais repositórios por número de skills coletadas, com sua participação neste catálogo do criador e sua distribuição ocupacional.

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Repositórios e skills representativas

code-repair
Desenvolvedores de software

Triggered on runtime errors in the scan loop. Diagnoses the root cause, writes a targeted fix to src/, and reports what changed. The calling harness runs pytest before merging — if tests fail, the fix is reverted automatically.

2026-05-05
feedback-loop
Cientistas de dados

Post-trade feedback loop system: shaped-reward logging, diagnostics, and self-heal. Use when investigating trade outcomes, checking system health, or understanding automated corrective actions.

2026-05-05
mcp-tools
Administradores de redes e sistemas de computador

Buddy MCP server: 15 tools for system observability, feedback loop control, OANDA state, and knowledge management. Use when querying system health, investigating trades, or triggering diagnostics/self-heal.

2026-05-05
trade-reflection
Cientistas de dados

Spawned automatically on trade close by ClaudeReflectionHandler. Reads the just-closed trade, compares prediction to outcome, and writes structured learnings / rule drafts / weight proposals that Buddy picks up on the next scan cycle.

2026-05-05
code-repair
Desenvolvedores de software

Triggered on runtime errors in the scan loop. Diagnoses the root cause, writes a targeted fix to src/, and reports what changed. The calling harness runs pytest before merging — if tests fail, the fix is reverted automatically.

2026-04-26
trade-reflection
Cientistas de dados

Spawned automatically on trade close by ClaudeReflectionHandler. Reads the just-closed trade, compares prediction to outcome, and writes structured learnings / rule drafts / weight proposals that Buddy picks up on the next scan cycle.

2026-04-14
adaptive-gate-tuning
Cientistas de dados

Tune or audit ML Engine gate thresholds as a coordinated adaptive system. Use when confidence, momentum, risk, or agent-consensus thresholds are being changed; when one static gate bottlenecks an otherwise adaptive pipeline; or when the scanner alternates between over-trading and total suppression. Focus on coupled gate behavior, regime awareness, drawdown state, virtual trades, and safe one-change-at-a-time tuning.

2026-04-14
execution-safety-audit
Analistas de garantia de qualidade de software e testadores

Review changes to ML Engine's execution path, broker integration, and risk enforcement. Use when modifying `execution.py`, OANDA adapters, sizing, routing, or trade approval logic. Focus on preserving gate integrity, R:R minimums, correlation/risk controls, retry safety, state writes, and observability in a live trading environment.

2026-04-14
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