GitHub
error-recovery
Use when tasks fail due to transient errors. Provides structured retry strategies and graceful degradation patterns. Invoke on network errors, rate limits, or intermittent failures.
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BaxterCooper AI Skills
GitHub ↗浏览 BaxterCooper 维护的已发布 AI 技能，比较用途与说明，并通过来源仓库了解安装方式。
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已收录技能
10收录技能的仓库 Stars 合计
0仓库 Forks
0平均每个技能的仓库 Stars
0同一仓库中的多个技能可能共享 Stars，合计包含重复仓库数据。
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GitHub
orchestration
This skill should be used when orchestrating complex tasks, decomposing work into atomic units, dispatching to subagents, verifying outputs, or when discussing task verification and deviation tracking patterns.
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GitHub
parallel-dispatch
Use when facing multiple tasks or failures. Provides decision framework for concurrent vs sequential execution. Invoke before dispatching multiple subagents.
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GitHub
verification
This skill MUST be invoked before any completion claim, success report, or task transition. Mandates 5-step evidence protocol. Use when about to claim "done", "complete", "working", "fixed", or any success stat...
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GitHub
estimation
Use before committing to a task. Provides complexity analysis and scope assessment. Invoke when user asks "how complex" or before large features.
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GitHub
finishing
Use when all tasks are complete. Presents completion options and enforces test gate. Work is never left in limbo.
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GitHub
context-gathering
Use when entering an unfamiliar codebase, starting a new feature, or before any implementation task. Provides structured exploration protocol to understand before acting.
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GitHub
systematic-debugging
Invoke when debugging failures. MANDATORY when 3+ fix attempts have failed. Enforces root cause investigation before fixes.
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GitHub
tdd
Use for any code implementation task. Enforces RED-GREEN-REFACTOR cycle. "If you didn't watch it fail, you don't know if it tests the right thing."
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GitHub
writing-plans
Use when creating implementation plans. Mandates exact file paths, complete code samples, and expected output. No vague language allowed.
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默认按已收录数据中的 GitHub 仓库 Stars 排序。Stars 属于来源仓库，同一仓库的多个技能可能共享相同数值；它反映仓库关注度，不代表单个技能的安装量或质量评分。