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.
BaxterCooper AI Skills
GitHub ↗Explorez les skills IA publiés de BaxterCooper et consultez leurs instructions source.
Statistiques de l’auteur
Skills indexés
10Étoiles des dépôts des skills indexés
0Forks du dépôt
0Moyenne des étoiles par skill indexé
0Les étoiles d’un dépôt peuvent se répéter entre ses skills.
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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.
GitHub
parallel-dispatch
Use when facing multiple tasks or failures. Provides decision framework for concurrent vs sequential execution. Invoke before dispatching multiple subagents.
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...
GitHub
estimation
Use before committing to a task. Provides complexity analysis and scope assessment. Invoke when user asks "how complex" or before large features.
GitHub
finishing
Use when all tasks are complete. Presents completion options and enforces test gate. Work is never left in limbo.
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.
GitHub
systematic-debugging
Invoke when debugging failures. MANDATORY when 3+ fix attempts have failed. Enforces root cause investigation before fixes.
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."
GitHub
writing-plans
Use when creating implementation plans. Mandates exact file paths, complete code samples, and expected output. No vague language allowed.
Le classement utilise les étoiles du dépôt GitHub indexé. Plusieurs skills peuvent partager ce nombre : ce n’est ni un nombre d’installations ni une note de qualité.