from opencode-skills-collection10
Diagnose and optimize Agent Skills (SKILL.md) using session transcripts and static analysis to improve triggers, workflows, and token efficiency.
Runs an evidence-driven audit of Agent Skills using historical session data and static checks. Measures trigger rates, post-invocation user reactions, workflow completion, static quality rules, undertrigger/overtrigger rates, environment consistency, and token economics to produce prioritized fixes.
Use when skills are misfiring, underused, or you need a data-driven plan to improve skill routing and descriptions. Good for library maintenance, onboarding new skills, or periodic quality audits.
Targets agents and environments where session transcripts are available (Claude Code, Codex) and where read-only auditing of skill files is permitted.
This skill has not been reviewed by our automated audit pipeline yet.
Python Performance Optimization
Profile, analyze, and optimize Python applications for CPU and memory efficiency using profiling tools and performance best practices.
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Structured workflow for testing REST and GraphQL API security: auth, authorization, rate limiting, input validation and error handling.
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Practical guidance and commands for acquiring, analyzing, and extracting artifacts from memory dumps using tools like Volatility3 and common acquisition methods
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Guided methodology and best practices for binary reverse engineering, covering static and dynamic analysis workflows and common tooling.
