테스트 설계, 취약점 진단, 품질 보증 (1.3만건)
Systematic false positive verification for security findings. Provides structured methodology to confirm or dismiss scanner results, manual audit findings, and automated alerts. Adapted from Trail of Bits. Use when triaging security scan results or verifying audit findings.
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Django testing strategies with pytest-django, TDD methodology, factory_boy, mocking, coverage, and testing Django REST Framework APIs.
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Failure injection patterns, blast radius control, steady state hypothesis, and gameday planning for resilience testing.
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Framework for measuring and tracking agent response quality over time. Detects regressions before they reach production. Use when evaluating agent changes, auditing quality, or establishing performance baselines.
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Post-implementation cleanup that removes AI-generated bloat while preserving functionality. Runs pass-by-pass with test verification after each pass. Activate after kraken/spark complete a feature, or when a codebase needs hygiene work.
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Terminal pet that lives in your statusline. 12 species, 5 stats (DEBUGGING, PATIENCE, CHAOS, WISDOM, SPEED). Reacts to your workflow - happy when tests pass, sad when builds fail, excited during swarm mode. Deterministic species from user ID.
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Agent davranis testi ve protokol uyumluluk dogrulamasi. Agent'larin tanimli rollerine uygun davranip davranmadigini assertion-based test'lerle olcer. Personality drift, role violation ve output kalite regresyonu tespit eder.
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axe-core integration, WCAG 2.2 AA checklist, keyboard navigation testing, screen reader testing, and ARIA pattern validation.
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Precision-first adversarial bug hunting for runtime, logic, data, concurrency, and security defects. Uses deterministic risk triage, evidence-bounded retrieval, Hunter/Skeptic/Referee review, optional hybrid verification, and explicit immutable Fixer scope. Scan-only and single-pass by default; complete-coverage loops, edits, autonomous fixes, and commits each require explicit intent. Use for code review, security audits, regression hunting, PR review, and evidence-backed remediation planning in skills-capable coding agents.
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Generate or refresh a STRIDE-based threat model for the current repository using Bug Hunter-native artifacts. Use whenever the repository has no threat model yet, the architecture changed materially, a security review needs fresh trust-boundary context, or the user explicitly asks for a threat model.
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Final arbiter for Bug Hunter. Receives Hunter findings and Skeptic challenges, independently re-reads code, and delivers authoritative verdicts with CVSS scoring and proof-of-concept generation for security findings.
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Run a focused STRIDE-based security review using Bug Hunter-native artifacts. Use whenever the user asks for a full security audit, repository security review, weekly security scan, PR security review with deeper validation, or wants dependency CVEs and threat-model context combined into one workflow.
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Deep behavioral code analysis agent for Bug Hunter. Performs multi-phase scanning to find logic errors, security vulnerabilities, race conditions, and runtime bugs. Uses doc-lookup (Context Hub + Context7) for framework verification. Reports structured JSON findings.
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Scan code changes for security vulnerabilities using Bug Hunter-native artifacts and STRIDE context. Use whenever the user asks for PR security review, commit-diff scanning, staged-change security checks, branch-comparison security review, or pre-merge security analysis of changed code.
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Validate security findings for exploitability, reachability, and real-world impact using Bug Hunter-native findings artifacts. Use after security scans, before patch generation, or whenever the user wants confirmation that a suspected vulnerability is actually exploitable.
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Configure security information and event management (SIEM) systems for threat detection, log aggregation, and compliance. Use when implementing centralized security logging, writing detection rules, or meeting audit requirements across cloud and on-premise infrastructure.
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Reduces attack surface across OS, container, cloud, network, and database layers using CIS Benchmarks and zero-trust principles. Use when hardening production infrastructure, meeting compliance requirements, or implementing defense-in-depth security.
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When validating system performance under load, identifying bottlenecks through profiling, or optimizing application responsiveness. Covers load testing (k6, Locust), profiling (CPU, memory, I/O), and optimization strategies (caching, query optimization, Core Web Vitals). Use for capacity planning, regression detection, and establishing performance SLOs.
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Write robust, portable shell scripts with proper error handling, argument parsing, and testing. Use when automating system tasks, building CI/CD scripts, or creating container entrypoints.
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Design and implement disaster recovery strategies with RTO/RPO planning, database backups, Kubernetes DR, cross-region replication, and chaos engineering testing. Use when implementing backup systems, configuring point-in-time recovery, setting up multi-region failover, or validating DR procedures.
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Authentication, authorization, and API security implementation. Use when building user systems, protecting APIs, or implementing access control. Covers OAuth 2.1/OIDC, JWT patterns, sessions, Passkeys/WebAuthn, RBAC/ABAC/ReBAC, policy engines (OPA, Casbin, SpiceDB), managed auth (Clerk, Auth0), self-hosted (Keycloak, Ory), and API security best practices.
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Strategic guidance for choosing and implementing testing approaches across the test pyramid. Use when building comprehensive test suites that balance unit, integration, E2E, and contract testing for optimal speed and confidence. Covers multi-language patterns (TypeScript, Python, Go, Rust) and modern best practices including property-based testing, test data management, and CI/CD integration.
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Evaluate LLM systems using automated metrics, LLM-as-judge, and benchmarks. Use when testing prompt quality, validating RAG pipelines, measuring safety (hallucinations, bias), or comparing models for production deployment.
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Implement production-ready service mesh deployments with Istio, Linkerd, or Cilium. Configure mTLS, authorization policies, traffic routing, and progressive delivery patterns for secure, observable microservices. Use when setting up service-to-service communication, implementing zero-trust security, or enabling canary deployments.
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