gtars
High-performance toolkit for genomic interval analysis in Rust with Python bindings. Use when working with genomic regions, BED files, coverage tracks, overlap detection, tokenization for ML models, or fragment analysis in computational genomics and machine learning applications.
gtars
High-performance toolkit for genomic interval analysis in Rust with Python bindings. Use when working with genomic regions, BED files, coverage tracks, overlap detection, tokenization for ML models, or fragment analysis in computational genomics and machine learning applications.
orchestrate-review
Use when user asks to "deep review the code", "thorough code review", "multi-pass review", or when orchestrating the Phase 9 review loop. Provides review pass definitions (code quality, security, performance, test coverage), signal detection patterns, and iteration algorithms.
orchestrate-review
Use when user asks to "deep review the code", "thorough code review", "multi-pass review", or when orchestrating the Phase 9 review loop. Provides review pass definitions (code quality, security, performance, test coverage), signal detection patterns, and iteration algorithms.
bio-longread-alignment
Align long reads using minimap2 for Oxford Nanopore and PacBio data. Supports various presets for different read types and applications. Use when aligning ONT or PacBio reads to a reference genome for variant calling, SV detection, or coverage analysis.
bio-rnaseq-qc
RNA-seq specific quality control including rRNA contamination detection, strandedness verification, gene body coverage, and transcript integrity metrics. Use when validating RNA-seq libraries before differential expression analysis.
bio-methylation-methylkit
DNA methylation analysis with methylKit in R. Import Bismark coverage files, filter by coverage, normalize samples, and perform statistical comparisons. Use when analyzing single-base methylation patterns, comparing samples, or preparing data for DMR detection.
detection-coverage-analysis
Analyzes detection coverage using Sigma, Splunk, and Elastic rules. Use when checking coverage for techniques, tactics, threat actors, or generating Navigator layers from detections.
qcsd-cicd-swarm
QCSD Verification phase swarm for CI/CD pipeline quality gates using regression analysis, flaky test detection, quality gate enforcement, and deployment readiness assessment. Consumes Development outputs (SHIP/CONDITIONAL/HOLD decisions, quality metrics) and produces signals for Production monitoring.
QE Coverage Analysis
O(log n) sublinear coverage gap detection with risk-weighted analysis and intelligent test prioritization.
qcsd-development-swarm
QCSD Development phase swarm for in-sprint code quality assurance using TDD adherence, code complexity analysis, coverage gap detection, and defect prediction. Consumes Refinement outputs (BDD scenarios, SFDIPOT priorities) and produces signals for Verification.
security-visual-testing
Security-first visual testing combining URL validation, PII detection, and visual regression with parallel viewport support. Use when testing web applications that handle sensitive data, need visual regression coverage, or require WCAG accessibility compliance.
qe-security-visual-testing
Security-first visual testing combining URL validation, PII detection, and visual regression with parallel viewport support. Use when testing web applications that handle sensitive data, need visual regression coverage, or require WCAG accessibility compliance.
source-unifier
Merge multiple documentation sources (docs, GitHub, PDF) with conflict detection. Use when combining docs + code for complete skill coverage.
Test Observability & Analytics
Implementing test observability with execution analytics, failure trend analysis, coverage gap detection, and test suite health dashboards.
Mutation Test Generator
Generate and run mutation tests to measure test suite effectiveness by introducing code mutations and verifying detection rates.
PR Test Impact Analyzer
Analyze pull request code changes to determine which tests are affected, recommend test execution order, and identify missing test coverage for modified code paths
test-automation-expert
Comprehensive test automation specialist covering unit, integration, and E2E testing strategies. Expert in Jest, Vitest, Playwright, Cypress, pytest, and modern testing frameworks. Guides test pyramid design, coverage optimization, flaky test detection, and CI/CD integration. Activate on 'test strategy', 'unit tests', 'integration tests', 'E2E testing', 'test coverage', 'flaky tests', 'mocking', 'test fixtures', 'TDD', 'BDD', 'test automation'. NOT for manual QA processes, load/performance testing (use performance-engineer), or security testing (use security-auditor).
dev_invoke_kimi-cli
Delegate testing, QA, and code review tasks to Opencode CLI using Kimi K2.5 model via markdown file handoff. Write test request to TASK.md, Opencode with Kimi K2.5 generates tests/reviews, outputs to OUTPUT.md. Use for test generation, QA verification, edge case detection, code coverage analysis, security reviews. Triggers: kimi, kimi k2.5, kimi cli, opencode kimi, test generation, QA, quality assurance, code review, unit tests, integration tests, edge cases, test coverage, testing, kimisubagent, togetherai kimi, opencode/kimi-k2.5-free, togetherai/moonshotai/Kimi-K2.5 Prerequisites: Opencode CLI installed, Together.ai API key (if using togetherai provider) Models: opencode/kimi-k2.5-free (recommended), togetherai/moonshotai/Kimi-K2.5 (alternative)
traceability-auditor
Validates complete requirements traceability across EARS requirements → design → tasks → code → tests. Trigger terms: traceability, requirements coverage, coverage matrix, traceability matrix, requirement mapping, test coverage, EARS coverage, requirements tracking, traceability audit, gap detection, orphaned requirements, untested code, coverage validation, traceability analysis. Enforces Constitutional Article V (Traceability Mandate) with comprehensive validation: - Requirement → Design mapping (100% coverage) - Design → Task mapping - Task → Code implementation mapping - Code → Test mapping (100% coverage) - Gap detection (orphaned requirements, untested code) - Coverage percentage reporting - Traceability matrix generation Use when: user needs traceability validation, coverage analysis, gap detection, or requirements tracking across the full development lifecycle.
CI/CD Optimization
Comprehensive CI/CD pipeline methodology with quality gates, release automation, smoke testing, observability, and performance tracking. Use when setting up CI/CD from scratch, build time over 5 minutes, no automated quality gates, manual release process, lack of pipeline observability, or broken releases reaching production. Provides 5 quality gate categories (coverage threshold 75-80%, lint blocking, CHANGELOG validation, build verification, test pass rate), release automation with conventional commits and automatic CHANGELOG generation, 25 smoke tests across execution/consistency/structure categories, CI observability with metrics tracking and regression detection, performance optimization including native-only testing for Go cross-compilation. Validated in meta-cc with 91.7% pattern validation rate (11/12 patterns), 2.5-3.5x estimated speedup, GitHub Actions native with 70-80% transferability to GitLab CI and Jenkins.
gtars
High-performance toolkit for genomic interval analysis in Rust with Python bindings. Use when working with genomic regions, BED files, coverage tracks, overlap detection, tokenization for ML models, or fragment analysis in computational genomics and machine learning applications.
code-reviewer
Comprehensive code review and analysis for software quality assurance. Use when Claude needs to review code in any format including (1) individual files (Python, R, JavaScript, etc.), (2) directory structures and project organization, (3) scripts and automation code, (4) Jupyter notebooks and data analysis workflows, (5) documentation assessment and improvement suggestions, (6) bug detection and logic verification, (7) testing coverage and strategy evaluation, (8) code consistency and maintainability analysis. Provides actionable improvement recommendations across all aspects of software development.
validation
Runs production readiness validation checks. Includes type checking, linting, tests, coverage, security, and dead code detection. Stack-agnostic.
Security & Vulnerability Testing
Production-grade security testing with agentic vulnerability detection, SAST/DAST tools, OWASP Top 10 coverage, threat modeling, and AI-powered security analysis achieving 92% detection accuracy (OpenAI Aardvark benchmark 2024)
gtars
High-performance toolkit for genomic interval analysis in Rust with Python bindings. Use when working with genomic regions, BED files, coverage tracks, overlap detection, tokenization for ML models, or fragment analysis in computational genomics and machine learning applications.
js-agents-entropy-scan
JS/JSDoc microkernel project code entropy scanning and fixing. Suitable for Agent systems built with pure JavaScript + JSDoc. Trigger conditions: - The user requests a code quality scan for js/agents or a similar JS microkernel project - The user says "/js-entropy-scan" or "scan code entropy" - Checks required: JSDoc coverage, TODO/FIXME cleanup, leftover console calls, error-handling conventions, export consistency, dead code detection
testgen
Generate tests with expert routing, framework detection, and auto-TaskCreate. Triggers on: generate tests, write tests, testgen, create test file, add test coverage.
sensor-coverage
Comprehensive Asset Inventory & Coverage Tracker for LimaCharlie. Builds sensor inventories, detects coverage gaps (stale/silent endpoints, Shadow IT), calculates risk scores, validates telemetry health, and compares actual vs expected assets. Use for fleet inventory, coverage SLA tracking, offline sensor detection, telemetry health checks, asset compliance audits, or when asked about endpoint health, asset management, or coverage gaps.
pr-review
Pull request and code review with diff-based routing across five dimensions: code quality and guideline compliance, test coverage analysis, silent failure detection, type design and invariant analysis, and comment quality auditing. Classifies changed files and loads only relevant review methodologies. Produces severity-ranked findings (Critical, Important, Suggestion) with confidence scoring. Replaces pr-review-toolkit plugin. Trigger phrases: "review my PR", "review this code", "check my changes", "is this ready to merge", "audit this PR", "review before committing", "check code quality", "any issues with this code", "pre-merge review", "look over my changes", "code review". Use this skill when reviewing code before commit or merge, checking PR quality, or when the user asks for feedback on recent modifications.
pt-lotl-techniques
Demonstrates Living-off-the-Land (LotL) techniques using native OS tools to simulate realistic threat actor behavior during authorized penetration tests. Use when proving attack feasibility without custom malware, testing detection coverage, and validating what a real adversary could achieve with only built-in system capabilities.
mapping-mitre-attack-techniques
Maps observed adversary behaviors, security alerts, and detection rules to MITRE ATT&CK techniques and sub-techniques to quantify detection coverage and guide control prioritization. Use when building an ATT&CK-based coverage heatmap, tagging SIEM alerts with technique IDs, aligning security controls to adversary playbooks, or reporting threat exposure to executives. Activates for requests involving ATT&CK Navigator, Sigma rules, MITRE D3FEND, or coverage gap analysis.
performing-threat-hunting-with-elastic-siem
Performs proactive threat hunting in Elastic Security SIEM using KQL/EQL queries, detection rules, and Timeline investigation to identify threats that evade automated detection. Use when SOC teams need to hunt for specific ATT&CK techniques, investigate anomalous behaviors, or validate detection coverage gaps using Elasticsearch and Kibana Security.
implementing-threat-modeling-with-mitre-attack
Implements threat modeling using the MITRE ATT&CK framework to map adversary TTPs against organizational assets, assess detection coverage gaps, and prioritize defensive investments. Use when SOC teams need to align detection engineering with threat landscape, conduct threat assessments for new environments, or justify security tool procurement.
implementing-mitre-attack-coverage-mapping
Implement MITRE ATT&CK coverage mapping to identify detection gaps, prioritize rule development, and measure SOC detection maturity against adversary techniques.
deploying-edr-agent-with-crowdstrike
Deploys and configures CrowdStrike Falcon EDR agents across enterprise endpoints to enable real-time threat detection, behavioral analysis, and automated response. Use when onboarding endpoints to EDR coverage, configuring detection policies, or integrating Falcon telemetry with SIEM platforms. Activates for requests involving CrowdStrike deployment, Falcon sensor installation, EDR policy configuration, or endpoint detection and response.
implementing-siem-use-cases-for-detection
Implements SIEM detection use cases by designing correlation rules, threshold alerts, and behavioral analytics mapped to MITRE ATT&CK techniques across Splunk, Elastic, and Sentinel. Use when SOC teams need to expand detection coverage, formalize use case lifecycle management, or build a detection library aligned to organizational threat profile.
building-soc-metrics-and-kpi-tracking
Builds SOC performance metrics and KPI tracking dashboards measuring Mean Time to Detect (MTTD), Mean Time to Respond (MTTR), alert quality ratios, analyst productivity, and detection coverage using SIEM data. Use when SOC leadership needs operational visibility, continuous improvement tracking, or executive-level reporting on security operations effectiveness.
gtars
High-performance toolkit for genomic interval analysis in Rust with Python bindings. Use when working with genomic regions, BED files, coverage tracks, overlap detection, tokenization for ML models, or fragment analysis in computational genomics and machine learning applications.
skill-auditor
Perform structured, reproducible audits of agent skills — testing mechanical correctness, agent usability, output quality, context efficiency, EARS compliance, prompt complexity, multi-agent coordination, audit convergence (reproducibility across runs), finding divergence (specificity and tailoring), AGENTS.md adherence (rule absorption verification), documentation/runtime staleness drift detection, CLI discoverability helper coverage, idempotency, error recovery, and credential safety. Covers 25 audit domains (D1–D25) with confidence-scored findings at every level. Use when (1) auditing or health-checking a skill end-to-end, (2) verifying AGENTS.md adherence, audit convergence, or finding divergence, or (3) validating scripts, CLIs, context/token footprint, EARS requirement syntax, prompt complexity, name consistency, dispatch prompt quality, or structured confidence-scored audit reports.
dotnet-test-quality
Measuring test effectiveness. Coverlet code coverage, Stryker.NET mutation testing, flaky detection.
forge-verifier
Gap detection and verifier creation. Reports tools without verifier coverage, suggests verifiers by output group, generates verifier stubs and barrel registration.
gtars
High-performance toolkit for genomic interval analysis written in Rust with Python bindings. Use it when working with genomic regions, BED files, coverage tracks, overlap detection, tokenization for machine-learning models, or fragment analysis in computational genomics and machine learning applications.
QA Sentinel Agent
Specialized quality assurance knowledge for test coverage analysis, bug detection, and quality gates.