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Found 1,359 Skills
Use when starting, designing, organizing, finishing, or shipping an n8n workflow. Covers visual layout (sticky notes), descriptions that capture the *why*, node names, validation, testing, folders/projects, and publishing. Triggers on create_workflow_from_code, update_workflow, validate_workflow, publish_workflow, archive_workflow, "design", "lay out", "organize", "structure", "sticky", "describe this workflow", "ship", "deploy", "publish", "name this workflow", or any folder/project organization request.
Codex-native Academic Research Skills suite for deep research, academic paper writing, manuscript review, full research-to-paper pipelines, and experiment planning or validation. Use when the user asks for deep research, literature review, systematic review, meta-analysis, research question refinement, academic paper drafting, paper revision, citation or integrity checks, reviewer simulation, peer review, editorial decision letters, research-to-paper workflows, experiment execution planning, statistical interpretation, or human study protocol support. Also use for Claude-style ARS command aliases such as /ars-plan, ars-plan, /ars-outline, /ars-abstract, /ars-lit-review, /ars-citation-check, /ars-disclosure, /ars-format-convert, /ars-revision-coach, /ars-revision, and /ars-full. This skill vendors ARS role prompts, references, templates, and shared handoff schemas under ars/.
Design and operate data quality programs for financial data — golden source architecture, validation rules, data lineage, exception management, profiling, and governance. Use when building validation rules for pricing or client data pipelines, designing a data quality monitoring framework, establishing golden source designations across systems, implementing data lineage for BCBS 239 or MiFID II, investigating reconciliation breaks or billing errors traced to bad data, preparing for regulatory exams on data accuracy, building data quality scorecards, or defining data stewardship roles. Trigger on: data quality, golden source, data lineage, data validation, data profiling, exception management, data governance, BCBS 239, data completeness, data accuracy, validation rules, data anomaly, data stewardship, data quality scorecard.
Guides edge and tactical autonomous systems—perception-planning-control under latency and safety constraints; behavior trees/state machines vs learned policies; human-on-the-loop; geofencing, no-strike rules, mission abort; sim and field testing; ROS2/middleware patterns; sensor fusion; degraded modes; autonomy audit logging. Use for UAS/autonomous stacks, safety rules, HITL, sim-to-field validation, fail-safe—not LLM products (ai-engineer), LLM red team (ai-redteam), safeguard serving (ml-infrastructure-engineer-safeguards), governance only (ai-risk-governance), MCU firmware without autonomy (embedded-real-time-software-engineer), plant PLC/DCS (control-software-developer), HIL security bench (hardware-in-the-loop-security-tester).
Guides hands-on actuarial analyst work for insurance, reinsurance, and pension—reserving and loss development (IBNR, triangles, chain-ladder diagnostics), pricing and rate indication support (experience, trend, credibility, basic GLM at spec level), data validation and model I/O review, reporting packs and workpapers, assumption application under actuary direction, and statutory tie-outs at analyst depth. Use when the user mentions actuarial analyst, loss development, IBNR, reserve analysis, rate indication, pricing support, actuarial workpaper, triangle analysis, credibility, experience study, actuarial reporting, or reserve roll-forward—not actuary sign-off (actuary), consulting engagements (actuarial-consulting), assumption governance (assumption-setting), ALM strategy (asset-liability-management), P&C legal depth (property-casualty-insurance), charts only (data-visualization), or ETL-only pipelines (data-scrubbing).
Guides cleaning and standardizing tabular datasets before analysis, modeling, or reporting—profiling, quality rules, missing values, duplicates, outliers, type coercion, encoding fixes, record linkage, deduplication, high-level PII handling (not legal advice), actuarial/insurance field scrubbing, reproducible scrub pipelines, validation checks, and sign-off. Distinct from warehouse ETL or statistical modeling. Use when the user asks for "data scrubbing", "clean this dataset", "scrub the data", "data cleaning", "dedupe records", "handle missing values", "outlier treatment", "standardize columns", "data quality rules", "profile this table", or "prepare data for modeling". Not warehouse pipelines (data-warehouse-engineer), ML modeling (data-scientist, actuary), privacy programs (compliance-engineer), FinOps only (finops-analyst), or assumption governance (assumption-setting).
Guides Validation by Educational Experience (VEE) for North American actuarial credential paths (SOA, CAS)—how VEE fits preliminary requirements, current topic areas (Economics, Accounting & Finance, Mathematical Statistics; subject to society updates), approved-course criteria, candidate workflow and documentation, SOA vs CAS submission timing relative to ASA/ACAS progress, international/transfer considerations, and common pitfalls. Use for VEE, validation by educational experience, VEE credit, actuarial VEE requirements, SOA VEE, CAS VEE, VEE economics, VEE statistics, VEE accounting and finance, college credit for actuarial exams, submit VEE transcript—not deep exam study (pre-actuarial-foundations, advanced-short-term-actuarial-mathematics, advanced-long-term-actuarial-mathematics), workpapers (actuarial-analyst), signing (associate-actuary, appointed-chief-actuary), official transcript qualification rulings, or generic degree planning.
Guides actuarial consulting engagements—client scoping and SOW design, stakeholder communication (CFO, risk, boards, regulators at overview level), due diligence and M&A actuarial support, reserving/pricing/capital review programs, model validation and opinion support, regulatory interaction prep, and deliverable governance (memos, exhibits, management presentations). Use when the user mentions actuarial consulting, actuarial engagement, reserve opinion, due diligence actuarial, model validation engagement, actuarial memo, SOW actuarial, regulatory actuarial, M&A reserves, or actuarial review—not deep technical modeling execution (actuary), P&C line education only (property-casualty-insurance), legal advice (commercial-counsel), or generic management consulting without actuarial lens (business-consultant).
Guides secure software delivery and DevSecOps for cleared/classified or high-side programs—disconnected or air-gapped CI/CD, artifact promotion across classification boundaries (conceptual), SBOM/signing/ provenance, SAST/DAST/secrets/IaC/container gates, supply-chain controls, STIG/CIS deploy baselines, IaC for classified landing zones, cleared developer workstations, build/deploy audit logging, and ATO/RMF pipeline evidence (not SSP ownership). Use for classified DevSecOps, cleared pipeline, high-side CI/CD, air-gapped build, cross-domain release, classified software delivery, STIG pipeline, ATO evidence CI, SBOM classified, secure software factory—not portfolio cyber governance (classified-cyber-security-senior-manager), ISSO/SSP (information-systems-security-officer-classified-specialist), commercial-only DevSecOps (devsecops), general DevOps (devops), build-only validation (build-validator), pentest (penetration-tester), or enterprise GRC-only (compliance-specialist).
Guides CI/CD for agent skills repositories and skill packages—pipeline design (build, test, validate, package), GitHub Actions for PR checks and release promotion, environment gates, secrets hygiene (no secrets in repo), skill-creator integration (quick_validate.py, package_skill.py), .skill artifact strategy, rollback, and operational runbooks for skill releases. Use when the user mentions CI/CD, CI/CD engineer, pipeline design, GitHub Actions, skill validation CI, package skills, release pipeline, deploy skills, PR checks, continuous integration, or skill release workflow—not application-only CI without skill packaging (devops), pre-flight plan go/no-go (build-validator), IDP or golden paths (platform-engineer), org-wide SLO and error-budget programs without pipeline ownership (site-reliability-engineer), or portfolio catalog governance without pipeline YAML (ai-skill-manager).
Guides authoring, review, optimization, and false-positive debugging of YARA-X detection rules for malware identification across PE, script, npm, Office, Chrome extensions (crx module), and Android DEX (dex module). Covers string and atom quality, condition short-circuiting, legacy YARA migration, yarGen/FLOSS workflows, goodware validation, and production deployment—not full malware reverse engineering, network IDS (Suricata/Snort), or memory forensics (Volatility). Use when the user asks to write YARA rule, YARA-X, yr check, yr scan, false positive YARA, yarGen, malware detection rule, crx module, dex module, optimize YARA performance, or migrate legacy YARA.
Orthogonally-integrated Hegelian syntopical analysis for SAQ/VIVA/concept grounding with systematic textbook citations. Implements thesis extraction → antithesis identification → abductive synthesis across multiple authoritative sources. Tensor-integrated with /m command: activates S×T×L synergies (textbook-grounding × pdf-search × qmd = 0.95). Triggers on requests for model SAQ responses, VIVA preparation, concept explanations requiring textbook evidence, or any PEX exam content needing systematic cross-reference validation.