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Found 58 Skills
Apply structured critical thinking — identifying claims, evidence, reasoning chains, hidden assumptions, and logical fallacies — to evaluate or construct specific written arguments rigorously. Use this skill when the user presents a concrete argument, claim, op-ed, research finding, or piece of reasoning to be analyzed for logical validity or flaws, even if they say 'is this argument valid', 'what logical fallacies are in this', or 'what assumptions am I making in this thesis'. Do NOT use for casual plan review, trip planning, project risk brainstorming, or pre-mortems — 'poke holes in my plan' requests are red-team / risk review, not argument analysis.
Senior Code Architect & Quality Assurance Engineer for 2026. Specialized in context-aware AI code reviews, automated PR auditing, and technical debt mitigation. Expert in neutralizing "AI-Smells," identifying performance bottlenecks, and enforcing architectural integrity through multi-job red-teaming and surgical remediation suggestions.
Use when the user asks to "create an evaluator", "create evals", "create a scenario", "write a test scenario", "design a test case", "test my agent", "build eval coverage", "plan a test suite", "create red team tests", "set up test profiles", "configure conditional actions", "write a conditional action evaluator", "build a deterministic test", "design an IVR test", "IVR navigation test", "write a unit test for a voice agent", "build a regression test", "scripted scenario", "scripted voice test", "structured evaluator", "exact flow test", "sequential conditions", "fixed sequence test", or "run evals". Covers individual evaluator design, suite coverage strategy, test profiles, mock-tool data design, conditional actions (deterministic / unit test / regression / IVR navigation flows), and best practices for workflow / red-team / edge-case / deterministic test types.
Guides SOC operations—alert triage, SIEM/EDR investigation, enrichment, playbook execution, false-positive closure, escalation decisions, and detection tuning feedback. Use when working SOC queues, investigating suspicious alerts, correlating events, documenting analyst notes, or deciding escalate vs close—not for declared incident command, timelines, evidence preservation, or regulatory comms (incident-responder), incident program design (incident-management-engineer), binary/firmware RE (reverse-engineer), red team operations (red-team-specialist), or enterprise security strategy (cybersecurity).
Guides ML/research engineering for safeguards—safety classifier development, harm benchmarks and eval suites, labeled dataset design, fine-tuning and ablations, calibration and slice analysis, attack-surface research memos, and promotion criteria for new moderation models. Use when building or evaluating guardrail models, designing safety benchmarks, measuring precision/recall on policy categories, comparing mitigation techniques, or writing research reports on classifier improvements—not for production inference gateways (ml-infrastructure-engineer-safeguards), PII/leakage privacy research (privacy-research-engineer-safeguards), red-team attack campaigns (ai-redteam), AI governance policy (ai-risk-governance), general non-safety research (ai-researcher), or token-efficiency studies (research-engineer-scientist-tokens).
Provides calibrated decision analysis using Charlie Munger-style multiple mental models, inversion, incentive mapping, circle-of-competence checks, misjudgment audits, second-order effects, and forecast updates. Use when the user asks for an oracle take, a hard call, a decision memo, a premortem, an outside view, a red-team, a sanity-check, what am I missing, think this through, or wants a strategy, hire, investment, plan, product, partnership, or major life choice analysed. Avoid for simple factual lookups or time-sensitive legal, medical, or market questions without fresh evidence.
Guides information security engineering—implementing and operating security controls, identity and access systems, encryption and secrets management, security tool integrations (SIEM, EDR, SOAR), cloud guardrails, hardening baselines, and remediation engineering for vulnerabilities. Use when building SSO/RBAC/PAM patterns, configuring KMS or certificate lifecycle, deploying WAF/DLP or EDR connectors, writing security-as-code policies (OPA, SCPs, CIS benchmarks), integrating logging to SIEM, automating security workflows, or validating control fixes—not for SOC triage (soc-analyst), pentesting (penetration-tester, network-pentester, web-pentester), red team (red-team-specialist), CI gates only (devsecops), platform provisioning without security ownership (infrastructure-engineer), CISO/exec program (chief-information-security-officer), security program strategy (cybersecurity), GRC program and audit prep (compliance-specialist), or product tenancy isolation (product-infrastructure-security-engineer).
End-to-end deep research and analysis pipeline. Takes a raw idea or market question, conducts deep web research, builds a competitive landscape, runs multi-framework intelligence analysis (/think), stress-tests it (/red-team), researches the red team findings, re-thinks with adversarial data, re-red-teams, and iterates until divergence between think and red-team is low (conviction stabilizes). Then generates a comprehensive single-file HTML report with all findings: market landscape, competitive analysis, intelligence briefs, red team results, how to win, and how you could lose. Use when the user says "/deepthink", "deep think", "deep research", or wants a comprehensive research-to-report pipeline on any idea, market, or strategic question.
Guides proactive threat hunting for advanced SOC—hypothesis-driven hunt campaigns, advanced SIEM/query workflows, baseline and anomaly analysis, MITRE ATT&CK–aligned techniques, threat intel fusion, detection engineering feedback, and hunt reporting with IR handoff. Use for threat hunting, proactive hunt, hypothesis-driven detection, advanced SOC, hunt campaign, detection engineering, MITRE ATT&CK hunt, anomaly hunting—not routine SOC alert triage (soc-analyst), declared incident command (incident-responder), adversary simulation campaigns (red-team-specialist), disk forensics acquisition (digital-forensics-analyst), authorized pentest (penetration-tester), or binary RE lab work (reverse-engineer).
Guides information security risk analysis—risk identification and scoring, risk registers, threat/vulnerability/control mapping, treatment recommendations (accept/mitigate/transfer/avoid), third-party and supply-chain risk framing, business impact analysis, KRIs, and risk committee or board narratives. Aligns with ISO 27005 and NIST RMF concepts without full compliance audits. Use for security risk assessment, risk register maintenance, inherent/residual risk scoring, FAIR-style quantitative framing, treatment decisions, third-party risk tiers, or executive risk reporting—not SOC alert triage (soc-analyst), pentest execution (penetration-tester, web-pentester, network-pentester), control implementation (information-security-engineer, cloud-security-engineer), GRC program and audit prep (compliance-specialist), audit evidence automation (compliance-engineer, cloud-compliance-specialist), AI model risk programs (ai-risk-governance), or adversary simulation (red-team-specialist).
Drafts, reviews, rewrites, and coaches outcome-based OKR sets across team, department, product, or company scopes. Supports five entry modes (Guided default, One-Shot via --oneshot, Sustained Coach, Audit Only, Rewrite). Diagnoses empowered-team context and adjusts framing; refuses to fabricate baselines or targets; refuses to use OKR scores for compensation; reframes feature-delivery KRs into outcome KRs. Use when planning quarterly OKRs, translating strategy into team outcomes, reviewing draft OKRs for quality, or converting roadmap-as-OKR drafts into proper OKR sets.
Guides AI ops leadership—LLM SRE, model/prompt releases, eval/incidents, cost/capacity, vendors, and cross-functional cadence. Use for AI platform ops, LLM SLAs, incidents, rollout governance, unit economics, red-team/eval gates, and team rituals—not memory (ai-memory-developer), context code (ai-context-engineer), security programs (cybersecurity), token roadmaps (ai-token-improvement-plan-engineer), solution architecture (applied-ai-architect-commercial-enterprise), skills portfolio (ai-skill-manager), or vertical AI product eng management (engineering-manager-vertical-ai-products). Prompt/eval team management and golden-set release policy: engineering-manager-agent-prompts-evals. Safeguard inference platform: ml-infrastructure-engineer-safeguards. Safeguard model research: ml-research-engineer-safeguards.