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Found 6,686 Skills
Use this skill when the user requests to "read paper", "analyze paper", "summarize paper", "read a paper", "analyze literature", "help me look at this paper", "paper notes", or provides a PDF file that appears to be an academic paper. It is specialized for CV/DL papers. It also supports Zotero integration: "read this paper...", "quickly look at this paper...", "critically analyze this paper...", "read XXX from Zotero", "batch read papers under the VLA category in Zotero" **Important Trigger Phrases**: "read XXX", "read this one", "help me read" → must call this skill
CLI for moving AI-generated UI designs from Google's Stitch platform into development workflows with local preview, site generation, and agent integration.
Interactive setup guide for using Infisical as a secret management tool in your projects. Helps users integrate Infisical into local development (CLI), Docker containers (build-time and runtime secret injection), CI/CD pipelines (GitHub Actions, GitLab CI), Kubernetes (Operator + CRDs), and application code (Node.js, Python, Go, Java, .NET, Ruby SDKs). Also walks through choosing and configuring machine identity auth methods (Universal Auth, AWS Auth, Kubernetes Auth, OIDC, etc.). Use this skill whenever someone asks about: using Infisical, injecting secrets, infisical run, infisical init, connecting their app to Infisical, Docker secrets, Kubernetes secrets operator, machine identity setup, SDK initialization, CI/CD secret injection, or 'how do I get my secrets into my app'.
Design, build, and optimize dashboards for RIA practice management with AUM tracking, revenue analytics, and KPI frameworks. Use when the user asks about tracking firm-level metrics, monitoring advisor productivity, measuring organic growth rate, analyzing client retention and attrition, building executive or branch manager views, setting up exception alerts for NIGO or rebalancing drift, benchmarking against industry peers, or designing role-based dashboard access. Also trigger when users mention 'how is the practice doing', 'revenue per advisor', 'client attrition', 'net new assets', 'effective fee rate', 'practice benchmarking', 'AUM growth decomposition', 'advisor capacity', or 'referral tracking'.
Identify and prevent sales practice violations under FINRA and SEC rules governing broker-dealer conduct. Use when the user asks about churning or excessive trading metrics, mutual fund breakpoint discounts, selling away or private securities transactions, outside business activities, unauthorized trading, supervisory procedure design, senior investor protections, trusted contact persons, variable annuity suitability, or options account approval. Also trigger when users mention 'turnover ratio is high', 'rep did trades without authorization', 'breakpoint abuse', 'trusted contact for elderly client', 'selling away from the firm', 'supervision failure', '1035 exchange review', 'marking the close', or ask whether a broker's conduct violates FINRA rules.
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 technical program management for security coordinated vulnerability disclosure (CVD)— disclosure policy, intake and triage SLAs, researcher coordination, fix/remediation tracking, embargo and publication timelines, CVE/advisory coordination, bug bounty program operations, and cross-functional gates (security engineering, legal, comms, product). Use when running a CVD or responsible disclosure program, disclosure calendar, bounty ops, or unblocking multi-team remediation for reported vulnerabilities—not for hands-on pentest (offensive-security-analyst), SOC triage (defensive-security-analyst), vuln scanning in CI (devsecops), enterprise security strategy (cybersecurity), generic non-security programs (technical-program-manager), or contract redlines (commercial-counsel).
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).
This skill should be activated when the user requests to "deepen a topic", "analyze a topic", "help me write an outline", "will this topic go viral", "help me diagnose a topic", "is this topic worth pursuing", or "how to improve this topic". Even if the user only shares a topic and asks for opinions, you should proactively initiate the diagnosis process instead of providing a simple response. Driven by the cognitive hijacking theory, it features four modules: Perspective Collision (challenging the topic's premise), Topic Diagnosis (graded using 🛵🚗✈️), Outline Design (emotional peak planning), and Style Validation (alignment with li-writer style). It generates a comprehensive deepening report and saves it as a file. Do NOT trigger this skill for: merely recording topics (use li-recorder), directly writing scripts (use li-writer). Use when the user wants to "develop a topic", "analyze topic potential", "write an outline", "will this topic go viral", or needs full topic diagnosis + outline design. Trigger even if the user just shares a topic and asks for opinions.
Profile a new tabular dataset before modeling. Find target leakage, missing data patterns, high-cardinality categoricals, near-constant features, redundant pairs, and non-linear relationships that Pearson correlation misses. Use whenever the user hands you a CSV or parquet and asks "what should I do with this?" Always run this skill before training any model on data you haven't seen before.
Remove the DebugBridge SPM package and all #if DEBUG wiring from an iOS app. Cleans up StateServer, DebugOverlay, accessor codegen output, and app-side hooks installed by /ios-qa. This is a convenience wrapper — the structural Release-build guard (Package.swift conditional + CI swift build -c release check) is the safety-critical path. Use when asked to "clean the iOS debug bridge", "remove DebugBridge", or "strip the gstack iOS instrumentation". (gstack) Voice triggers (speech-to-text aliases): "clean the iOS debug bridge", "remove DebugBridge", "strip the gstack iOS instrumentation".
Deeper risk assessment for a single feature or product area when the launch review found something that needs more than a line item. Structured analysis: what could go wrong, how likely, how bad, what mitigates it. Use when user says "deep dive on this risk", "risk assessment for [feature]", "what could go wrong with", or when launch-review flags a novel issue.