profiling-transaction-fingerprints

Configures SSO authentication and SCIM 2.0 provisioning for CockroachDB across four distinct layers — Cloud Console SSO (SAML/OIDC), DB Console SSO (OIDC), SQL/Cluster SSO (JWT or LDAP/AD), and SCIM 2.0 automated provisioning. Use when enabling centralized identity management, setting up SSO for compliance, or automating user lifecycle management.

Audits a self-hosted CockroachDB cluster against the CIS CockroachDB Benchmark v1.0.0 Level 1 controls. Supports two audit depths — quick automated scans and full CIS audit procedures. Produces a structured PASS/FAIL/MANUAL report covering installation, system hardening, logging, user access, data protection, and CockroachDB settings. Use when preparing for CIS compliance assessments, hardening self-hosted deployments, or validating security posture against industry benchmarks.

Audits the security posture of a CockroachDB cluster (Cloud or self-hosted) across network, authentication, authorization, encryption, audit logging, and backup dimensions. Use when assessing cluster security readiness, preparing for compliance reviews, or investigating security configuration gaps.

Configures SQL audit logging on CockroachDB clusters to capture security-relevant events including authentication, privilege changes, and sensitive data access. Use when enabling audit logging for compliance, setting up role-based audit policies, or verifying audit configuration.

Configures and hardens IP allowlists for CockroachDB Cloud clusters to restrict network access to authorized CIDR ranges. Use when tightening network security, removing overly permissive allowlist entries like 0.0.0.0/0, or setting up allowlists for a new cluster.

Configures log and metric export for CockroachDB Cloud clusters to external monitoring services including AWS CloudWatch, GCP Cloud Logging, and Datadog. Use when setting up log export for audit compliance, configuring metric export for monitoring, or troubleshooting log delivery issues.

Configures private network connectivity for CockroachDB Cloud clusters including AWS PrivateLink, GCP Private Service Connect, Azure Private Link, egress private endpoints, and VPC peering. Use when setting up private endpoints to eliminate public internet exposure, configuring egress to external services like Kafka, or establishing VPC peering.

Hardens CockroachDB user privileges by auditing and tightening role-based access control, reducing admin grants, restricting PUBLIC role permissions, and applying least-privilege principles. Use when reducing excessive privileges, cleaning up admin access, or implementing RBAC best practices.

Rigor Explore compatible skill slug for meaningful and potentially novel deep learning research candidates. Use when the researcher has chosen the task family, dataset, benchmark, evaluation method, provided SOTA references, and wants candidate-only exploration on top of `current_research` with auditable repo understanding, idea gating, fair comparison, and governed experiments written to `explore_outputs/`. Do not use for README-first trusted reproduction, open-ended direction finding, narrow code-only or run-only exploration, passive repo analysis, verified novelty claims, or implicit experimentation.

Rigor Reproduce compatible skill slug for README-first deep learning repository reproduction. Use when the user wants an end-to-end, minimal-trustworthy flow that reads the repository first, selects the smallest documented inference or evaluation target, coordinates intake, setup, trusted execution, optional trusted training, optional repository analysis, and optional paper-gap resolution, enforces conservative patch rules, records evidence assumptions deviations and human decision points, and writes the standardized `repro_outputs/` bundle. Do not use for paper summary, generic environment setup, isolated repo scanning, standalone command execution, silent protocol changes, score chasing, or broad research assistance outside repository-grounded reproduction.

Rigor Train skill for deep learning research repositories. Use when a documented or selected training command should be run conservatively for startup verification, short-run verification, full kickoff, or resume, with command, config, seed, log, checkpoint, status, and metric evidence written to standardized `train_outputs/`. Do not use for environment setup, exploratory sweeps, speculative idea implementation, or end-to-end orchestration.

Rigor Improve / Rigor Explore run leaf skill for bounded exploratory evidence in deep learning research repositories. Use when the researcher explicitly authorizes exploratory runs such as small-subset validation, short-cycle guess-and-check, batch sweeps, idle-GPU search, or quick transfer-learning trials, with fair-comparison caveats and no-overclaim summaries in `explore_outputs/`. Do not use for end-to-end exploration orchestration on top of `current_research`, trusted baseline execution, conservative training verification, default routing, verified SOTA claims, or implicit experimentation.

Search, scrape, crawl, extract structured data, and monitor web pages via the ScrapeGraph AI CLI. Use when the user asks to search the web, scrape a webpage, grab content from a URL, extract JSON from a site, crawl documentation or site sections, monitor a page for changes, inspect request history, check ScrapeGraph credits, or validate API setup.

When the user wants to create sales collateral, pitch decks, one-pagers, objection handling docs, or demo scripts. Also use when the user mentions 'sales deck,' 'pitch deck,' 'one-pager,' 'leave-behind,' 'objection handling,' 'deal-specific ROI analysis,' 'demo script,' 'talk track,' 'sales playbook,' 'proposal template,' 'buyer persona card,' 'battle card,' 'battlecard,' 'competitive one-pager,' 'win-loss analysis,' 'why are we losing deals,' 'loss reasons,' 'how do I respond to this objection,' 'prospect just said,' 'help my sales team,' 'sales materials,' or 'what should I give my sales reps,' 'cold call script,' or 'voicemail script.' Use this for any document or asset that helps a sales team close deals. For public competitor comparison pages, see competitors. For running buyer interviews or churn research, see customer-research. For marketing website copy, see copywriting. For cold outreach emails, see cold-email. For the offer being sold (bonuses, guarantees, pricing structure), see offers.

Web search and content extraction with Tavily and Exa via inference.sh CLI. Apps: Tavily Search, Tavily Extract, Exa Search, Exa Answer, Exa Extract. Capabilities: AI-powered search, content extraction, direct answers, research. Use for: research, RAG pipelines, fact-checking, content aggregation, agents. Triggers: web search, tavily, exa, search api, content extraction, research, internet search, ai search, search assistant, web scraping, rag, perplexity alternative

When the user wants to conduct, analyze, or synthesize customer research. Use when the user mentions "customer research," "ICP research," "talk to customers," "analyze transcripts," "customer interviews," "survey analysis," "support ticket analysis," "voice of customer," "VOC," "build personas," "customer personas," "jobs to be done," "JTBD," "what do customers say," "what are customers struggling with," "Reddit mining," "G2 reviews," "review mining," "digital watering holes," "community research," "forum research," "competitor reviews," "customer sentiment," "PMF survey," "product/market fit survey," "customer interview questions," "interview outreach," "Sales Safari," or "find out why customers churn/convert/buy." Use for analyzing existing research assets, mining online sources, AND running primary research (interviews and surveys). For writing copy informed by research, see copywriting. For acting on research to improve pages, see cro.