Skills
97,905 packaged capabilities and playbooks for agents. Install any of them with one command.
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Clean, split, and featurize multivariate time-series data before embedding it with the Omega model. Bundles three reusable building blocks: `DataPreprocessor` (diagnose timestamp regularity, gaps, and nulls; build continuous gap-aware temporal blocks with imputation), `DataSplitter` (out-of-time or random train/test split that respects temporal order), and `FeaturePreparer` (pivot per-sensor embeddings into a "joint state" (X, y, metadata) matrix with optional L2 / standardization / PCA). Use this skill when the user is preparing raw sensor CSVs for the Omega model (`atai-newton-omega-model`), when training data has gaps and they're unsure whether to drop / impute / split, or when an n-shot CSV looks noisy and they want a principled cleanup pipeline. Do NOT use this skill to run inference or produce embeddings (use `atai-newton-omega-model`). Do NOT use for video / image / text data (use `atai-newton-fusion-model`) — time-series only.
Computes the optimal shaded bid for a first-price sealed-bid auction given a true private value, an estimate of the number of competing bidders N, and a value-distribution assumption. Implements the `(N-1)/N` equilibrium shading rule for uniform private values, adjusts for log-normal or empirical value distributions, layers a risk-aversion adjustment, and caps output against the bidder's remaining budget. Domain-neutral auction theory reusable across fantasy sports (baseball FAAB, NBA/NHL waiver auctions), prediction-market limit sizing, sealed procurement bids, and any blind-bid context. Use when user mentions "first-price auction bid", "sealed bid shading", "(N-1)/N", "FAAB bid amount", "auction shading", "optimal bid first-price", "bid for sealed-bid", "blind bid sizing", or when downstream logic needs a principled shade factor rather than an ad-hoc heuristic.
Guides privacy audit risk assessment including risk universe development, inherent and residual risk scoring, control effectiveness evaluation, risk-based audit planning, heat map generation, risk appetite alignment, and audit prioritization by risk exposure. Covers the full audit risk assessment cycle from scoping through ongoing monitoring. Keywords: audit risk assessment, risk universe, inherent risk, residual risk, control effectiveness, risk-based audit planning.
Add transitions at auto-editor's cuts — cross-dissolves, Premiere Pro's transitions (push, clock-wipe, glitch, page-peel, iris-round, and the rest, including its Legacy folder), and audio crossfades — and carry them into Premiere, DaVinci Resolve, Final Cut Pro, Shotcut or Kdenlive. Use when someone wants smoother cuts, fades at the start and end, a particular transition, or transitions that survive an editor export or import.
Automated enforcement of GDPR Article 5(1)(e) storage limitation principle. Covers TTL-based deletion, retention policy engines, archival workflows, legal hold exemptions, and lifecycle automation. Includes technical implementation patterns for automated data expiry and defensible deletion across distributed systems.
A methodology for lateral movement from Azure Cloud to on-premises AD. Use after obtaining Azure/Entra ID privileges when access to an on-premises Active Directory environment is needed, when the target uses a hybrid identity architecture such as Azure AD Connect/Cloud Sync/PTA/Federation, or when PRT/Certificate/Cookie credentials are needed for Cloud-to-OnPrem lateral movement. Covers 14 lateral techniques: Pass the PRT/Certificate/Cookie, Cloud Kerberos Trust, Connect Sync/Cloud Sync credential extraction, PTA Agent backdoor, Federation Token forgery, Seamless SSO silver ticket, Exchange Hybrid impersonation, Arc GPO deployment script injection, and on-premises cloud credential extraction.
Guidance for the security-side use of Azure Monitor and Log Analytics — designing the workspace strategy that feeds Microsoft Sentinel and Defender for Cloud, choosing analytics vs basic vs auxiliary log tiers, retention and archive, table-level transformations to drop noise pre-ingestion, Data Collection Rules (DCRs) and Azure Monitor Agent (AMA), workspace topology (single vs regional vs sovereign), commitment tiers and cost control, customer-managed keys for the workspace, RBAC including table-level RBAC, integration with Sentinel (workspace requirements), and decommissioning legacy MMA. WHEN: Log Analytics workspace design, Azure Monitor security data, Sentinel workspace, log tier basic auxiliary, AMA Azure Monitor Agent, DCR data collection rule, drop columns ingestion transform, log retention archive, workspace CMK, table-level RBAC, log ingestion cost control. DO NOT USE for Sentinel detection authoring (use sentinel-detection-engineering), App Insights instrumentation (use appinsights-instrumentation), or non-security observability.
Manages privacy compliance for employee background checks including criminal record processing under Art. 10 GDPR, DBS checks (UK), national law variations, and reference verification. Applies proportionality and data minimisation to pre-employment screening, defines retention limits, and addresses role-based necessity assessments. Keywords: background check, criminal record, Art. 10, DBS, pre-employment screening, vetting, data minimisation, proportionality.
Scandit Barcode Capture (`BarcodeCapture`) in native iOS (Swift) projects — the low-level, full-control single-barcode scanning mode (BarcodeCapture + DataCaptureView + overlay), without the pre-built SparkScan UI. Use for integration, scan settings, result handling, overlay customization, SDK version migration (v6→v7→v8), replacing a third-party barcode scanner, or troubleshooting.
Extract Bilibili videos and opus/article posts into readable Markdown knowledge notes. Use when the user asks to extract/refine/summarize/organize B 站 or bilibili video/image-text/dynamic/opus content, save a B 站 note to a local knowledge base, include useful comments, handle multi-part videos, fetch B 站 AI subtitles, download opus images, or fall back to audio transcription.
Guidance for choosing the right protein binder design tool. Use this skill when: (1) Deciding between BoltzGen, BindCraft, or RFdiffusion, (2) Planning a binder design campaign, (3) Understanding trade-offs between different approaches, (4) Selecting tools for specific target types. For specific tool parameters, use the individual tool skills (boltzgen, bindcraft, rfdiffusion, etc.).
Develop brand positioning strategy including positioning statements, perceptual maps, and brand personality/archetype analysis. Use this skill when the user needs to define or refine how their brand is perceived relative to competitors, craft a positioning statement, build a brand identity framework, or map competitive positions — even if they say 'what makes us different', 'our brand feels generic', or 'how do customers see us vs competitors'.
Analyze unit economics to evaluate per-unit profitability and business model scalability. Use this skill when the user needs to assess whether each transaction, customer, or product unit is profitable, evaluate startup viability, or optimize contribution margins — even if they say 'does our business model work', 'what's our margin per order', or 'can we scale profitably'.
Find what a change could break somewhere else before it ships, beyond the diff, and prove the one fact it's safe because of by running real code instead of writing it up. Use for “blast radius of X,” “what could this break,” or reviewing a small diff you don't trust. Reach for it before shipping a change that deletes or alters something other code depends on.
Blender 5.x geometry nodes — procedural modeling, scattering, mesh/curve/volume ops, simulation zones, repeat zones, Bone Info, Font socket, UV nodes, volume grid nodes, and scripting node trees via Python (bpy). Includes 5.0 and 5.1 changes.
Use this skill when reviewing BoxLang code for quality, correctness, security vulnerabilities, performance issues, style violations, or when providing structured code review feedback following BoxLang best practices and security guidelines.
Use this skill when working with BoxLang's interceptor/event system: creating interceptors, registering announcement points, announcing custom events with announce() or announceAsync(), building pre/post operation hooks, validation interceptors, security guards, or leveraging BoxRegisterInterceptor() BIF for standalone and module-based interception.
Use this skill when installing, configuring, or using BoxLang modules: box install, boxlang.json module settings, BoxLang+ premium modules (bx-pdf, bx-redis, bx-csv, bx-spreadsheet), CFML compatibility, ORM, mail, and module introspection.
Scans Reddit, X, LinkedIn, Instagram, TikTok, YouTube, blogs, news, and review platforms for brand mentions — scoring each across four dimensions (reach, velocity, sentiment, and risk-topic match) so teams can respond before one spirals. Sources adapt to the market: B2B brands weight LinkedIn, G2, and trade press; consumer brands weight TikTok, Instagram, and YouTube. Each is bucketed into Crisis / Watch / Engage / Log with a suggested owner and response window. Use when asked to "monitor brand mentions", "scan for brand mentions", "what are people saying about [brand]", "brand monitoring", "social listening", "run a brand sweep", "find high-risk mentions", or any variation of brand monitoring across web and social. Do NOT use for one-time company research or due diligence — use company-deep-dive instead. Do NOT use for competitor messaging/positioning analysis — use competitor-positioning instead. Do NOT use for funding/hiring/business signals on a competitor — use competitor-intel instead.
Use this skill to analyze a brand from their website before creating content. Triggers: "analyze brand", "research brand", "brand guidelines", "brand profile", "understand brand", "brand colors", "brand voice", "before creating content for" Extracts: colors, typography, voice/tone, products, audience, competitive positioning. Outputs a reusable brand_profile.json that producer skills can use.
Builds a comprehensive breach response team playbook defining CSIRT and privacy team structure with named roles (incident commander, legal counsel, communications, IT forensics, DPO), escalation matrices, communication templates, pre-negotiated vendor contacts, and regulatory authority contacts organized by jurisdiction. Keywords: breach response playbook, CSIRT, incident response team, escalation matrix, communication templates, vendor contacts.
Bugcrowd-specific reporting tactics complementing report-writing: VRT category search-and-fallback strategy when no exact match exists, manual severity override when VRT defaults underrate impact, severity-request paragraph as first body section, OOS-clause rebuttal templates (rate limiting on auth-flow endpoints, debug-info framing, user-enumeration with sensitive PII, theoretical-issue counter), chained-finding cross-reference patterns, target selection for QA-vs-prod programs, researcher-side hygiene (Bugcrowdninja email alias, account state restoration, friendly-tester posture). Use when filing a Bugcrowd submission, when VRT default seems wrong, when triager closes as OOS or downgrades severity, when chaining linked submissions, or when scope distinguishes production from QA. Pairs with report-writing and triage-validation.
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An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.