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Detect missing authentication and broken function-level authorization vulnerabilities in a codebase using a three-phase approach: recon (map endpoints and the role/permission system), batched verify (check auth/authz in parallel subagents, 3 endpoints each), and merge (consolidate batch results). Covers unauthenticated access and vertical privilege escalation (e.g., regular user accessing admin-only functions). Requires sast/architecture.md (run sast-analysis first). Outputs findings to sast/missingauth-results.md. Use when asked to find missing auth, broken access control, or privilege escalation bugs.

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Perform codebase analysis and architecture mapping as the first phase of a security assessment. Explores the tech stack, frameworks, entry points, data flows, and trust boundaries. Outputs sast/architecture.md. Run this before any vulnerability detection skill. Use when asked to analyze a codebase for security or when sast/architecture.md does not yet exist.

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Map tanstack ecosystem partner metadata to installable add-on ids using tanstack ecosystem --json, tanstack create --list-add-ons --json, and tanstack create --addon-details --json. Covers exclusive categories, provider options, and router-only compatibility constraints.

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Anti-slop skill for PRODUCT UI - dashboards, data tables, forms, multi-step flows, settings, list/detail, app shells. The agent reads the surface, budgets the frame first, and ships dense interfaces that are correct at every edge case (overflow, long labels, empty/error/loading states, i18n expansion, keyboard/a11y). House-system-first; maps to Carbon/Polaris/Atlaskit/Fluent/Primer/Material3/Radix-shadcn/Ant. The counterpart to taste-skill, which owns landing/portfolio/marketing.

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Master skill — set up the full agent harness for any repo so an agent can work it reliably: legible (map-not-manual docs + custom lints), executable (one-command dev stack), verifiable (e2e gate + a verify-before-ship loop), plus commit hygiene and entropy control. Use when onboarding a new/unfamiliar codebase to agent-driven development — "set up the harness", "make this repo agent-ready", "harness this codebase".

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INVOKE THIS SKILL when building, testing, or deploying Managed Deep Agents in LangSmith. Walks a user through their first agent end to end — interviewing them about what they want to build, mapping it onto what MDA can actually do, then scaffolding and deploying it. Covers the file-based project layout; define_deep_agent / defineDeepAgent; instructions, skills, memory, identity, tools, MCP servers, connections, middleware, sandboxes, schedules, channels, and evals; the mda CLI; GitHub deployments; and Context Hub.

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Generates an x-ray.md pre-audit report covering overview, enhanced threat model (protocol-type profiling, git-weighted attack surfaces, temporal risk analysis, composability dependency mapping), invariants, integrations, docs quality, test analysis, and developer/git history. Triggers on 'x-ray', 'audit readiness', 'readiness report', 'pre-audit report', 'prep this protocol', 'protocol prep', 'summarize this protocol'.

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Use when deciding which English agriculture / environment / earth-science journal skill to invoke next, comparing fit across the 30-journal agriculture-and-environment roadmap, or routing a manuscript before venue-specific re-framing. Routes by sub-field (agronomy / plant / soil / food / environment / earth / climate), contribution type, and evidence shape (field trial / lab assay / observational survey / model / dataset).

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Use when building exhibits for an American Anthropologist (AA) manuscript — photographs, maps, site plans, artifact images, kinship diagrams, transcripts, evidence tables, and multimodal media — so they are self-contained, accessible (alt text), ethically cleared (consent, permissions), and count toward the word budget. Designs exhibits; it does not run analysis or clear permissions for you.

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Use when anticipating how AEJ: Economic Policy referees and editors will read a manuscript, before submission or before an R&R, to pre-empt the objections that sink policy-evaluation papers. Maps likely pushback to fixes and calibrates expectations; it does not write the response letter (see aejpol-rebuttal) or fix the identification.

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Use when an AEJ: Economic Policy manuscript needs a framework that maps reduced-form estimates into a welfare, cost-benefit, or distributional policy object — sufficient statistics, MVPF, optimal-policy, or a small applied model. Builds the estimate-to-welfare bridge and states its assumptions; it does not run the empirical estimation or write the prose.

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Use when the credibility of the causal evaluation of a policy is the bottleneck for an AEJ: Economic Policy manuscript — DID/event study, IV, RDD/bunching, or RCT of a program. Stress-tests the quasi-experimental policy-evaluation design to the AEJ: Policy bar before exhibits are finalized; it does not build the welfare mapping or write exhibits.

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Use when the causal identification argument is the bottleneck for an American Economic Journal: Applied Economics (AEJ: Applied) manuscript — RCT, difference-in-differences/event study, regression discontinuity, IV, or shift-share. Stress-tests the data-to-causal-estimate mapping to the AEJ: Applied credibility bar before exhibits are finalized; it does not write the prose or build the package.

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Use when strengthening ACM CCS reproducibility evidence, including the artifact-availability posture, threat-model-to-evidence mapping, attack reproduction steps, defense overhead measurement, measurement-dataset provenance, environment and version pinning, and honest justification when artifacts cannot be shared.

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Use when strengthening an AAAI paper's reproducibility checklist (placed after references), experimental traceability, seed and hyperparameter reporting, compute and cost disclosure, dataset access and licensing, code/data ZIP readiness, and the claim-to-evidence map that Phase-1 reviewers use to judge rigor across AAAI's broad AI scope.

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Audit Xcode project configuration, build settings, scheme behavior, and script phases to find build-time improvements with explicit approval gates. Use when a developer wants project-level build analysis, slow incremental builds, guidance on target dependencies, build settings review, run script phase analysis, parallelization improvements, or module-map and DEFINES_MODULE configuration.

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Pre-sales-call intelligence composite. Deep dives on the person AND their company before a sales call, then maps findings to your product to generate talking points, objection prep, and a call strategy. Goes beyond generic attendee research — this is sales-specific intelligence that helps SDRs, AEs, and founders walk into calls with a plan. Tool-agnostic — works with any CRM, research source, and calendar.

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Crawl a website's sitemap and blog index to build a complete content inventory. Lists every page with URL, title, publish date, content type, and topic cluster. Groups content by category and topic. Optionally deep-reads top N pages for quality analysis and funnel stage tagging. Use before SEO audits, content gap analysis, or brand voice extraction.

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Monitor Twitter/X, Reddit, LinkedIn, and Hacker News for trending narratives, viral posts, and hot-button topics in your space. Maps trends to ad hook opportunities with timing urgency scores. Tells you what to run ads about right now while the topic is hot.

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End-to-end Google Search Ads campaign builder. Performs deep keyword research (competitor SEO, review language mining, Reddit/HN community terminology, site audit), builds keyword architecture with funnel mapping and intent classification, creates ad group structure, generates headline/description variants, builds negative keyword lists, recommends bid strategy, and exports a campaign-ready CSV for Google Ads Editor import.

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Render a punchy ~12s vertical (9:16) music-only direct-response OFFER ad as a 4-beat kinetic-typography film — HEADLINE slam → real PRODUCT drop → CLAIM/proof → CTA pill — from one config of copy slots, a real product photo, a brand palette, fonts, bpm, and beat split. DETERMINISTIC + FREE (a bundled Remotion project; springs + interpolate, no AI-gen for visuals). Backgrounds are engine gradient divs off the palette, props are inline SVG, the ONLY composited bitmap is the REAL product photo (objectFit:contain, never stretched), and ALL headline/claim/CTA/URL/wordmark text is typeset in the engine — never AI-rendered (the format's credibility guard). A driver binds the config to Remotion input props, renders the 9:16 master, and derives a 1:1 center-crop with ffmpeg. Two gating checks run before render (claim verbs must match the product's physical format; the claim beat needs an edge-entry mechanism prop). Use for the motion-graphics-offer-ad format.

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Assemble the FREE steps of the product-hypermotion + kinetic-typography video format — dice ONE Seedance 2.0 hypermotion clip into 5-6 segments and intercut them with PIL kinetic-typography spec/CTA cards (italic skew, 1.08x outline echo, 3D extrusion, slam-with-shake, inversion flash) plus a real-logo PIL end card (base64-decoded from the brand SVG), center-crop 1:1 to 9:16, and explicit-map mux a music bed. Deterministic, FREE (PIL + FFmpeg), no paid calls, the real logo and spec typography stay pixel-crisp. The paid steps (the ONE Seedance i2v, the music) are separate capabilities; the recipe orchestrates them. Use for the product-hypermotion format.

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Ports existing Databricks notebooks and jobs to Fabric, covering dbutils to notebookutils, secret scopes to Key Vault, DBFS to OneLake, Unity Catalog mapping to schema-enabled Lakehouses, Jobs and Delta Live Tables to Spark Job Definitions and Pipelines, and Photon to the Native Execution Engine. Use whenever Databricks code has to be converted. For Fabric notebook code that is not being migrated, use spark-cli.

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Migrates Synapse Data Factory pipelines to Fabric Data Factory, turning linked services into Fabric connections, inlining datasets into activities, converting global parameters to Variable Libraries, and mapping SynapseNotebook to TridentNotebook. Use for pipeline JSON. For Synapse Spark notebook code use synapse-migration.

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