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Image-to-video (or text-to-video) via any FAL video model (Kling, Seedance, Veo), ROUTED THROUGH THE GooseWorks fal-proxy so the call bills the Ads agent. The template recipe names the model + params; image_url inputs must be public URLs (the orchestrator hosts local frames with the MCP media_upload). Returns the result video URL and downloads it. Use for the generative base clip of any video-ad format.

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Assemble an animated character-explainer video ad (any art style — Pixar-style 3D, claymation, anime, paper-cut, felt) (~77s, 9:16) built on an "N types of X" listicle spine — a recurring human protagonist plus a locked cast of N persona characters, one per list item. Given the per-scene i2v clips + a per-scene target-duration table + a narration track, it trims each clip to its scene window, re-encodes every segment to identical 1080x1920/30fps/libx264/yuv420p (decrease+pad, never crop) so the concat demuxer never drops frames, concats, and muxes audio — in RESTYLE mode the source ad's VO+music mix is reused verbatim, in ORIGINAL mode fresh per-scene VO (loudnorm I=-14) is mixed under an optional music bed (loudnorm I=-26). A static-still fallback loops a scene's keyframe when its clip is missing/failed, so the master always assembles; libass captions are burned last. FREE deterministic assembly (Python + ffmpeg, no bash, no paid calls); the recipe supplies the clips, keyframes, VO or source audio, and caption table and gates the paid cast-anchor/keyframe/Kling-i2v/VO/music calls to their own capabilities. Use for the 3d-character-explainer listicle format.

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Plan manipulator motion and generate trajectories in MATLAB. Use when the task involves moving a robot arm between configurations or poses — whether the user says "trajectory," "motion," "path," "move from A to B," or "plan." This skill applies regardless of whether the user explicitly mentions collisions or obstacles; if geometry exists in the workspace, collision safety is implicit. Triggers on: manipulatorRRT, manipulatorCHOMP, dlCHOMP, contopptraj, trapveltraj, collision-free path, motion planner, RRT, CHOMP, TOPPRA, path shortening, obstacle avoidance for manipulators, time-optimal trajectory, velocity limits, acceleration limits, occupancyMap3D, meshtsdf, collision objects as environment, trajectory between waypoints, joint interpolation, move between poses, constant velocity, trapezoidal profile, feed rate. Also triggers when a user has IK solutions or waypoints and needs to connect them — whether for time-optimal motion, constant-speed welding/cutting, or any other trajectory parameterization.

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Draft from the vault: outline from concept pages, keep citations to the user's own sources, and surface where their material disagrees. Use this skill when the user wants to write an article, post, essay or newsletter based on what they have collected, or asks what they could write about a topic. Do NOT use for research reports, for writing with no grounding in the vault, or for editing text the user wrote themselves unless asked.

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Turn raw source material in a second-brain vault into linked wiki pages: read the source, split it into concepts and entities, write or update pages, connect them to existing pages, and record the run in the log. Use this skill whenever the user drops a file into raw/, pastes an article, transcript or PDF and asks to add it to the vault, says "ingest this", "add this to my second brain", "process raw", or asks to catch up on unprocessed sources, even if they do not name the ingest command. Do NOT use for answering questions from an existing vault, for linting or repairing pages, or for editing notes the user wrote by hand.

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Post a comment (or a formal PR review) to a GitHub issue or pull request in mariadb-operator/mariadb-operator. Use whenever the user wants to publish something to GitHub for this repo — "comment on issue #123", "post this as a PR comment", "leave a note on #456", "reply on the PR" — and especially when they want the output of the mariadb-operator-pr-review skill delivered to GitHub instead of just shown in chat, e.g. "review PR #1234 and post it as a comment" or "post the review results to the PR". Always confirms the exact comment text with the user before publishing — never posts autonomously.

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Ensures the tenant has a usable Power Platform Pipelines host environment before any pipeline operation runs. Detects host state via the same resolution order as the Power Apps UI (org-db setting → BAP env metadata → default-custom-host setting); if any existing host (Platform or Custom) is found, uses it. If no host is bound to the source env, provisions a new **Platform Host** (recommended, idempotent) or a **Custom Host** via the BAP env-create API with the `D365_ProjectHost` template, or guides the user through PPAC install / `New custom host` (manual fallbacks). Polls lifecycle operations, verifies the host responds to Pipelines API calls, writes a host-check artifact other ALM skills consume. Use when asked to: "set up pipelines host", "ensure pipelines host", "no pipelines host", "install pipelines", "create pipelines host", "provision platform host", "provision custom host". Also invoked transparently by /power-pages:setup-pipeline when its host discovery step finds nothing.

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Force-links a development or target environment to a Power Platform Pipelines host, overriding any existing association with a previous host. Use when creating a deploymentenvironments record fails with "this environment is already associated with another pipelines host", or when intentionally migrating an environment from one host to another (e.g., Platform Host → Custom Host, or between two Custom Hosts). Calls the documented `ManageEnvironmentStamp` Dataverse action (the API behind the "Force Link" button in the Deployment Pipeline Configuration app). DESTRUCTIVE to the previous host: makers lose access to any pipelines in that host that used this environment. Reversible by running Force Link from the previous host. Use when asked to: "force link environment", "force-link to new host", "switch pipelines host", "environment already associated with another host", "take over pipelines association", "relink environment to host".

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Migrates a traditional Power Pages site from Bootstrap 3 to Bootstrap 5. Downloads the site, runs the pac pages bootstrap-migrate engine, reviews the change report, applies AI-assisted fixes for the residual hierarchy/CSS changes the engine only flags, uploads the migrated site (which auto-enables the Bootstrap 5 runtime flag), verifies the flag, and validates. Use when the user wants to upgrade an older Bootstrap-3 portal to Bootstrap 5. NOT for code sites (React/Vue/Angular/Astro) — those are never Bootstrap-3.

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Run a structural-review debate between two lenses — lowy (volatility-based decomposition) and hickey (structural simplicity) — on the current diff. Each reviews independently, then they cross-examine every finding until they agree per-finding, and the agreed fixes are applied. Use when the user types `/lens-debate`, or asks to "have lowy and hickey review this", "run the lens debate", "debate this diff structurally", or "argue the structure of this PR until the lenses agree".

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Expert UK Cyber Essentials and Cyber Essentials Plus advisor — the NCSC-owned, IASME-delivered baseline certification. Covers the current Danzell question set (Requirements for IT Infrastructure v3.3, mandatory for assessment accounts from April 27, 2026) and the Willow transition, the five control themes (firewalls, secure configuration, security update management, user access control, malware protection), scoping rules for cloud services, BYOD and home working, the 14-day critical-update rule, mandatory MFA for cloud services and the new auto-fail questions, CE Plus technical audits, pricing, annual renewal, the included cyber liability insurance, and procurement mandates (PPN 014, MoD Defence Cyber Certification, NHS). Use this skill whenever a user mentions Cyber Essentials, CE Plus, IASME, the UK government cyber certification, Danzell or Willow question sets, UK public-sector or MoD supply-chain security requirements, or wants a readiness gap assessment.

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Verifies UK case-law citations, pinpoint references and quotations against the official public register — The National Archives' Find Case Law — and statutory references against legislation.gov.uk, before a document that cites them is relied on, served or filed. Every check returns a graded verdict: VERIFIED, MISMATCH (the citation resolves to a different case — the classic AI miscitation), NOT ON REGISTER, OUTSIDE COVERAGE (the register cannot answer — absence proves nothing), or UNCHECKABLE (a law-report citation). The grading exists because there are two ways to get this wrong: citing a case that does not exist, and accusing a real case of not existing. Use when asked to check citations, verify a case exists, confirm a quotation is verbatim, check a pinpoint paragraph, audit a draft's authorities, screen a document for hallucinated cases, or check a statutory provision is in force. Not a substitute for reading the judgment: existence is not authority.

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Verification-first methodology for the post-WWII tribunals: the IMT at Nuremberg, the twelve Nuremberg Military Tribunals, and the IMTFE at Tokyo. Citations are verified against the official records (Blue/Green Series, Pritchard-Zaide) and the digital archives (Avalon, Harvard NTP, UVA IMTFE). Guards the four classic traps (IMT vs NMT; Nuremberg vs Tokyo; Charter article numbers; majority judgment vs separate opinions, e.g. the Pal dissent). Research aid, not legal advice. Part of the open-source "Skills for International Justice" library — methodology: github.com/jeannesulzer/international-criminal-tribunals-skills

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Use this skill whenever a lawyer or mediator needs help analyzing a dispute for mediation purposes. This includes: reviewing case materials (pleadings, contracts, correspondence, evidence) to identify issues in dispute, summarizing each party's position and interests, conducting legal analysis of the key issues, proposing mediation strategies or settlement directions, and preparing for mediation sessions. Trigger this skill when the user mentions 'mediation', 'dispute analysis', 'settlement', 'dispute resolution', 'identify issues in dispute', 'party positions', 'mediation brief', 'case analysis for mediation', 'ADR', 'mediation preparation', 'caucus strategy', 'settlement options', or any request to analyze a conflict between two or more parties with the goal of finding resolution. Also trigger when the user uploads case files and asks for a structured breakdown of who wants what, what the core disagreements are, or how the case might settle. Even if the user doesn't explicitly say 'mediation', trigger when the context involves analyzing opposing positions in a dispute with a resolution-oriented (rather than litigation-oriented) goal.

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A drafting-and-review copilot for a founders' / co-founders' agreement — the terms fixing equity, vesting, IP, roles, control, deadlock, and departure between cofounders. Jurisdiction-agnostic, anchored on the Delaware C-corp default. Two modes: DRAFT (intake → equity & vesting → clauses → blocker triage → pre-signature check) and REVIEW (audit an existing agreement against an 18-clause checklist and red-flag scan). It handles the highest-dispute terms first-class: the equity split as documented reasoning (not a fake calculator), reverse vesting and the 83(b) clock, present-tense IP assignment (the Stanford v. Roche trap), leaver buyback and dead equity, and the deadlock clause most tools omit. It drafts for the venture, never one founder against another. Not legal advice.

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Turn an interpretive-ambiguity audit of a legal text — contract, statute, regulation, or judicial opinion — into a polished deliverable. Produces a multi-page website (default), a single-page interactive site, a Microsoft Word document, a PowerPoint deck, or a LaTeX/PDF. Use whenever a user has a stress-test result, ambiguity audit, or "where will this be litigated" scenarios and wants to publish, present, or share them. Triggers on "publish the audit," "make a report from this," "turn this into a website / deck / brief / Word doc," "make a Netlify site," "build slides of these ambiguities," "render the scenarios," "package this stress test," "produce a LaTeX version," and similar. Pairs with the ambiguity-stress-test skill (the underlying analysis) but works on any structured or semi-structured ambiguity analysis. Visual design is opinionated but the user can override colors, fonts, and brand label. Most formats need Python and a writable filesystem; single-file HTML works where the host has neither.

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Design game experience, systems, and levels. Converge the chosen concept into one GAME_DESIGN defining the player promise, core loop, how the world responds, the systems actually needed, level pacing, feedback, failure, and the specification for a complete playable slice. Use for design the game world, deepen the gameplay and levels, write the game design document, design the branching story structure, scenes, dialogue and consequences. 游戏体验、系统与关卡策划。把选定概念收束为一份 GAME_DESIGN，定义玩家承诺、核心循环、世界响应、必要系统、关卡节奏、反馈、失败及可供构建的完整切片设计。用于设计游戏世界、深化玩法和关卡、设计互动叙事的场景对白与分支因果等需求。

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Your brand designer. Names the business (with the trademark, domain and handle checks to run before falling in love with a name), writes the voice, a one-line promise and a tagline, and briefs the look: colours, type, logo and the first things a customer sees, so they match the positioning the marketing director chose. Use when the user says "name my business", "brand this", "logo", "brand identity", "what should it look like", "tagline", or "brand voice".

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Builds an offer too good to refuse. Lists every problem the buyer hits on the way to the result they want, turns each into a solution, trims to what is cheap to deliver and valuable to the buyer, and stacks it with honest bonuses, a guarantee the CFO can afford, real urgency and a clear name. Scores it on the value equation (outcome, likelihood, time, effort) and re-tests it on a quick buyer panel. Use when the user says "make my offer better", "why won't people buy", "what should I include", "guarantee", "bonuses", "grand slam offer", or after the panel shows people passing.

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The consumer panel. Spins up a swarm of buyer sub-agents (default 100, --quick for 20) trained on the user's target customer, each with a different income, age, buying behaviour and objection, shows every one the same pitch, and runs the business through 100 buyer scenarios to see who buys, who doesn't, and why. Tallies the answers into buy rates by segment, the reasons people pass in their own words, what would flip a no, and price answers for founder-pricing. Use when the user says "would people buy this", "test it on customers", "run the consumer panel", "simulate buyers", "who is my customer", or "validate demand".

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The ORFhunteR package is a R and C++ library for an automatic determination and annotation of open reading frames (ORF) in a large set of RNA molecules. It efficiently implements the machine learning model based on vectorization of nucleotide sequences and the random forest classification algorithm. The ORFhunteR package consists of a set of functions written in the R language in conjunction with C++. The efficiency of the package was confirmed by the examples of the analysis of RNA molecules fr

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omicsViewer visualizes ExpressionSet (or SummarizedExperiment) in an interactive way. The omicsViewer has a separate back- and front-end. In the back-end, users need to prepare an ExpressionSet that contains all the necessary information for the downstream data interpretation. Some extra requirements on the headers of phenotype data or feature data are imposed so that the provided information can be clearly recognized by the front-end, at the same time, keep a minimum modification on the existin

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We propose an Asymmetric Within-Sample Transformation (AWST) to regularize RNA-seq read counts and reduce the effect of noise on the classification of samples. AWST comprises two main steps: standardization and smoothing. These steps transform gene expression data to reduce the noise of the lowly expressed features, which suffer from background effects and low signal-to-noise ratio, and the influence of the highly expressed features, which may be the result of amplification bias and other experi

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Build prospect lists where the prospect is already one hop from the client, and write the line that says so. Seven members, each with its own source. Current-customer alumni is the priority member - everyone who ever worked at one of the client's customers or case-study companies and has since moved on. Triggers on "warm intro", "who do we know at that account", "they used to work at our customer", "alumni of our case study company", "shared investor angle", "who is in the same city as our rep", "did they visit our site". Outputs warm_intro_line plus a per-member evidence column.

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