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Generate comprehensive edge cases and test scenarios by decomposing features across 12 dimensions. Use before implementation or testing to catch issues early.

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Generate pytest test cases for Python functions and classes

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Scaffold a first eval suite for an agent: mine real failures into cases, write behavioural checks over traces, and generate the runner. Use when the user wants evals, regression tests for an agent, a golden set, or asks how to know a prompt/model change did not break things. Do NOT use for a single task's done-check (goal-test) or for auditing context (context-audit).

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Turn a vague task into a testable definition of done and generate an executable goal-test script for it, optionally with a bounded retry loop around a headless agent. Use when the user wants to run an agent in a loop, asks how to know when an agent task is finished, or says a goal like "improve X" needs to become checkable. Do NOT use for building eval suites over many cases — that is evals-bootstrap.

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Use when captions, subtitles, or the spoken text of a YouTube video is needed — even if not explicitly requested: pasted video links or IDs, requests to read, quote, or translate a video, accessibility needs, deaf/HoH use cases, content review, or language learning. Fetches timestamped caption data from any YouTube video. Not for uploading subtitles or account management.

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Simple scroll-triggered reveal animations using AOS (Animate On Scroll). Use this skill when building marketing pages, landing pages, or content-heavy sites requiring basic fade/slide effects without complex animation orchestration. Triggers on tasks involving scroll animations, scroll-triggered reveals, AOS, simple animations, or basic scroll effects. Alternative to GSAP ScrollTrigger and Locomotive Scroll for simpler use cases. Compare with motion-framer for React-specific animations.

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Organize a Power BI or Analysis Services semantic model end to end so it is ready for report authors, Excel users and Copilot - table groups, display folders, Title Case business names and naming conventions, hierarchies, sort-by columns, hiding, Analyze in Excel (IsAvailableInMDX), descriptions, format strings, data categories, context annotations, DAX formatting and UDFs, calculated-object justification, duplicate removal, perspectives, translations and security roles. Use whenever the user asks to "organize", "tidy", "clean up", "polish", "prepare", "standardize" or "make report-ready" a model or one table in it (for example "organize the date table"), to "fix naming conventions", "rename fields", "make names human readable" or "fix abbreviations", even when they name only one of these aspects, and whenever a model is driven through the Tabular Editor 3 MCP or the te CLI for that purpose. Not for DAX performance tuning (dax skill) or model design and star-schema changes (semantic-model skill).

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Use when investigating common or slow variants, repeated work, unusual paths, or a specific Process Mining case.

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Integrates Power Pages generative-AI summarization APIs (PREVIEW) into a Single Page Application (SPA) site — the Search Summary API and the Data Summarization API — on any record-detail or list page. Generates per-target service code (CSRF-handled) and AI site settings; delegates Web API settings, table permissions, and web roles to `/integrate-webapi` and `/create-webroles`. Use whenever a user wants AI/Copilot output that condenses Dataverse content on a Power Pages site — an AI summary, AI-generated overview or "key insights" across a record or list, a search-results summary, a case/incident summary, or recommendation-chip refinement — even when phrased as "AI-generated paragraph", "insights", or "overview". Do NOT use for: generative pages in model-driven apps (use the model-apps `genpage` skill), Copilot Studio agents/chatbots, summarizing documents or PDFs, Power BI dashboards, plain keyword search with no AI summary, or plain Dataverse CRUD (use `/integrate-webapi`).

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Capture a 2-3 line pitch from the user, draft a product overview (PRD.md) and a technical design (ARCHITECTURE.md) for a third-party `.ppmplugin` native control, then walk through every operation's iOS + Android implementation strategy with opinionated recommendations (library choice, hosting, key APIs, edge cases) and capture the agreed spec in ARCHITECTURE.md §3.<n>. The depth of ARCHITECTURE.md is what lets the scaffold skill generate complete working code instead of TODO placeholders. Iterates with the user until they approve both docs. Optionally seeds from a design doc / FRD URL. PRD.md + ARCHITECTURE.md are the source of truth for every downstream skill (generate, build, assemble). Run this BEFORE any code is generated.

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Generate food and beverage video prompts for Seedance 2.0 on Higgsfield. Use whenever the user wants food videos, recipe content, restaurant promos, beverage ads, cooking videos, food ASMR, menu showcases, food delivery ads, café content, or any food/drink video. Triggers on: food video, recipe, cooking, restaurant, beverage, food ad, food ASMR, menu, café, cocktail, food photography video, appetite appeal, food styling, mukbang, or any food/drink video request. Use even for "make my food look delicious" or "restaurant promo video.

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Evaluate an AI workflow against representative cases and its permitted actions. Use for model, retrieval or agent evaluation; tests do not grant release authority.

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Build a multi-quarter roadmap from a backlog of ideas, requests, and ongoing initiatives. Use this skill when planning the next quarter, sequencing dependent work, balancing build vs improve vs maintain, or making the case for what NOT to do. Triggers on roadmap, quarterly planning, what should we build next, sequencing, prioritization, OKR planning, capacity planning, what's on the roadmap, plan the year, what to ship next quarter. Also triggers when stakeholders are pulling in different directions and the team needs a defensible plan.

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EU AI Act (Regulation (EU) 2024/1689) compliance advisor — risk classification across all four tiers, all 9 prohibited practices (Art. 5, including the nudification/CSAM prohibition from Dec 2, 2026), all 8 Annex III high-risk use case areas, provider and deployer obligations (Arts. 9–17, 26), GPAI model obligations including the July 2025 Code of Practice (Arts. 51–55), conformity assessment and CE marking (Arts. 43–48), EU AI database registration, Art. 50 transparency (chatbots, synthetic media, AI-generated content), governance (AI Office, AI Board), penalties (Art. 99), confirmed phase-in timeline (Digital Omnibus, Reg. (EU) 2026/1744, in force July 27, 2026: Annex III deferred to Dec 2, 2027; Annex I to Aug 2, 2028), and cross-framework mapping to ISO 42001, NIST AI RMF, and GDPR. Use for any EU AI regulation, AI system classification, or AI compliance question. Current as of August 2026. GPAI enforcement powers active since August 2, 2026.

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Multi-AI second opinion via OpenAI Codex CLI. Three modes: Review (pass/fail gate), Challenge (adversarial edge-case finder), Consult (freeform with session continuity). Read-only with streaming output and thinking traces. Cross-model analysis when review has already run.

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Selects a fine-tuning technique (SFT, DPO, RLVR, or RLAIF) for the user's use case and validates it against the selected model's available recipes. Use when the user has decided to finetune and needs to choose a technique, or when the technique needs to be validated against a model. Requires a base model to already be selected (via model-selection skill).

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Selects a base model for the user's use case by querying SageMaker Hub. Use when the user asks which model to use, wants to select or change their base model, mentions a model name or family (e.g., "Llama", "Mistral", "Nova"), or wants to evaluate a base model — always activate even for known model names because the exact Hub model ID must be resolved. Queries available models, presents benchmarks and licenses, and confirms selection.

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HR business partnership across talent strategy, org development, and employee relations. Use when building workforce plans, designing performance reviews, resolving employee relations cases, or advising leadership on org change.

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Terraform provider acceptance test patterns using terraform-plugin-testing with the Plugin Framework. Covers test structure, TestCase/TestStep fields, ConfigStateChecks with custom statecheck.StateCheck implementations, plan checks, CompareValue for cross-step assertions, config helpers, import testing with ImportStateKind, sweepers, and scenario patterns (basic, update, disappears, validation, regression), and ephemeral resource testing with the echoprovider package. Use when writing, reviewing, or debugging provider acceptance tests, including questions about statecheck, plancheck, TestCheckFunc, CheckDestroy, ExpectError, import state verification, ephemeral resources, or how to structure test files.

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Use when the user needs to design evaluation datasets, create test cases, stratify samples, generate adversarial examples, extract eval dimensions from traces/specs, or build a labeled evaluation set. Also use when the user mentions test data design, eval coverage, difficulty stratification, synthetic data generation for eval, or "how to create good evaluation data." Outputs datasets in OpenJudge-compatible format.

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Pick the right LLM for LEGAL TRANSLATION — translating contracts, statutes, case law, and legal correspondence across languages, including Arabic/MENA. Vendor-neutral routing triangulated from mid-2026 evidence (WMT25 human eval, SwiLTra-Bench legal-MT, multilingual-reasoning proxies, ArabLegalEval). There is NO clean legal-translation leaderboard, so this vertical is directional and treats human legal-linguist review as mandatory. Asks up to 4 quick questions (language pair, cost, speed, privacy/certification), then recommends a primary model + fallback + what to avoid + what a human must verify. Use when someone asks "which model to translate this contract/statute", "best AI for legal translation", "translate this legal doc to/from Arabic", or is about to machine-translate legal text without a fixed model.

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No Inference / Source-Locked Verification. Forces Claude to answer ONLY from user-provided materials and/or online sources actually accessed — no inference, no assumptions, no gap-filling. Every factual, legal, numerical, or procedural claim must be anchored to a cited source. Use whenever Claude reviews documents, summarises evidence, checks accuracy, drafts submissions, creates timelines, extracts facts, checks citations, analyses rules, prepares legal arguments, compares documents, verifies claims, produces chronologies, works from uploaded materials, performs legal research, checks case status, or does anything where evidential fidelity matters. Also trigger on: 'source-locked', 'no inference', 'only from the materials', 'don't assume', 'stick to the evidence', 'verify this', 'check this is right', 'work from the documents'. Overrides Claude's default tendency to fill gaps. If evidential accuracy matters, use this skill.

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Verification-first methodology for the Special Court for Sierra Leone and its Residual Special Court. Citations are verified against rscsl.org and legal-tools.org. Covers Taylor, the AFRC/CDF/RUF cases, the child-soldier and forced-marriage holdings, the head-of-State immunity decision, and the fixed-term (no life) penalty regime. 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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Prepare a lawyer for an adversarial proceeding the way Neal Katyal's "Harvey" prepared him for the SCOTUS tariffs argument: profile the tribunal from their prior opinions and questions, predict the specific questions you will face, map narrow "escape routes" each judge can walk through without abandoning prior commitments, and spar adversarially until only the strongest answers survive. The model is the sparring partner. The human still wins the case. Use when: preparing for oral argument, appellate argument, motion hearing, evidentiary hearing, deposition (taking or defending), arbitration, mediation, or any proceeding where a known decision-maker will fire questions at you in real time. Also useful for stress-testing a brief before filing. Proactively suggest when: the user mentions an upcoming hearing/argument with named judges or arbitrators, drafts a brief and wants it pressure-tested, asks "what will Justice X / Judge Y ask me," or talks about preparing for a specific bench.

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