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Statically enforce a privacy/redaction boundary on an artifact tree before publication, the way an AST checker enforces a code contract. Builds a two-tier gate — a shape-based deny-list (regex over identifier shapes) plus a structure-aware tier that parses JSON/HTML/SVG/Markdown/code and asserts sensitive content cannot appear in meaningful positions — with a strict exit-code contract, label-only output that never echoes the patterns themselves, and false-positive narrowing instead of suppressions. Use when gating a public mirror, a disclosure draft, a wire-capture export, or any artifact that must pass a leak check before it ships, and when a plain line-grep is too coarse to trust.

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Design and implement multi-stage CI/CD pipelines using GitHub Actions with matrix builds, dependency caching, artifact management, and secret handling. Create workflows that span linting, testing, building, and deployment stages with parallel execution and conditional logic. Use when setting up automated testing and deployment for a new project, migrating from Jenkins or CircleCI to GitHub Actions, implementing matrix builds across platforms, adding build caching, or creating multi-stage pipelines with security scanning and quality gates.

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ORM patterns for NestJS: TypeORM, Prisma, Mongoose. Covers entities, repositories, transactions, migrations, common pitfalls (N+1, cascade deletes, transaction boundaries). Use this skill to: - Detect which ORM the project uses and apply matching patterns. - Define entities/schemas with the right decorators. - Inject repositories or Prisma client correctly. - Run transactions at the service boundary. - Write migrations that round-trip cleanly. Do NOT use this skill for: - Module/DI patterns (see nest-conventions). - Decorator usage broadly (see decorator-patterns). - Non-ORM raw SQL (rare; flag in BLOCKERS if needed).

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Plan synthetic routes and judge whether a proposed molecule can actually be made, using AiZynthFinder's Monte-Carlo tree search over template-derived reactions and a purchasable building-block stock. Use this skill to configure expansion and filter policies, choose a stock file, run route search over a candidate set, and read the returned trees — solved fraction, route depth, and which building blocks a route bottoms out in. Also trigger on AiZynthFinder, retrosynthetic tree search, synthetic accessibility, SAscore, RAscore, building-block stock, reaction template, or route scoring.

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Fires after fixing any non-trivial bug or regression. Asks: could the graph have caught this as a guarantee? Pairs with reflection-in-and-on-action — picks up after "earliest catchable signal" and asks the next question: was that signal expressible in graph? Triggers: (1) after any non-trivial bug fix is verified working, (2) after a regression report (something used to work, broke), (3) during step 6 (knowledge extraction) of the workflow, (4) when reflection-on-action surfaces a "would have been catchable" signal. Outcome is a triage decision (graph-reachable? rule expressible? rule sound?) and either a draft Linear issue + guarantee proposal, or a recorded "graph capability gap" note. Never auto-creates guarantees.

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Continuous self-reflection routine combining Schön (reflection-in-action / reflection-on-action) and Mezirow (content / process / premise) levels, anchored on KAMI values (val-002 глубина, val-007 честность перед собой, принцип 1 правда, принцип 2 нулевая толерантность к бреду). Triggers FIRE DURING THE TURN, not at end. Use when: (1) about to make a 2nd+ patch attempt at the same problem, (2) user pushes back with "стоп / нет / опять / так, ещё раз / не то / пиздёж", (3) noticing self drifting into "I think that..." without evidence, (4) about to report "готово", (5) copying a pattern from one place to another, (6) task took >2× expected time. Embeds scientific method (explicit hypotheses + falsifiability + prediction-first + alternatives) as substrate for premise-level reflection, not as ceremony.

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Build AI data extraction pipelines. TRIGGERS - Use when user needs help with ai-extraction-pipeline related tasks.

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"Apply action research through Plan-Act-Observe-Reflect cycles and Participatory Action Research (PAR) to generate knowledge while improving practice. Use this skill when the user needs to design practitioner research that integrates inquiry with intervention, facilitate participatory research with stakeholders, structure iterative improvement cycles, or when they ask 'how do I research my own practice', 'how do I involve participants as co-researchers', or 'how do I combine research with practical change'.".

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Identify and exploit Server-Side Request Forgery (SSRF) vulnerabilities in Next.js applications, specifically focusing on insecure server actions or API routes fetching user-controlled URLs on the server-side.

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Execute sophisticated Data Extraction and Privacy Leakage attacks explicitly against Large Language Models (LLMs) to natively force the neural network entirely into organically regurgitating exact, verbatim strings of Highly Confidential Personally Identifiable Information (PII), proprietary source code, or copyrighted material categorically memorized intrinsically during its foundational pre-training phase.

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Use when handling Django transactions and concurrency - atomic, select_for_update, on_commit, upserts, M2M ordering

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Use when the user wants to transact on any Volcengine commercial product — purchase/provision it, ask what it costs, or unsubscribe from it. Covers three actions: buy (purchase, subscribe, provision, open, place an order; Chinese "开通 / 购买 / 下单 / 买 / 售卖 / 订购"), price (how much does it cost, quote, billing rules, estimated spend; Chinese "多少钱 / 价格 / 报价 / 费用 / 怎么收费 / 如何计费 / 预估费用"), and unsubscribe (cancel a subscription, refund a prepaid instance; Chinese "退订 / 退款 / 取消订阅"). Trigger even when the user does not mention "sale" but expresses a clear purchase, pricing, or cancellation intent toward a Volcengine product. Only handles these three transaction actions; anything outside them is out of scope.

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Canonical patterns for caching in Yuzu CI workflows. Two snippets — one for ephemeral GHA-hosted runners (split actions/cache/restore + actions/cache/save, never `save-always: true`) and one for self-hosted runners (local filesystem cache under `runner.tool_cache`, no GHA cache round-trip). Use when adding a new vcpkg/ccache/dependency cache step to any workflow under `.github/workflows/`, or when reviewing a PR that touches `actions/cache@`.

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Guides the usage of Gemini Interactions API on Gemini Enterprise Agent Platform. Use when the user wants to use the stateful, server-managed Interactions API for multi-turn conversations, background execution, streaming, structured output, and function calling on the Agent Platform.

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Use this skill when building custom channel integrations with the Agentforce Agent API or BYOC (Bring Your Own Channel) for CCaaS — covering session lifecycle management, webhook handling, externalSessionKey design, sequenceId sequencing, BYOC Interaction API integration, and conversation state management. NOT for standing up a standard channel (Embedded Service, Slack, Experience Cloud, Messaging) — use agentforce/agent-channel-deployment. NOT for writing the Apex actions the agent invokes — use agentforce/custom-agent-actions-apex.

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Design Agentforce conversations that span multiple turns without losing context: session variable scoping, conversation memory, clarifying-question patterns, topic-to-topic (now subagent) handoff, and the right abstractions for accumulating state across turns. NOT for deciding the topic boundaries themselves or out-of-scope behavior — use agentforce/agent-topic-design. NOT for single-turn agent actions and their input/output contracts — use agentforce/agent-actions.

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Apex test patterns for @InvocableMethod agent actions: per-reason-code branch coverage, bulk safety, callout mocking, deterministic assertions. NOT for testing whether the agent routes to the right topic or answers well — use agentforce/agent-testing-and-evaluation. NOT for designing the error envelope the tests assert on — use agentforce/agent-action-error-handling.

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Authoring and managing Agentforce agent definitions using the declarative Agent Script DSL (.agent files) and associated metadata types, including the Agent Script language for the new Agentforce Builder (hybrid-reasoning -> logic vs | prompt instructions, @actions/@subagent/@variables references, subagents). Use when creating agents in source control, writing or debugging Agent Script, debugging agent metadata, or understanding the metadata lifecycle of GenAiPlugin/GenAiPlanner/BotVersion types. Triggers: 'how do I deploy an Agentforce agent using source control', 'convert an agent topic to a subagent', 'what metadata types make up an Agentforce agent', 'agent test run command failing in CI pipeline', 'GenAiPlugin vs GenAiPlanner metadata relationship', 'Agent Script logic vs prompt instructions'. NOT for Apex-based agent actions — use agentforce/custom-agent-actions-apex. NOT for clicking the agent together in the Builder UI — use agentforce/agentforce-agent-creation.

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Use when overriding the default UI of an Agentforce agent action's Apex input or output with your own Lightning web components via a LightningTypeBundle (schema.json + editor.json/renderer.json, lightning__AgentforceInput / lightning__AgentforceOutput targets, the @apexClassType binding). NOT for standard agent actions with primitive inputs/outputs (only Apex-class input/output can be overridden), NOT for Flow screen custom property editors (use flow/flow-custom-property-editors), and NOT for general LWC-in-Lightning-page work (use lwc/* skills).

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Use this skill when designing, auditing, or troubleshooting behavioral boundaries for Agentforce agents — including topic (now subagent) Scope fields, agent-level system instructions, topic/action filters, the Escalation topic, restricted topics, and Instruction Adherence monitoring. Trigger keywords: agent guardrails, agent out of scope, restrict agent behavior, topic scope, subagent scope, agent fallback, Escalation topic, abuse prevention, action filters. NOT for Trust Layer content filtering (Einstein Trust Layer is a separate product concern), NOT for general topic routing design (use agentforce/agent-topic-design), NOT for prompt template construction (use agentforce/prompt-builder-templates).

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Advanced Lightning App Builder usage: component visibility filters, custom page templates, Dynamic Forms, Dynamic Actions, page performance optimization, LWC targetConfig constraints on record pages. Use when building complex record pages or custom app templates. NOT for Dynamic Forms basics — use admin/dynamic-forms-and-actions. NOT for exposing an LWC via js-meta.xml targets — use lwc/lwc-app-builder-config.

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Use this skill when deploying a trained Einstein Discovery model to production records declaratively — activating a prediction definition, mapping output fields to page layouts, adding the Einstein Discovery Action to a Flow, running bulk predict jobs, and monitoring model health via Model Manager UI. Trigger keywords: prediction definition activation, bulk predict job, Einstein Discovery Flow action, Model Manager, prediction field mapping, model refresh activation, scoring job, Einstein Discovery recommendations on record. NOT for authoring the story in CRM Analytics Studio — use admin/einstein-discovery-setup. NOT for programmatic scoring through the API — use agentforce/einstein-discovery-development.

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Use this skill when configuring FSC financial planning objects, designing periodic review cycles, modeling risk assessment workflows, or tracking goal progress in Financial Services Cloud. Trigger keywords: FinancialGoal, FinancialPlan, goal tracking, risk tolerance, review cycle, financial planning workflow, Discovery Framework, Revenue Insights. NOT for wealth management process discovery — use admin/wealth-management-requirements. NOT for Action Plan template mechanics — use admin/fsc-action-plans.

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Use this skill when designing the FSC client onboarding process — mapping document collection touchpoints, approval steps, compliance checkpoint sequencing, and welcome journey handoffs. Trigger keywords: client onboarding design, onboarding workflow requirements, document collection flow, compliance checkpoint, welcome journey, intake process design. NOT for configuring the Action Plan template itself — use admin/fsc-action-plans. NOT for OmniScript screen and branching requirements — use admin/omniscript-flow-design-requirements.

日本語の概要は準備中です。原文の説明を表示しています。