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Review and adapt MetaX attention backends, MLA, sparse indexers, cache layouts, and their kernel wrappers against a target vLLM revision and the actually installed MetaX component APIs. Verify dispatch, supported configurations, and GPU numerical behavior. Use for attention adaptations outside vllm_metax/patch/; do not apply monkey-patch headers or patch audit requirements.
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Internal downstream skill for ctf-sandbox-orchestrator. CTF-sandbox workflow for cloud metadata services, instance identity, workload identity, link-local credential paths, role assumption, and metadata-to-privilege trust edges. Use when the user asks to inspect metadata-service access, instance credentials, pod or workload identity, link-local token paths, SSRF-to-metadata escalation, or explain how metadata-derived credentials turn into accepted cloud or control-plane privilege. Use only after `$ctf-sandbox-orchestrator` has already established sandbox assumptions and routed here.
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Fix silent metadata issues in RFDB node storage. Covers two traps: (1) metadata flattening — nested metadata fields become top-level after serialization, so node.metadata.field is undefined but node.field works. (2) reserved keys — fields named "type", "id", "name", "file", "exported" are silently stripped from metadata by _parseNode() to prevent overwriting top-level node fields.
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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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Authoring and managing Agentforce agent definitions using the declarative Agent Script DSL (.agent files) and associated metadata types. Use when creating agents in source control, debugging agent metadata, or understanding the metadata lifecycle of GenAiPlugin/GenAiPlanner/BotVersion types. Triggers: 'how do I deploy an Agentforce agent using source control', 'what metadata types make up an Agentforce agent', 'agent test run command failing in CI pipeline', 'GenAiPlugin vs GenAiPlanner metadata relationship'. NOT for Apex-based agent actions (use custom-agent-actions-apex). NOT for UI-based agent creation (use agentforce-agent-creation).
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Metabolomics pathway analysis — metabolite identification (HMDB, KEGG, ChEBI), pathway mapping (Reactome, KEGG, MetaCyc), disease associations, enzyme/gene linkage. Use for metabolite-to-pathway-to-disease connections, BridgeDb-based ID conversion, and integrating metabolomics with gene-level pathway analyses.
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Runs the MS-DIAL preprocessing workflow (peak picking, MS2Dec spectral deconvolution, alignment, gap-filling) and imports the alignment-result table into R or Python with honest filtering. Use when preprocessing LC-MS DDA/DIA (SWATH) raw data with MS-DIAL, deciding MS-DIAL vs XCMS, configuring the MsdialConsoleApp console run, or parsing an MS-DIAL export into a clean feature matrix. For programmatic R peak detection and the feature-table-as-artifact framing see metabolomics/xcms-preprocessing; for lipid annotation mode see metabolomics/lipidomics; for MSI-level confidence honesty see metabolomics/metabolite-annotation; for drift correction and QC see metabolomics/normalization-qc.
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Designs and validates quantitative targeted metabolomics assays (MRM/SRM on triple-quadrupole, PRM on high-resolution instruments) to report absolute concentrations. Covers the internal-standard strategy (external cal -> global IS -> standard addition -> stable-isotope-labeled IS), weighted calibration judged by back-calculated %RE not R-squared, ion-ratio quantifier/qualifier confirmation, matrix-effect/recovery characterization, and ICH M10 method validation. Use when quantifying a closed panel of known metabolites with units, building or validating an LC-MS/MS assay, choosing an IS or calibration weighting, or judging whether a reported concentration is trustworthy. For untargeted feature detection see metabolomics/xcms-preprocessing; for group statistics see metabolomics/statistical-analysis; for flux/MID/tracing see metabolomics/isotope-tracing.
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Genera tickets profesionales de soporte para Meta Business Suite / WhatsApp Business API optimizados para recibir prioridad URGENTE 24hr resolution. Úsala SIEMPRE que el usuario mencione crear un ticket a Meta, escalar un caso WABA, apelar un ban o restricción, reportar un false positive, abrir caso de soporte WhatsApp Business, problema de onboarding, rechazo de template, errores de Cloud API, OTP delivery, verification stuck, BM restricted, display name rejection, o cualquier issue de una WhatsApp Business Account. También activa cuando el usuario dice frases como "ayúdame a redactar un caso para Meta", "necesito reportar esto a soporte", "hay que escalar esto a WhatsApp", "ticket para Meta", o describe un problema de una cuenta de cliente de Vambe sin pedir ticket explícitamente pero claramente necesita uno. También activa ante preguntas del tipo "¿cómo apelar esto?" o "¿qué hago si Meta dice X?" relacionadas con WABA, BM o verificación.
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Next.js route metadata, per-route favicons, OpenGraph, and Twitter cards. Use when adding a route or layout, adding a favicon or social share image, auditing missing metadata, naming tab titles, or touching createRouteMetadata, createDynamicRouteMetadata, generateFaviconMetadata, or titlePrefix.
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Create and audit meta descriptions, the short page summaries used in search results. Find missing, duplicate, or unsuitable descriptions and write distinct summaries that accurately explain each page’s content and value.
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Plan and review paid advertising across Google Ads, Meta, LinkedIn, and other platforms. Organize audiences, budgets, and bidding, then assess results using customer acquisition costs and sales data while separating evidence, hypotheses, and missing information.
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Use COBRApy to model metabolic networks and calculate possible reaction flows under defined constraints. Compare gene knockouts, nutrient conditions, and production limits, while checking model validity and keeping computational predictions separate from experimental findings.
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Analyze campaign data across advertising platforms, check whether results are comparable, and assess costs and returns. Get budget test proposals with stated evidence, uncertainty, spending limits, and rollback criteria.
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Trace server-side request forgery, where a server fetches a supplied URL, through internal services and metadata endpoints in a CTF sandbox. Document credential scope and distinguish successful token extraction from access actually accepted by another service.
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Research competitors’ paid ads on Meta and Google, then examine their messaging, formats, and landing pages. Produce a strategy report showing paths from ads to signups, gaps in competitors’ approaches, and ideas for campaigns to test.
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Build a Table v9 plugin when built-in settings and typed metadata are insufficient. Guides custom state, options, and methods, with initialization hooks and runtime checks to ensure declared APIs actually exist and reset correctly.
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Create paid ad headlines and body copy tailored to each platform's character limits. Use existing performance data to develop variations, explore new messaging angles, and check copy for length, quality, and potential rejection risks.
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Analyze ARIS usage logs to propose evidence-based changes to skill instructions, reviewer prompts, and workflow defaults. Receive a report and focused patch proposals, with selected patches staged for a separate application process.
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Build Next.js 14+ applications with App Router, server-rendered components, and form actions. Produces routes, page layouts, data fetching, loading and error states, and SEO metadata, while supporting performance optimization and deployment preparation.
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Coordinate paid advertising work across twelve platforms, from account audits and budget planning to creative briefs, experiments, monitoring, and reports. Ground recommendations in evidence and execute account changes only when explicit approval and required safeguards are in place.
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Audit advertising accounts across twelve platforms using account data and documented sources. Identify measurement, budget, creative, and policy issues, then produce prioritized actions with evidence coverage, confidence, and missing information clearly recorded.
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Audit how advertising platforms, GA4, and app measurement tools assign credit for conversions. Compare event definitions, reporting windows, and duplicate handling to explain discrepancies and produce an evidence-based measurement improvement plan.
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Submit compact MetaboLights requests for study discovery and study-level metabolomics metadata. Use when a user wants concise MetaboLights summaries
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