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Choose tools and workflows for 3D modeling, dimensioned CAD parts, scan processing, rendering, and fabrication. Capability tables and recipes help connect tasks from photographs or initial designs to printable parts, CNC toolpaths, or game assets.
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Search for and install skills that fill a missing capability, or open the Skills settings for management. When suitable options are unavailable, hand off to the built-in skill-creator and continue the original task.
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Build and review Kubernetes Operators, controllers that keep custom resources in their desired state. Included tools check resource definitions and Go reconciliation code, then assess operational capabilities and suggest improvements.
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Route Convex development and operations requests to the relevant specialist skills and current procedures, covering app setup, backend features, code reviews, authorization checks, production monitoring, data migrations, and cost analysis.
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Convert articles, tutorials, or prompt collections into reusable agent skills, with one independent capability per skill. Package portable instructions, example prompts, working demos, preview images, and validation so the methods can transfer to other projects.
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Guide site integration work from capability discovery and authentication choices through implementation and validation. Cover account features, administrative resources, check-ins, or native editor usability, while documenting evidence, supported behavior, and paths that remain unverified.
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The art-route layer of the Forge skills. route_media.py is the one command that generates an image or an image-to-video clip - through the paid API of any provider whose key is configured (OpenAI, Google Gemini, xAI, BytePlus ModelArk, fal.ai; the configured key is the owner's consent), else through the user's own signed-in Codex or Grok CLI - and prints one JSON line with the route, artifact, sha256 and cost estimate; with no route it answers no-route (codeart2d is then the last resort). Also the capability check (forge_doctor), API key configuration, the spend ledger, resume and Codex image adoption. Use when a Forge skill sends a generation here, for the capability check, or when the user asks about keys, routes or spend. Not for planning, processing or QA of sprites, video frames or maps (generate2dsprite, video2dsprite, generate2dmap) or for code-drawn art (codeart2d).
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Use when Jetson codec, profile, chroma, bit-depth, dimension, engine-count, or operational support must be reconciled from live APIs, authenticated NVIDIA samples, and NVIDIA documentation; also applies the content-DRM scope.
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Use this skill when the user wants to invoke the read-only doca_caps CLI to ask what DOCA sees on this host — listing DOCA devices and PCIe addresses, listing representor devices, asking which DOCA libraries are available on the current OS, checking per-device per-library capabilities, scoping output to a specific PCIe address, or capturing a side-effect-free capability snapshot for debug or install smoke-test. Trigger even when the user does not explicitly mention "doca_caps" or "capabilities print tool" — typical implicit phrasings include "what does DOCA actually see on this box", "is my BlueField PF visible to DOCA", "is Flow available on my RHEL host", "enumerate VF representors for pf0", "doca_caps: command not found", or "empty output for RDMA, is the tool broken". Refuse and route elsewhere for DOCA installation (doca-setup owns it; never walk the steps), library-internal capability matrices (Flow pipe creation, RDMA verbs features), streaming telemetry / DTS, or modifying the shipped binary.
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[omh] Parallel tool-call capability in doubt: report the version and whether MCP parallel tool calls are enabled, then apply the diff for parallel tool calls only after approval; an update only on request. Use when the user says: parallel-tools, parallel tools, hermes parallel tools setup, update hermes for parallel tools, check parallel tool support, enable parallel tool calls, verify parallel tools capability, check hermes version for parallel tools.
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[omh] Explaining OMH itself: current-source-first documentation for OMH itself: product identity, public capability catalog, model routing, local state, and long-term memory. Use when the user says: product-docs, OMH documentation, oh-my-hermes documentation, what is OMH, what is oh-my-hermes, how does OMH work, OMH capability catalog, OMH skill catalog.
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Builds capability — skills gaps, career frameworks, training that transfers to the job, and internal mobility. Use this to design a career ladder, close a capability gap, decide whether to build or hire a skill, structure onboarding into a role, or work out why training keeps failing to change anything.
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Builds the capability to notice an attack in progress — deciding what to log and retain, centralizing it somewhere tamper-resistant, writing detections that fire on attacker behavior rather than on individual events, tuning out the noise that trains people to ignore alerts, and defining what happens when something fires. Use this to design or assess monitoring coverage, work out why an incident went unnoticed, cut alert volume without losing signal, or decide what a detection capability should cost.
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Generate MCP capability declarations from tool and resource inventory with proper versioning and feature flags.
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Eval-Driven Development (EDD) for AI workflows. pass@k metrics, capability evals, regression evals. Triggers: eval, edd, pass@k, capability, regression, benchmark.
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Discovers connected MATLAB-supported hardware devices, searches by capability, and checks required support packages and add-ons. Use when the user asks what hardware is connected, finds a device that supports a capability (e.g., CAN, analog input), or checks if required support packages or add-ons are installed. Does NOT connect to, configure, or acquire data from devices — defers to device-specific skills for usage workflows.
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First-tier tech company P7 capability advisor for evaluating, coaching, and giving career advice against a P7 technical/product/expert profile. Use when the user asks for P7-level assessment, promotion readiness, capability gaps, resume/project review, interview preparation, or concrete growth advice based on first-tier tech company P7 expectations.
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First-tier tech company P9 capability advisor for evaluating, coaching, and giving career advice against a P9 senior expert, director, or business/organization-level leader profile. Use when the user asks for P9-level assessment, promotion readiness, executive capability gaps, strategic project review, resume positioning, interview preparation, or growth advice based on first-tier tech company P9 expectations.
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First-tier tech company P8 capability advisor for evaluating, coaching, and giving career advice against a P8 senior expert, architect, or domain-owner profile. Use when the user asks for P8-level assessment, promotion readiness, capability gaps, project or resume review, interview preparation, or growth advice based on first-tier tech company P8 expectations.
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Provides multi-school trading Q&A, chart/OHLCV analysis, annotation, and fresh-market workflows covering ICT/SMC, ChanLun, Wyckoff, Price Action, Order Flow, VSA, and Elliott Wave. Use for trading concepts; capability-discovery questions about available analysis lenses, Schools, models, modes, or data sources; attached charts; pasted OHLCV; chart annotation; or asset-plus-timeframe requests across crypto, stocks, or forex. Defaults unselected market analysis to strict ICT/SMC, honors explicit School/source selectors, and fails closed when no native analyzer exists. Phase 1 comparison is Q&A-only; fetch fresh Mobius Quant API data only after the capability gate.
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Build or consume Model Context Protocol (MCP) servers and clients in .NET using the official MCP C# SDK, including stdio, Streamable HTTP, tools, prompts, resources, and capability negotiation. USE FOR: .NET MCP servers or clients; stdio versus HTTP transport choices; tools, resources, prompts, completions, and capability negotiation. DO NOT USE FOR: unrelated stacks; generic tasks that do not need this specific guidance. INVOKES: inspect the repository context, edit targeted files, and run relevant build, test, lint, or validation commands when changes are made.
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Routes substantive ML, AI, data, scientific-computing, and software-engineering requests to the smallest useful set of managed repository skills. Invoke proactively when a request names or implies a package, framework, model family, dataset, modality, workflow, backend, deployment target, evaluation method, or implementation approach that may benefit from repository guidance, even if no repository is named. Narrow progressively from area to family to repository root: inspect only the one or two most likely area pages; compare candidates by capability, task surface, model/data format, training versus inference versus evaluation intent, runtime constraints, and root-skill description; then open only the selected root and relevant sub-skills, references, or scripts. Select multiple repositories only when each adds a distinct capability. Do not load the whole collection, treat dependencies or incidental integrations as capabilities, choose by name alone, or force a match when no exact taxonomy family applies.
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Use when designing organizational structure (team topologies, Conway's Law alignment), mapping stakeholders by power-interest for change initiatives, defining team interface contracts (APIs, SLAs, decision rights, handoffs), assessing capability maturity (DORA, CMMC, agile maturity models), planning org restructures (functional to product teams, platform teams, shared services), or when user mentions "org design", "team structure", "stakeholder map", "team interfaces", "capability maturity", "Conway's Law", or "RACI".
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Teach any topic deeply from first principles and build evidence-based paths toward exceptional capability. Use when a user asks to understand, explain, learn, or deep-dive into a topic; asks why or how something works, why it matters, how alternatives compare, or what different perspectives reveal; requests current paradigms, a complete roadmap or curriculum, deliberate practice and feedback, or a top-1%-level mastery plan. Answer explanation questions completely before offering a curriculum; route explicit mastery goals to an adaptive practice and proof-of-capability system.
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