179건 · 관련도순
Configure compression for command output, prose, and chat history before sending them to AI providers. Choose suitable engines, adjust language rules, and preview compressed text and reported savings before enabling a mode.
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Identify and unpack malware compressed with UPX to prepare executable files for static analysis, which examines code without running it. The workflow covers altered header repair, debugger-based recovery, and validation before analysis in Ghidra or IDA.
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Guides an application’s first deployment to GKE, Google’s managed Kubernetes service. Covers application assessment, container creation, image storage, deployment configuration, security settings, health checks, and verification that the application is running.
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Add team-specific evaluation criteria to plugin-eval by designing a metric pack, a set of custom checks and measurements. Create its manifest and JSON-producing script, then run it through the evaluator using a consistent output structure.
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Audit a website or digital experience against its supplied source references for originality and plagiarism risk. Use when Codex must compare current or historical site output with reference pages, capture packs, screenshots, copy, brands, numbers, images, assets, videos, layouts, motion, or code; raise evidence-backed red flags; distinguish common visual grammar from distinctive copying; and propose concrete fixes without making unsupported legal claims.
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Update peon-ping configuration — volume, pack rotation, categories, active pack, and other settings. Use when user wants to change peon-ping settings like volume, enable round-robin, add packs to rotation, toggle sound categories, or adjust any config.
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Plan and build 2D game maps and scenes - top-down and side-scrolling levels, tilemaps, prop packs, parallax backgrounds and HD-2D battle or story plates - with collision, navigation and reachability checks, environment motion, a playable HTML preview and export to Tiled, Godot 4 or LDtk. Map art (terrain, tiles, props, plates, parallax layers) is image generation by default, through generate2dmedia route_media.py (the API when a key is configured, else the local Codex or Grok CLI); map data (layout, collision, exits, spawns) is written as data. Use for any map, level, room, scene, background, terrain or prop-kit request. Not for characters, creatures, items or FX (generate2dsprite), character animation (video2dsprite), code-drawn tiles or maps (codeart2d, only on request) or calling an image or video API by itself (generate2dmedia).
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Exports sanitized metadata, parameters, reproducibility details, quality metrics, and optional review artifacts from Medical AI inference runs or evidence packs to MLflow. Use after inference, including NV-Generate runs; not for live training tracking, model registration, or clinical use.
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Use this skill when the user is deploying or operating the DOCA Argus Service — the packaged BlueField-side runtime-security container that watches the BlueField and attached host for suspicious activity, integrity violations, and operational anomalies, and forwards findings to a SIEM (Splunk / ELK / Sentinel / syslog). Covers the four-axis config (detection policy, forwarding, sampling, host coverage), running the NGC container on BlueField Arm, and wiring the forwarder. Trigger even without "DOCA Argus" by name — typical implicit phrasings: "container green but no findings arrive", "false-positive flood in Splunk", or "runtime security on a fleet of BlueField-3s". Refuse and route elsewhere for installing DOCA, SIEM-side ingest stanzas, pre-baked detection-rule packs, and metrics observability (DOCA Telemetry). Argus is NVIDIA's currently- promoted runtime-security framework, superseding the older App Shield library; name it first for new runtime-security work.
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Geolocate or chronolocate a photo with tool-verified reasoning (where was this taken / when was it taken / photo geolocation / geo-guessing). Given one or more photos, intake.py does metadata, OCR and reverse image search (Baidu/Yandex) in one command; clues and candidates go on a candidate board (board.py) that ranks them and gives the next step; clues.py looks up calling codes, driving side, plates and area codes from region packs; for satellite and street view the machine ranks first and you look only at the top few (CLIP in sat_scan.py, DINOv2+SIFT in match.py); plus sun and shadow math, OSM Overpass and DEM skylines. Every conclusion is checked against real data; output is coordinates + error radius, evidence images and tiered confidence. Use when the user shares a photo and asks where was this taken / geolocate this / when was this taken / 这是哪 / 在哪拍的 / 帮我定位这张照片 / 网络迷踪 / 图寻 / 几点拍的.
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Use when the user asks to "build a message house", "write a PR-FAQ for our launch", or "define the launch narrative and value pillars"; derives from the positioning canvas a message house — tagline, one-liner, three value pillars, per-persona proof points (each labeled Measured / User-provided / [needs source]) — plus a working-backwards PR-FAQ narrative spine (launch-day tense, empty-chair test, five external + five internal FAQs) and per-channel message angle packs (angles, not finished copy). Not for the positioning canvas itself — use positioning-mapper; not for finished blog posts or pages — use content-writer; not for ad or email units — use each discipline creative builder; not for claim adjudication — use offer-claims-registry. 消息屋/PR-FAQ/价值支柱/发布叙事
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Build, run, debug and ship 3D city games in Godot 4 — procedurally generated cities (block grids, districts, weighted building typologies, MultiMesh batching, facade shaders, terrain, day/night, landmarks), first-person controllers, headless verification, Blender-generated .glb assets, rigged character and animation packs, real OpenStreetMap-derived cities, WebAssembly export, and cloud GPU streaming on GCP. Use this skill whenever the work involves Godot or a .gd/.tscn/.gdshader/project.godot file; whenever someone wants to start, set up, clone onto a new machine, or stand up a 3D game or city generator; whenever they mention procedural city, city generator, block grid, building typology, MultiMesh, facade shader, terrain heightmap, navmesh, Godot export templates, export presets, headless Godot, .glb pipeline, Blender asset generation, character rigs or borrowed animations; and whenever they want to deploy or share a game — web export, SharedArrayBuffer/COOP/COEP, Selkies, pixel streaming, GPU VM, or "let people play this without installing anything." Reach for it even on vague asks like "get this running", "why is my city slow", "my model faces backwards", "make it work on a cloud machine", or "set this up somewhere else too" when a Godot 3D project is in play.
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Use when a task involves game textures or materials through the Scenario MCP: seamless or tileable textures, themed texture packs (brick, wood, stone, floors, hand-painted), PBR materials (albedo, metallic, roughness, normal) on 3D assets, retexturing a mesh, material iteration from reference images, texture upscaling that must preserve tiling, or sizing textures for game engines. Keywords: seamless texture, tileable, PBR, material, retexture, texture upscale, surface.
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Build professional data packs for A-share investment banking deals — M&A due diligence, IC materials, company profiles. Adapted from the original datapack-builder skill for Chinese data sources (AkShare, 巨潮, exchange filings) and CAS accounting. Triggers on "A股数据包", "投行数据包", "datapack China", "due diligence pack A-share", or "IC data pack [company]".
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Build a product-specific Amazon FBA prep, labeling, packing, and shipment-readiness plan. Use when a seller asks how to prepare units for FBA, choose barcode and labeling steps, plan poly-bagging, bubble wrap, sets, case packs, cartons, dangerous-goods review, supplier or prep-center instructions, or prevent receiving delays. Do not use as a substitute for current Seller Central requirements.
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Set up and run an Aeon agent instance - get started from scratch, pick which skills to turn on or install more from packs, reschedule or change what runs, edit what an existing skill does, fix a skill that isn't firing, set the STRATEGY.md north star and soul/ voice, turn a coding-agent chat into a scheduled Aeon skill, and mine past coding-agent conversations for recurring work worth automating as a skill. Use when the user mentions Aeon, aeon.yml, an Aeon skill / instance / routine / pack, asks to schedule, enable, edit, or debug an agent that runs on a cron, or asks what of their repeated/manual work Aeon could take over.
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Install a community skill pack into this fork from a GitHub repo and ship it as an auto-merged PR
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Package one of this agent's own skills as a standalone community pack and submit it to the aeon registry as a PR
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Generate Nano Banana Pro (Gemini 3 Pro Image) prompts for e-commerce product photography. Given a user-uploaded product photo, this skill identifies the main subject, asks the user to choose a scene type, then outputs a professional, ready-to-paste English prompt optimized for Nano Banana Pro's image-to-image capabilities. Use this skill whenever the user uploads a product image and wants to generate an e-commerce photo, product shot, commercial image, or marketing visual using Nano Banana Pro / Gemini. Trigger phrases include: "ecom shot", "电商图", "产品图", "商品图", "product photo", "e-commerce image", "make a product shot", "generate a Nano Banana prompt for this product", "帮我做一张电商主图", "白底图", "商拍", "产品摄影", "hero shot", "packshot", or any request involving turning a casual product photo into a professional commercial image. Also trigger when the user mentions Nano Banana / Gemini image generation with a product photo.
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Use when module planning and source coverage are done and the run needs writer-ready per-module packs.
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Fill `outline/tables_index.md` from `outline/table_schema.md` + evidence packs (NO PROSE in cells; citation-backed rows).
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Write `output/DRAFT.md` (or `output/SNAPSHOT.md`) from an approved outline and evidence packs, using only verified citation keys from `citations/ref.bib`.
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Use when approved tutorial context packs exist and the run needs the final article-first tutorial deliverable.
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Extract per-subsection “anchor facts” (NO PROSE) from evidence packs so the writer is forced to include concrete numbers/benchmarks/limitations instead of generic summaries.
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