「static」の検索結果

Generate AI video ads and image ads through the Novoads REST API (api.novoads.ai). Use when the user wants a UGC video, a product video, a talking-head ad, an AI actor holding a product, a TikTok or Reels or Shorts ad, a static image ad, or asks to "make me an ad", "generate a video", or names a model (Seedance, Seedance 2.5, Seedance Mini, Omni Flash, Veo 3.1, Sora 2, GPT Image 2, Nano Banana Pro, Reve). Handles upload, dialogue approval, cost confirmation, generation, polling, QA, and download. A product photo lands here when it SEEDS a new scene; when the picture itself should move, unchanged, that is image-to-motion. Not for editing an existing video file and not for publishing to an ad platform.

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Builds a stylized 3D animated ad on the Novoads REST API as a STORYBOARD: four to six beats, each rendered from its own key frame, narration laid into the gaps, a music bed, captions burned on, assembled locally with ffmpeg. Carries the genre's beat formulas (anthropomorphized problem character, protagonist reveal, mascot mechanism scene, composited end card). Use for ANY Pixar-style, Disney-style, 3D animated or animated-film-look ad at ANY length: "Pixar style ad", "3D animated ad", "animated movie look", "cute 3D character ad", "a quick animated ad", "15 second animated ad", "30 second animated ad", "storyboard ad", "several scenes", "animated ad with a voice-over", "little mascots", or a product URL or photo for an emotional animated spot. No one-call tier, so ffmpeg is required. Not for stop-motion clay (use claymation-ad), talking-head UGC (novoads-api), video cloning, or static image ads.

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This skill provides systematic bug detection and discovery capabilities for VS Code extensions. Use when searching for hidden bugs, analyzing code for potential issues, investigating suspicious behavior, performing code audits, or proactively finding bugs before they manifest. Covers static analysis patterns, dynamic analysis techniques, code smell detection, and systematic codebase investigation.

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Uses Ghidra to disassemble and decompile a binary, navigate to key routines via imports and strings, annotate decompiled code, and run headless scripts to automate extraction of C2, crypto, and config. Activates for requests to reverse engineer with Ghidra, decompile a binary, or script Ghidra headless analysis.

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Uses capa to identify malware capabilities from a binary: running rule-based detection over disassembly, mapping matched capabilities to MITRE ATT&CK and MBC, and interpreting results to focus deeper analysis. Activates for requests to run capa, generate a capability report, or map a sample's behaviors to ATT&CK automatically.

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Detects packing and encryption by measuring Shannon entropy across a binary's sections and regions: flagging high-entropy executable sections, entropy spikes, and size/raw-vs-virtual anomalies that indicate compression or encryption. Activates for requests to measure entropy, detect packing, or assess whether a sample is compressed/encrypted.

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Extracts ASCII and Unicode strings from a binary and classifies them into investigative categories: URLs, IPs, file paths, registry keys, mutexes, commands, and API names, prioritizing the analyst's attention. Activates for requests to extract strings, classify strings output, or pull human-readable artifacts from a sample.

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Establishes behavioral baselines from historical telemetry (process, network, or logon events) so hunts can flag rare and first-seen activity instead of relying on static signatures. Activates for requests to build a telemetry baseline, find rare or first-seen activity, or compute frequency baselines for anomaly hunting.

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Reverse engineers binaries with Binary Ninja using its analysis stack and Python API to enumerate functions, navigate IL levels (LLIL/MLIL/HLIL), and automate annotation and extraction. Activates for requests to reverse a binary with Binary Ninja, script the Binary Ninja API, or work with its intermediate languages.

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Reverse engineers binaries using radare2/rizin interactively, covering analysis initialization, navigation, disassembly and graph views, patching, and the visual mode workflow. Activates for requests to reverse a binary with radare2 or rizin, learn r2 commands, or navigate and disassemble a sample in r2.

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Analyzes cryptojacking/coinminer malware by extracting mining pool endpoints (stratum), wallet addresses, algorithm and miner identifiers (XMRig and forks), and persistence or resource-control settings from static strings and config. Activates for requests to analyze a cryptominer, extract mining pool and wallet IOCs, or identify coinminer configuration.

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Analyzes a PE file's import and export tables to infer capability: mapping imported APIs to behaviors (networking, crypto, injection, persistence), spotting dynamic-resolution stubs, and reading exports of malicious DLLs. Activates for requests to analyze PE imports, inspect the IAT/exports, or infer capability from API usage.

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Decrypts statically embedded malware configuration blobs by trying common schemes (single-byte and multi-byte XOR, RC4, base64 layers) and scoring decoded output for config-like content. Activates for requests to decrypt an embedded config, recover hardcoded settings from a blob, or brute-force a configuration encryption scheme.

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Deobfuscates malicious JavaScript from droppers, web pages, and HTA/scriptlets: unrolling string-array and char-code encodings, resolving eval/Function chains, and statically recovering payloads and URLs without executing untrusted code. Activates for requests to deobfuscate JavaScript, decode obfuscated JS, or analyze a malicious script dropper.

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Detects sandbox and analysis evasion techniques in a sample by scanning static strings, imports, and API traces for VM artifact checks, timing/sleep stalls, anti-debug calls, and environment fingerprinting. Activates for requests to detect sandbox evasion, find anti-VM or anti-debug checks, or explain why a sample did not detonate.

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Analyzes bootkit and rootkit samples by identifying boot-process tampering (MBR/VBR/ UEFI), kernel-mode components, and stealth hooking techniques from static indicators. Activates for requests to analyze a bootkit or rootkit, examine MBR/UEFI tampering, or identify kernel-mode stealth components.

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Analyzes infostealer samples by mapping the browser, credential store, wallet, and application paths they target, and the exfiltration channel used, from static strings and behavior. Activates for requests to analyze an infostealer, identify targeted credential stores, or map stealer collection and exfiltration behavior.

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Analyzes remote access trojan command-and-control by mapping the RAT command set, identifying the C2 transport and beacon parameters, and cataloging operator capabilities from static strings and config. Activates for requests to analyze RAT C2, map a trojan command handler, or identify remote-access capabilities and C2 transport.

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Analyzes malicious PDF documents: parsing the object structure for JavaScript, OpenAction/launch triggers, embedded files, and URIs, then extracting and decoding suspicious streams without opening the document in a reader. Activates for requests to analyze a malicious PDF, inspect PDF JavaScript, or extract embedded payloads from a PDF.

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Analyzes weaponized Windows shortcut (.lnk) files: parsing the shell link structure for the target command, arguments, icon, and working directory, and recovering hidden PowerShell/cmd payloads and embedded content used in phishing. Activates for requests to analyze a malicious LNK, parse a shortcut file, or extract a command from a .lnk.

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Improve a skill using a test-fix-retest loop. Runs static checks, proposes targeted fixes, rewrites the skill, re-tests, and keeps or reverts based on score change.

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。

Validate skill files for structural compliance and behavioral correctness. Three modes: static (linter), spec (behavioral), audit (coverage report).

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Use when planning or reviewing a frontend testing strategy, selecting the right test layer by risk, mapping coverage across static checks, unit tests, component tests, integration tests, E2E, Storybook/visual regression, a11y, security, performance, or CI gates. Do not use to write individual component/E2E tests or merely run existing validation commands; Chinese triggers include test strategy, test layering, test plan, coverage matrix.

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Use when a task needs the judgment of an Embedded/Firmware Engineer — analyzing worst-case execution time for a hard real-time deadline, choosing static over dynamic memory allocation to avoid fragmentation on a long-uptime device, keeping an interrupt service routine minimal and deferring work to the main loop, synchronizing a variable shared between an ISR and main context to prevent a torn read, or verifying a hardware register interaction against the datasheet's exact timing rather than observed bench behavior.

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。