3,111 artifacts
Skills, MCPs, agents, and plugins. Search to find fast, or page through the catalog.
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Provides comprehensive GitHub operations using gh CLI and GitHub API. Activates when working with pull requests, issues, repositories, workflows, or GitHub API operations including creating/viewing/merging PRs, managing issues, querying API endpoints, and handling GitHub workflows in enterprise or public GitHub environments.
End-to-end playbook for shipping high-quality pull requests to open-source projects you don't maintain — discovery, CONTRIBUTING compliance, PR-size check, minimal-diff implementation, PR description with AI-assisted disclosure, conflict resolution, and post-submission maintainer interaction. Use whenever creating, editing, or pushing a PR to a third-party GitHub repo — "submit a PR", "open a PR", "fix this upstream", "rebase against main", "respond to the bot review", an `owner/repo` target, or 提 PR / 上游 PR / 贡献代码 / rebase 冲突 / 回应维护者.
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Extract Feishu (Lark) Docs, Wiki pages/collections, spreadsheets, and Minutes (妙记) transcripts into faithful local Markdown via the lark-cli API (no LLM rewriting of the body; browser-DOM fallback when lark-cli can't reach the content). Use whenever the source is a Feishu/Lark URL and fidelity matters — 导出飞书文档/合集/妙记转写, 把飞书 wiki/知识库转 markdown, archiving a Feishu collection, exporting a 妙记 transcript, or saving a Feishu page — even if the user only says clipping, archiving, converting, or "save this". Also covers the owner-exported .docx → faithful Markdown path.
Verifies factual claims in documents using web search and official sources, then proposes corrections with user confirmation. Use when the user asks to fact-check, verify information, validate claims, check accuracy, or update outdated information in documents. Supports AI model specs, technical documentation, statistics, and general factual statements.
Create, parse, and control Excel files on macOS. Professional formatting with openpyxl, complex xlsm parsing with stdlib zipfile+xml for investment bank financial models, and Excel window control via AppleScript. Use when creating formatted Excel reports, parsing financial models that openpyxl cannot handle, or automating Excel on macOS.
Download, export, save, or package images from a Google Gemini conversation/chat/app page, especially uploaded images or generated image previews visible in a Gemini thread. Use when the task needs logged-in Chrome/Gemini state, opening Gemini image lightboxes, downloading the larger displayed image files, renaming them in order, and producing a ZIP archive.
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Batch-generate and compare visual design directions so a user can choose the style they actually want. Use when the user says they cannot describe an abstract visual style, asks for many style options, wants to choose from generated UI/design-system images, rejects outputs as too colorful/too dead/too generic, or needs an existing UI/design system evolved without discarding current assets.
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Start or reuse a self-contained local web gallery for browsing Codex-generated images. Use when the user asks to browse Codex generated images, open a local image gallery, inspect ~/.codex/generated_images, view a Codex image output folder, or browse image files produced by Codex.
Investigate and resolve Cloudflare configuration issues using API-driven evidence gathering. Use when troubleshooting ERR_TOO_MANY_REDIRECTS, SSL errors, DNS issues, or any Cloudflare-related problems. Focus on systematic investigation using Cloudflare API to examine actual configuration rather than making assumptions.
Generates professional animated CLI demos as GIFs using VHS terminal recordings. Handles tape file creation, self-bootstrapping demos with hidden setup, output noise filtering, post-processing speed-up, and frame-level verification. Use when users want to create terminal demos, record CLI workflows as GIFs, generate animated documentation, build demo tapes for README files, or need to showcase any command-line tool visually. Also triggers on "record terminal", "VHS tape", "demo GIF", "animate my CLI", or any request to visually demonstrate shell commands.
Programmatic screenshot capture on macOS. Find window IDs with Swift CGWindowListCopyWindowInfo, control application windows via AppleScript (zoom, scroll, select), and capture with screencapture. Use when automating screenshots, capturing application windows for documentation, or building multi-shot visual workflows.
Fetch comprehensive, login-free data for any Bilibili (B站) video — title, UP name and follower count, publish date, partition, tags, per-part cids, live stats (view, like, coin, favorite, share, reply, danmaku), and full danmaku (bullet-comment) text. Use this skill whenever working with a Bilibili video and needing real, citable numbers or metadata — ingesting a Bilibili source into a knowledge base, analyzing why a video performed, verifying a creator's claimed metrics, building a case study, or any time a Bilibili view/like/favorite count is about to be written into a document — fetch it, never hand-type or estimate it. Accepts BVID, av numbers, b23.tv short links, or full URLs. Subtitles are also covered but require the user's Bilibili login.
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记忆审计入口。当我主动决定审视记忆质量时，先读此文件判断应使用哪个子技能。
模式提取与失效解药分析。当发现多条记忆在讲同一个教训，或发现自己在一而再再而三地犯同样的错误时使用。
可发现性审计。当disclosure写法有问题、parent放错、alias缺失、子节点过多时使用。
死数据清洗。当一条记忆读不读你的行为都不会变、感悟没有现实锚点时使用。
信念对决。当父子节点内容冲突、或两条你都认可的记忆逻辑上不能并存时使用。
Conversation memory for AI assistants — record, transcribe, search meetings and voice memos. 19 skills for the full meeting lifecycle: brief → prep → record → tag → debrief → mirror → weekly → graph → video-review.
Voice conversations with Claude Code using local speech-to-text and text-to-speech
Turn complex codebases into clear, navigable architecture diagrams
Multi-cloud orchestration for ML workloads with automatic cost optimization. Use when you need to run training or batch jobs across multiple clouds, leverage spot instances with auto-recovery, or optimize GPU costs across providers.
Write publication-ready ML/AI/Systems papers for NeurIPS, ICML, ICLR, ACL, AAAI, COLM, OSDI, NSDI, ASPLOS, SOSP. Use when drafting papers from research repos, structuring arguments, verifying citations, or preparing camera-ready submissions. Includes LaTeX templates, reviewer guidelines, and citation verification workflows.
Evaluates LLMs across 60+ academic benchmarks (MMLU, HumanEval, GSM8K, TruthfulQA, HellaSwag). Use when benchmarking model quality, comparing models, reporting academic results, or tracking training progress. Industry standard used by EleutherAI, HuggingFace, and major labs. Supports HuggingFace, vLLM, APIs.
Applies cognitive science frameworks for creative thinking to CS and AI research ideation. Use when seeking genuinely novel research directions by leveraging combinatorial creativity, analogical reasoning, constraint manipulation, and other empirically grounded creative strategies.
Guides researchers through structured ideation frameworks to discover high-impact research directions. Use when exploring new problem spaces, pivoting between projects, or seeking novel angles on existing work.
Simplest distributed training API. 4 lines to add distributed support to any PyTorch script. Unified API for DeepSpeed/FSDP/Megatron/DDP. Automatic device placement, mixed precision (FP16/BF16/FP8). Interactive config, single launch command. HuggingFace ecosystem standard.
Generates publication-quality figures for ML papers from research context. Given a paper section or description, extracts system components and relationships to generate architecture diagrams via Gemini. Given experiment results or data, auto-selects chart type and generates data-driven figures via matplotlib/seaborn. Use when creating any figure for a conference paper.
Draft a LaTeX research paper from all previous stage outputs
Search academic literature and generate research hypotheses
Generate a Python code skeleton from an experiment blueprint
Minimal AI-driven research engine: idea → literature review → experiment plan → paper draft
WPA/WPA2-PSK attack methodology — four-way handshake capture via targeted deauthentication, PMKID attacks (no client required), hcxdumptool / hcxpcapngtool conversion to hashcat hc22000 format, GPU-accelerated cracking with dictionary, mask, and rule-based attacks, vendor default-PSK generators (UPC, Sky, BT, etc.), 802.11r FT key cracking, opportunistic key cache analysis, and signal-level optimization. Use when the in-scope network is WPA/WPA2 Personal — the most common consumer/SMB encryption mode.
WPA/WPA2/WPA3-Enterprise (802.1X / EAP) attack methodology — EAP method identification (PEAP-MSCHAPv2, EAP-TTLS, EAP-TLS, EAP-GTC, EAP-PWD, EAP-FAST), evil-twin RADIUS attacks with eaphammer for credential capture, MSCHAPv2 challenge-response cracking, EAP-TLS client certificate theft paths (DPAPI, NDES, AD CS auto-enrollment), supplicant validation bypass (missing server cert validation, missing CN pinning, BYOD misconfigurations), and post-capture pivots into AD via cracked domain credentials. Use for corporate Wi-Fi engagements where the network is 802.1X authenticated.
LoRaWAN and sub-GHz (433 / 868 / 915 MHz) attack methodology — LoRaWAN ABP/OTAA join attack, network/session key reuse, frame counter replay, downlink injection on TTN/Helium-style networks, sub-GHz protocol replay (KeeLoq garage doors, fixed-code remotes, TPMS spoofing, smart plug telemetry), HackRF / RTL-SDR / Flipper Zero workflows, signal analysis with Inspectrum / Universal Radio Hacker, and reconstruction of proprietary packet formats. Use for LoRaWAN deployments (smart cities, asset tracking, industrial telemetry), or any wireless device using the unlicensed 433/868/915 MHz bands (garage openers, doorbells, IoT sensors, RC equipment).
KRACK (CVE-2017-13077..082) and FragAttacks (CVE-2020-24586..588 + 26139-26147) — key reinstallation, fragmentation, and aggregation attacks against WPA2 supplicants. Covers Vanhoef's test scripts, viability against modern patched stacks (mostly mitigated post-2021), residual unpatched embedded devices and IoT vendors, and the practical limitations of these attacks in modern engagements. Use when assessing legacy supplicants, embedded clients, or vendors with poor patch cadence.
Deauthentication and disassociation attacks against 802.11 networks — targeted single-client deauth for handshake capture, broadcast deauth for DoS (with authorization), action-frame attacks bypassing 802.11w (PMF), beacon flooding, mdk4 / aireplay-ng tooling, and rate-limit / PMF-aware operation. Use to coerce client reconnection (handshake capture, evil-twin roaming), as targeted DoS, or to test PMF posture.
Bluetooth Low Energy (BLE) attack methodology — GATT enumeration, characteristic read/write without auth, pairing downgrade (Just Works forced), LE Secure Connections bypass, MITM via active relay, sniffing with Sniffle (TI CC1352) / Ubertooth / Frontline, encryption key extraction (LE Legacy Pairing crackable, LE Secure Connections strong), proximity authentication abuse (cars, locks), and companion-app trust analysis. Use for IoT BLE devices, smart locks, fitness trackers, medical devices, BLE beacons, or any device pairing over BLE.
Business logic vulnerability testing for web/mobile/API engagements. Covers workflow bypass, state machine violations, multi-step process abuse, price/quantity/discount manipulation, currency confusion, coupon stacking, refund/chargeback abuse, race conditions on logic boundaries, parameter tampering for hidden flows, role/tenant boundary violations, time-of-check vs use, anti-automation defeat, fraud-detection evasion, and subscription/quota abuse. Use when scoping an application after surface-level OWASP Top 10 has been covered, or when the asset is a transactional/marketplace/fintech/e-commerce/SaaS app where logic flaws produce direct financial impact.
Penetration test and red team report writing methodology. Covers executive summary structuring (risk-led narrative for non-technical readers), technical finding format (title, severity, affected scope, narrative, reproduction steps, impact, remediation, references), CVSS v3.1 / v4.0 scoring with vector justification, OWASP risk rating, evidence hygiene (redacting credentials, hashing client data, time-stamping every action), screenshot and PoC artifact management, finding chain narratives, scope/limitations/assumptions documentation, retest evidence and remediation tracking, deliverable formats (PDF, DOCX, HTML, JSON for SIEM ingestion), client-customer-deliverable separation, and common report mistakes (over-CVSSing, undermining the triager, missing the 'so what'). Use at the end of an engagement when authoring a deliverable, when restructuring a draft for executive readability, or when establishing a reusable report template for a consulting practice.
Mobile (Android + iOS) application penetration testing methodology. Covers static analysis (apktool/jadx for Android, class-dump/Hopper/IDA for iOS), dynamic instrumentation with Frida and Objection, SSL pinning bypass strategies, root/jailbreak detection bypass, deep-link / URL-scheme abuse, exported component attacks (Android activities, services, providers, receivers; iOS XPC, URL schemes, universal links), insecure data storage (SharedPrefs, KeyStore misuse, NSUserDefaults, Keychain ACL bypass), IPC / Intent redirection, WebView vulnerabilities (JavaScriptInterface, file:// access), Firebase/AWS/Azure misconfiguration leakage, mobile API testing, biometric/Face ID/Touch ID bypass, app-cloning and runtime patching, and mobile malware/RAT analysis primitives. Use for mobile pentest, bug bounty mobile triage, or app-store reconnaissance.
IoT and embedded device security testing methodology. Covers hardware reconnaissance (UART, JTAG, SWD, SPI flash, I2C EEPROM, eMMC chip-off), firmware acquisition (vendor portals, OTA capture, flash dump, binwalk extraction), firmware analysis (filesystem mounting, binary triage, hardcoded secrets, default credential discovery), bootloader attacks (U-Boot console, secure-boot bypass, fault injection), runtime attacks on embedded Linux/RTOS (busybox CVEs, MTD writes, /dev/mem), wireless protocol attacks (Zigbee, BLE, Z-Wave, LoRaWAN, Thread/Matter, sub-GHz), MQTT/CoAP/Modbus/BACnet/OPC-UA exploitation, mobile companion app analysis, cloud-IoT API abuse, and side-channel/glitching basics. Use for IoT pentest, smart-home assessment, ICS/OT testing, or embedded vulnerability research.