Results for “l2s”
53 skillsl2s-automation
Automate L2s operations through Composio's L2s toolkit via Rube MCP, with tool discovery and connection management.
66.9k
contract-addresses
Provides verified contract addresses for major DeFi protocols across Ethereum mainnet and L2s, verified on-chain via eth_getCode.
1.2k · bundle
More results
bitcoin-l2-spark
Spark by Lightspark: statechain-derived L2 with FROST threshold signatures, leaf architecture, Lightning compatibility. Beta launched April 2025; managed by Spark Operators (SOs). USE WHEN: integrating with Spark, evaluating Spark vs Ark vs Lightning, designing leaf-based UTXO trees.
28
layer-2s
Navigate the Ethereum L2 landscape: Arbitrum, Optimism, Base, zkSync, Unichain, and Celo. Covers how they work, deployment, bridging, and selection criteria, including 2025–2026 updates.
1.2k · bundle
lwc-styling-hooks
Theme Salesforce Lightning base components and custom LWCs using SLDS Styling Hooks, covering global and component hooks, shadow DOM considerations, Experience Cloud theming, and SLDS 2 migration.
15 · bundle
specialized
Specialized hardware interfaces and system reliability for Zephyr RTOS. Covers LVGL GUI development, Audio I2S/Codecs, Watchdog timers, and Fault Injection. Trigger when building human-machine interfaces (HMI), audio devices, or high-reliability mission-critical systems.
60 · bundle
lwc-pubsub-patterns
Implements sibling communication between Lightning Web Components using Lightning Message Service (LMS) or the legacy pubsub utility, covering message channel definition, publish/subscribe patterns, and scope selection.
15 · bundle
lwc-lds-writes
Creates, updates, and deletes Salesforce records from Lightning Web Components using Lightning Data Service, covering record input shapes, error handling, and cache refresh strategies.
15 · bundle
lwc-css-and-styling
Style Lightning Web Components using SLDS design tokens, styling hooks, scoped CSS, and ::part() while avoiding common pitfalls like !important and shadow-DOM piercing.
15 · bundle
l1-promote
Review L2 session facts and promote valuable ones to L1 Atomic Memory. Use at end of session or when L2 accumulates facts worth keeping permanently. Runs add-fact.sh for each promoted fact.
2
ltx2
AI video generation with LTX-2.3 22B — text-to-video, image-to-video clips for video production. Use when generating video clips, animating images, creating b-roll, animated backgrounds, or motion content. Triggers include video generation, animate image, b-roll, motion, video clip, text-to-video, image-to-video.
2
lead-generation-and-demand
Comprehensive B2B demand generation and lead acquisition skill. Use when building lead generation systems, creating demand acquisition campaigns, optimizing CAC, designing lead magnets, conducting lead research, or planning multi-channel demand strategies. Covers ICP definition, funnel strategy, channel optimization, lead scoring, attribution, and pipeline generation for B2B SaaS.
88
r2score
Computes the R2Score metric using torchmetrics, handling single and multi-output predictions with options for adjusted and variance-weighted scores.
3
detecting-living-off-the-land-with-lolbas
Detect abuse of legitimate Windows binaries (LOLBins) like certutil, regsvr32, mshta, and rundll32 using process telemetry, Sigma rules, and parent-child process analysis.
24.6k · bundle
nlss
Runs R statistics analyses on local datasets, producing NLSS-format tables, narratives, and JSONL logs from CSV, SAV, RDS, RData, or Parquet files.
54 · bundle
ivx-om-ltx2
AI video generation with LTX-2.3 22B — text-to-video, image-to-video clips for video production. Use when generating video clips, animating images, creating b-roll, animated backgrounds, or motion content. Triggers include video generation, animate image, b-roll, motion, video clip, text-to-video, image-to-video.
0 · bundle
bitcoin-l2-liquid
Liquid Network: federated sidechain by Blockstream. Confidential Transactions, asset issuance (LBTC, USDt-Liquid, others), 2-min blocks, n-of-m federation peg-out. Elements codebase. USE WHEN: building on Liquid, peg-in/peg-out integrations, designing CT-based privacy.
28
linkedin-ads
LinkedIn Ads platform expertise. Audit campaigns, optimize targeting (job title, company, seniority, industry), creative strategy, Lead Gen Forms, conversion tracking, and ABM campaigns. Use when the user asks about LinkedIn advertising, B2B paid social, LinkedIn campaign optimization, Lead Gen Forms, Matched Audiences, or professional audience targeting.
105 · bundle
lwc-graphql-wire
Reads related records across multiple sObjects in one GraphQL request, paginates related lists with cursors, and replaces overlapping @wire(getRecord) calls with a single cache-shared query.
15 · bundle
godmode
Jailbreak LLMs: Parseltongue, GODMODE, ULTRAPLINIAN.
0 · bundle
hunting-for-lolbins-execution-in-endpoint-logs
Hunt for adversary abuse of Living Off the Land Binaries (LOLBins) by analyzing endpoint process creation logs for suspicious execution patterns of legitimate Windows system binaries used for malicious purposes.
24.6k · bundle
ens-primary-name
Set your primary ENS name on Base and other L2s. Use when user wants to set their ENS name, configure reverse resolution, set primary name, or make their address resolve to an ENS name. Supports Base, Arbitrum, Optimism, and Ethereum mainnet.
1 · bundle
rag-caching
Caching strategies across the RAG stack. Semantic caching with GPTCache and LangChain, Redis-based embedding-similarity cache, cache key design, TTL/invalidation, partial caching (cache retrieval only), provider-native prompt caching (Anthropic, OpenAI), and hierarchical L1/L2 caches. USE WHEN: user mentions "semantic cache", "GPTCache", "LLM cache", "prompt caching", "Redis vector cache", "cache invalidation for RAG", "reduce LLM cost", "latency reduction LLM" DO NOT USE FOR: retrieval accuracy - use `rag-patterns`; groundedness checks - use `rag-guardrails`; incremental indexing - use `rag-production`
28
speculative-decoding
Accelerate LLM inference using speculative decoding, Medusa multiple heads, and lookahead decoding techniques. Use when optimizing inference speed (1.5-3.6× speedup), reducing latency for real-time applications, or deploying models with limited compute. Covers draft models, tree-based attention, Jacobi iteration, parallel token generation, and production deployment strategies.
0 · bundle
dsl-dynamic-stop-loss
Manages automated dynamic/trailing stop losses (DSL only) for leveraged perpetual positions on Hyperliquid. Default mode: High Water (pct_of_high_water) — the trailing floor is a percentage of the peak ROE, recalculated every tick, no ceiling. Also supports fixed ROE tiers for legacy positions. Monitors price via cron, ratchets profit floors through configurable tiers, syncs the stop loss to Hyperliquid via edit_position, and auto-closes positions on breach via mcporter. Supports LONG and SHORT, strategy-scoped state isolation, and automatic cleanup.
1 · bundle
ssl-tls-audit
TLS/SSL configuration audit. Tests protocol versions (SSLv2/3, TLS 1.0/1.1/1.2/1.3), cipher strength and ordering, certificate chain validation (intermediates, CT logs, OCSP stapling, pinning), known vulnerabilities (POODLE, BEAST, CRIME, Heartbleed, ROBOT, DROWN, Ticketbleed, GOLDENDOODLE), session management (ticket reuse, resumption, fixation), renegotiation attacks, TLS 1.3-specific issues (0-RTT replay, PSK modes, downgrade), HSTS deep analysis (preload, subdomains, bypass), and certificate revocation (CRL, OCSP responder, stapled response freshness). Compliance-mapped to PCI DSS 4.0 (full Section 4), NIST SP 800-52r2, and FedRAMP. Uses testssl.sh, sslscan, sslyze, openssl, nmap NSE scripts, and nuclei SSL templates. Multi-port scanning across 20+ TLS-bearing services.
21
godmode
Jailbreak API-served LLMs using G0DM0D3 techniques — Parseltongue input obfuscation (33 techniques), GODMODE CLASSIC system prompt templates, ULTRAPLINIAN multi-model racing, encoding escalation, and Hermes-native prefill/system prompt integration. Use when a user wants to bypass safety filters, jailbreak a model, or red-team model robustness.
0 · bundle
bitcoin-l2-stacks
Stacks: Bitcoin smart contract layer with Clarity language, sBTC for native peg, Nakamoto upgrade for fast finality, PoX (Proof of Transfer) consensus. USE WHEN: building Bitcoin smart contracts, integrating sBTC, evaluating Stacks vs RSK / EVM alternatives.
28
speculative-decoding
Accelerate LLM inference using speculative decoding, Medusa multiple heads, and lookahead decoding techniques for 1.5-3.6× speedup without quality loss.
10.4k · bundle
flux-2-klein
Generate images with Flux 2 Klein (Black Forest Labs' distilled fast variant of Flux 2) on RunComfy — bundled with the model's documented prompting patterns so the skill gets sharper output than naive prompting against the same model. Documents Flux 2 Klein's strengths (sub-second latency, multi-reference brand styling, declarative subject-first prompts), the step-count strategy (4–8 for fast iteration, ~25 for polish), the 9B vs 4B variant trade-off, and when to route to Flux 2 Pro / Seedream 5 / GPT Image 2 instead. Calls `runcomfy run blackforestlabs/flux-2-klein/9b/text-to-image` (or `/4b/`) through the local RunComfy CLI. Triggers on "flux 2 klein", "flux-2-klein", "flux klein", "BFL flux 2", or any explicit ask to generate with this model.
5
plan-rls-audit
Audit a Supabase/Postgres project for Row-Level Security and access-control gaps, then produce a phased remediation plan. Use when "RLS", "is my Supabase secure", "anyone can read my data", "lock down my tables". App-layer session/route gates → audit-auth-flows.
8
e2b
E2B Desktop Sandbox with autonomous computer use — cloud Linux environments for browser automation, visual UI grounding, screenshot analysis, and shell execution. Supports Browser Use cloud sessions, Playwright integration, and LLM-driven desktop control. Use when asked about sandboxes, computer use, browser automation, E2B, desktop control, visual testing, or cloud Linux environments.
9
lets-go-rss
Aggregate RSS feeds from YouTube, Vimeo, Behance, Twitter/X, Bilibili, Weibo, Douyin, Xiaohongshu, and Zhihu with incremental updates, deduplication, and AI classification.
99 · bundle
langfuse
Provides expertise in Langfuse for LLM observability, including tracing, prompt management, evaluation, and integration with LangChain, LlamaIndex, and OpenAI.
42.4k
langfuse
Expert in Langfuse - the open-source LLM observability platform. Covers tracing, prompt management, evaluation, datasets, and integration with LangChain, LlamaIndex, and OpenAI. Essential for debugging, monitoring, and improving LLM applications in production. Use when: langfuse, llm observability, llm tracing, prompt management, llm evaluation.
2
langfuse
Expert in Langfuse - the open-source LLM observability platform. Covers tracing, prompt management, evaluation, datasets, and integration with LangChain, LlamaIndex, and OpenAI. Essential for debugging, monitoring, and improving LLM applications in production.
1