pixel-art
Pixel art w/ era palettes (NES, Game Boy, PICO-8).
popular-web-designs
54 real design systems (Stripe, Linear, Vercel) as HTML/CSS.
pretext
Use when building creative browser demos with @chenglou/pretext — DOM-free text layout for ASCII art, typographic flow around obstacles, text-as-geometry games, kinetic typography, and text-powered generative art. Produces single-file HTML demos by default.
prose-writing-style
Use when brainstorming or discussing with the user, writing plans, answering user questions, or whenever a response needs direct technical prose rather than code, data, or a formal document.
sketch
Throwaway HTML mockups: 2-3 design variants to compare.
songwriting-and-ai-music
Songwriting craft and Suno AI music prompts.
touchdesigner-mcp
Control a running TouchDesigner instance via twozero MCP — create operators, set parameters, wire connections, execute Python, build real-time visuals. 36 native tools.
analyzing-backtests
Analyzes algorithmic trading backtest results from Jupyter notebooks and generates summary reports. Use when the user wants to analyze or summarize backtest notebooks.
data-juicer
Primer for using the data-juicer Python library (also written `datajuicer` or `DJ`) — a YAML-driven, OP-based system for cleaning, filtering, deduplicating, transforming, and synthesizing text and multimodal data for foundation models. Use this skill whenever the user mentions data-juicer, DJ, dj-process, dj-analyze, "DJ format", building data recipes / YAML pipelines for LLM training data, or writing custom Filter / Mapper / Deduplicator / Selector / Aggregator / Grouper operators ("OPs"). Also reach for it when the user is putting together a data preprocessing pipeline for LLM pre-training, post-tuning, or multimodal datasets and DJ would be a natural fit, even if they haven't named the library yet — flagging DJ as an option is often the most helpful move.
jupyter-live-kernel
Iterative Python via live Jupyter kernel (hamelnb).
youtube-content
YouTube transcripts to summaries, threads, blogs.
local-columnar-data-inspection
Inspect local columnar/partitioned datasets (Parquet, SQLite staging/workspace DBs, JSONL metadata exports) to answer data-availability, earliest/latest timestamp, schema, and provenance questions without assuming labels are obvious.
marimo-pair
>-
using-nautilus-trader
Use when building, backtesting, or deploying algorithmic trading systems with NautilusTrader (nautilus_trader) — writing Strategy/Actor classes and StrategyConfig, configuring BacktestNode/BacktestEngine, constructing instruments, order management, ParquetDataCatalog/wranglers, message bus and custom data streams, indicators, portfolio/analysis/report generation, or live TradingNode deployment. Curated for v1.230.0.
arch-aur-package-management
Use when setting up, repairing, or using Arch User Repository (AUR) workflows on Arch Linux: prerequisites, yay/paru helper installation, PKGBUILD downloads, libalpm rebuilds after pacman upgrades, and verification.
kanban-orchestrator
Decomposition playbook + anti-temptation rules for an orchestrator profile routing work through Kanban. The "don't do the work yourself" rule and the basic lifecycle are auto-injected into every kanban worker's system prompt; this skill is the deeper playbook when you're specifically playing the orchestrator role.
kanban-worker
Pitfalls, examples, and edge cases for Hermes Kanban workers. The lifecycle itself is auto-injected into every worker's system prompt as KANBAN_GUIDANCE (from agent/prompt_builder.py); this skill is what you load when you want deeper detail on specific scenarios.
offline-vap-cel-verification
Verify or safely change a Kubernetes ValidatingAdmissionPolicy (CEL) offline when the live admission gate is unavailable — golden-pin exact expressions, generate fixtures from the real renderer, run an independent intent-evaluator, and get an independent review.
webhook-subscriptions
Webhook subscriptions: event-driven agent runs.
kairos-collector-performance-baseline
Capture and interpret a durable before/after performance baseline for Kairos collector workers and orchestrator
kairos-crypto-hunt-safety
Use when running parallel Kalshi crypto lake assays in kairos-research; enforces safe DuckDB resource limits, causal signal controls, fill realism, and verified fee/L2 decoding.
kairos-emc-disk-growth-assessment
Diagnose rapid emc-local disk growth without destructive scans or changes
kairos-hotswap-disk-transfer-leg
Run a Kairos migration disk-to-disk copy leg on emc after a drive (PD1/PD2) is inserted into the hot-swap bay — identity gating by UUID, writer checks, persistent systemd rsync units. Use when the user says a PD drive was connected to emc and asks to initiate/continue the transfer.
kairos-ideation-slate-workflow
Run a multi-subagent, pressure-tested trading-strategy ideation round in kairos-research (workflowz style): source scouts → axis-pinned ideators → synthesizer with IRC verdict loop → adversarial reviewers → final critic, ending in a committed docs/ideas/ slate. Use when asked to ideate/refresh an experiment slate or run a round-N ideation campaign.
kairos-kalshi-direct-soak
Run a live Kalshi collector soak in kairos-collector via direct-launch (bypassing start-soak.sh's removed Task-8 rollout harness). Use to verify common-v5 orchestrator/worker/compactor changes produce parquet + converged gauges against the live prod feed.
kairos-lake-characterization-campaign
Orchestrate a parallel multi-agent descriptive characterization of a Kairos lake market vs reference data (e.g. Kalshi family vs pbp), producing a verified compendium doc — use when asked to \"characterize/describe\" a market surface with low-reasoning (sonic) subagents.
blogwatcher
Monitor blogs and RSS/Atom feeds via blogwatcher-cli tool.
kairos-new-lake-ingestion-family
Add a new REST/archive-sourced historical ingestion family (new venue/namespace) to kairos-data-pipeline: adapters package, DuckLake DDL/views/migrations, partition_replace assets, checks, and gates.
kalshi-backtest-artifact-controls
Mandatory artifact controls when assaying Kalshi (or any kline+tape) backtest signals: bar-label look-ahead audit, strict trade-through maker fills, month-split stability, adverse-selection fill checks
kalshi-delta-replay-dislocation-timing
Measure sub-second cross-market dislocation lifetimes on Kalshi lake data (any family) via validated orderbook_delta replay — use for arb-resolution timing, ladder coherence, or two-leg re-sync questions in kairos-research.
kde-mixture-experiment-forensics
Forensic checklist for reviewing local/matchup-level KDE or kernel-mixture density experiments (SEAM-style, conditional spray/density heads) whose local model loses to a pooled marginal baseline or shows a null conditioning effect
himalaya
Himalaya CLI: IMAP/SMTP email from terminal.
minecraft-modpack-server
Host modded Minecraft servers (CurseForge, Modrinth).
pokemon-player
Play Pokemon via headless emulator + RAM reads.
codebase-inspection
Inspect codebases w/ pygount: LOC, languages, ratios.
get-pr-comments
Retrieve and filter GitHub pull request comments with the gh CLI.
github-auth
GitHub auth setup: HTTPS tokens, SSH keys, gh CLI login.
github-code-review
Review PRs: diffs, inline comments via gh or REST.
github-issues
Create, triage, label, assign GitHub issues via gh or REST.
github-pr-workflow
GitHub PR lifecycle: branch, commit, open, CI, merge.
github-repo-management
Clone/create/fork repos; manage remotes, releases.
find-nearby
Find nearby places (restaurants, cafes, bars, pharmacies, etc.) using OpenStreetMap. Works with coordinates, addresses, cities, zip codes, or Telegram location pins. No API keys needed.
mcporter
Use the mcporter CLI to list, configure, auth, and call MCP servers/tools directly (HTTP or stdio), including ad-hoc servers, config edits, and CLI/type generation.
native-mcp
MCP client: connect servers, register tools (stdio/HTTP).
gif-search
Search/download GIFs from Tenor via curl + jq.
heartmula
HeartMuLa: Suno-like song generation from lyrics + tags.
songsee
Audio spectrograms/features (mel, chroma, MFCC) via CLI.
lambda-labs-gpu-cloud
Reserved and on-demand GPU cloud instances for ML training and inference. Use when you need dedicated GPU instances with simple SSH access, persistent filesystems, or high-performance multi-node clusters for large-scale training.
modal-serverless-gpu
Serverless GPU cloud platform for running ML workloads. Use when you need on-demand GPU access without infrastructure management, deploying ML models as APIs, or running batch jobs with automatic scaling.
evaluating-llms-harness
lm-eval-harness: benchmark LLMs (MMLU, GSM8K, etc.).
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