Browse Skills — Page 143
32,221 public skills · showing 14,201–14,300
- 100/100
heatmap-beautifier
aipoch/medical-research-skills
Professional beautification tool for gene expression heatmaps, automatically adds clustering trees, color annotation tracks, and intelligently optimizes label layout.
- 100/100
hedge-detector
lyndonkl/claude
Classifies every hedge in a substacker draft as either a precision hedge (keep — "n=1 may not replicate", "I do not know") or an epistemic-weakness hedge (flag — "I think", "perhaps", "arguably", "it could be argued"). Only flags weakness hedges; suggests either a commit (remove hedge, take position) or a specific hedge (name the uncertainty). Use when a draft feels wishy-washy or when a cluster of modal verbs appears. Trigger keywords: hedging, I think, perhaps, arguably, uncertainty, weak claim, wishy-washy.
- 80/100
hedgefundmonitor
eric861129/SKILLS_All-in-one
Query the OFR (Office of Financial Research) Hedge Fund Monitor API for hedge fund data including SEC Form PF aggregated statistics, CFTC Traders in Financial Futures, FICC Sponsored Repo volumes, and FRB SCOOS dealer financing terms. Access time series data on hedge fund size, leverage, counterparties, liquidity, complexity, and risk management. No API key or registration required. Use when working with hedge fund data, systemic risk monitoring, financial stability research, hedge fund leverage or leverage ratios, counterparty concentration, Form PF statistics, repo market data, or OFR financial research data.
- 100/100
hedging-strategy
HKUDS/Vibe-Trading
Hedging strategy design (beta hedge / option protection / tail risk / cross-asset hedging), including hedge-ratio calculation and cost evaluation.
- 100/100
helcim-automation
ComposioHQ/awesome-claude-skills
"Automate Helcim tasks via Rube MCP (Composio). Always search tools first for current schemas."
- 40/100
helicone
vm0-ai/vm0-skills
Helicone API for LLM observability — request logging, cost tracking, and performance analytics. Use when user mentions "Helicone", "LLM logs", "AI cost tracking", "request tracing", "token usage", "latency analytics", or "prompt monitoring".
- 100/100
helium-mcp
ComposioHQ/awesome-codex-skills
Search real-time news with bias scoring, get live stock/ETF/crypto data with AI analysis, ML options pricing, balanced news synthesis, and meme search via the Helium MCP server.
- 100/100
helium-mcp-v2
diegosouzapw/awesome-omni-skills
Helium MCP workflow skill. Use this skill when the user needs Connect to Helium's MCP server for news research, media bias analysis, balanced perspectives, stock/options data, and semantic meme search across 3.2M+ articles and 5,000+ sources and the operator should preserve the upstream workflow, copied support files, and provenance before merging or handing off.
- 100/100
helius
sendaifun/skills
Build Solana applications with Helius infrastructure. Covers transaction sending (Sender), asset/NFT queries (DAS API), real-time streaming (WebSockets, Laserstream), event pipelines (webhooks), priority fees, wallet analysis, and agent onboarding.
- 100/100
helius-dflow
sendaifun/skills
Build Solana trading applications combining DFlow trading APIs with Helius infrastructure. Covers spot swaps (imperative and declarative), prediction markets, real-time market streaming, Proof KYC, transaction submission via Sender, fee optimization, shred-level streaming via LaserStream, and wallet intelligence.
- 100/100
helius-phantom
sendaifun/skills
Build frontend Solana applications with Phantom Connect SDK and Helius infrastructure. Covers React, React Native, and browser SDK integration, transaction signing via Helius Sender, API key proxying, token gating, NFT minting, crypto payments, real-time updates, and secure frontend architecture.
- 100/100
helixa
BankrBot/skills
Helixa — Onchain identity, reputation, and Cred Scores for AI agents on Base. Use when an agent wants to mint an identity NFT, check its Cred Score, verify social accounts, update traits/narrative, query agent reputation data, check staking info, or search the agent directory. Supports SIWA (Sign-In With Agent) auth and x402 micropayments. Also use when asked about Helixa, AgentDNA, ERC-8004, Cred Scores, $CRED token, or agent identity.
- 100/100
hello-demo
oaustegard/claude-skills
Delivers a static Hello World HTML demo page with bookmarklet. Use when user requests the hello demo, hello world demo, or demo page.
- 100/100
hello-skill
agentskills-io/agent-skills-in-action
Generates a standardized, professional greeting based on the time of day and user role. Use this ONLY when the user initiates a conversation or asks for a formal introduction.
- 100/100
hello-world
github/copilot-cli-for-beginners
A minimal skill example - use when learning the skill format
- 100/100
helloleads-automation
ComposioHQ/awesome-claude-skills
"Automate Helloleads tasks via Rube MCP (Composio). Always search tools first for current schemas."
- 100/100
helm
simota/agent-skills
Simulating business strategy via short/mid/long-term scenario planning from financial, market, and competitive data. Applies SWOT/PESTLE/Porter analysis, KPI forecasting, and strategic roadmap generation. Does not write code.
- 100/100
helm-chart-builder
alirezarezvani/claude-skills
Helm chart development agent skill and plugin for Claude Code, Codex, Gemini CLI, Cursor, OpenClaw — chart scaffolding, values design, template patterns, dependency management, security hardening, and chart testing. Use when: user wants to create or improve Helm charts, design values.yaml files, implement template helpers, audit chart security (RBAC, network policies, pod security), manage subcharts, or run helm lint/test.
- 90/100
helm-chart-scaffolding
wshobson/agents
Design, organize, and manage Helm charts for templating and packaging Kubernetes applications with reusable configurations. Use when creating Helm charts, packaging Kubernetes applications, or implementing templated deployments.
- 100/100
helm-chart-scaffolding
benjaminasterA/antigravity-awesome-skills
Design, organize, and manage Helm charts for templating and packaging Kubernetes applications with reusable configurations. Use when creating Helm charts, packaging Kubernetes applications, or impl...
- 100/100
helm-chart-scaffolding-v2
diegosouzapw/awesome-omni-skills
Helm Chart Scaffolding workflow skill. Use this skill when the user needs Comprehensive guidance for creating, organizing, and managing Helm charts for packaging and deploying Kubernetes applications and the operator should preserve the upstream workflow, copied support files, and provenance before merging or handing off.
- 100/100
helm-charts
TheBushidoCollective/han
Use when understanding and creating Helm charts for packaging and deploying Kubernetes applications.
- 100/100
helm-templates
TheBushidoCollective/han
Use when working with Helm templates and template functions for generating Kubernetes manifests dynamically.
- 90/100
helm-values
TheBushidoCollective/han
Use when managing Helm values files and configuration overrides for customizing Kubernetes deployments.
- 100/100
help
ComposioHQ/awesome-claude-plugins
Show skill-bus overview, status, and available commands. Quick reference for all skill-bus features.
- 100/100
help-article-from-tickets
Significant-Gravitas/skills-catalog
Write a help article from repeat tickets, using only confirmed steps and the customer's own words.
- 100/100
help-center-answers-and-kb
Significant-Gravitas/skills-catalog
Use for how-to questions, repeat issues, and onboarding guidance: docs-first answers with citations, plus the saved reply or KB entry the next ticket reuses.
- 100/100
help-center-article-generator
gooseworks-ai/goose-skills
>
- 0/100
help-url-reference
Community-Access/accessibility-agents
Centralized help URL reference for accessibility remediation. Maps axe-core rule IDs to Accessibility Insights info-examples pages, document rule IDs to Microsoft Office and Adobe PDF help pages, and WCAG criteria to W3C Understanding documents. Use when generating CSV exports, markdown reports, or any output that links findings to external remediation documentation.
- 100/100
helpdesk-automation
benjaminasterA/antigravity-awesome-skills
Automate HelpDesk tasks via Rube MCP (Composio): list tickets, manage views, use canned responses, and configure custom fields. Always search tools first for current schemas.
- 100/100
helpdesk-automation-v2
diegosouzapw/awesome-omni-skills
HelpDesk Automation via Rube MCP workflow skill. Use this skill when the user needs Automate HelpDesk tasks via Rube MCP (Composio): list tickets, manage views, use canned responses, and configure custom fields. Always search tools first for current schemas and the operator should preserve the upstream workflow, copied support files, and provenance before merging or handing off.
- 100/100
helpwise-automation
ComposioHQ/awesome-claude-skills
"Automate Helpwise tasks via Rube MCP (Composio). Always search tools first for current schemas."
- 100/100
hephaestus-build
agentlas-ai/Agentlas-OS
Use when the user types /prompts:hep-build, mentions @Hephaestus for build work, asks to create a single Agentlas agent, create a multi-agent team, or package an existing local/external agent into Agentlas architecture.
- 100/100
hephaestus-cloud
agentlas-ai/Agentlas-OS
Use when the user types /hep-cloud or asks to staff from THEIR OWN Agentlas cloud packages only. Cloud is one exact source scope; Network means Local + owner Cloud + public Hub.
- 80/100
hephaestus-network
agentlas-ai/Agentlas-OS
Use when the user types /hep-network, mentions @Hephaestus, or asks Agentlas to staff a task from registered Local, owner Cloud, and public Hub agents or teams. The active host LLM is the temporary orchestrator.
- 100/100
hephaestus-storm
agentlas-ai/Agentlas-OS
Use when the user types /hep-storm, says @Hephaestus storm <goal>, or asks to drive a goal to verified completion through a force-robust Stormbreaker loop. Stormbreaker routes the goal to real Agentlas specialists, materializes a dependency-ordered pipeline fabric, and runs each work packet as a verifier-first hardened loop that does not stall, run away, or claim false success. Use it for loop-worthy work — apps, sites, agents, automations, debugging, multi-step research, data/report generation. Trivial questions are answered directly, not stormed.
- 100/100
herdr-e2b-bench
e2b-dev/herdr-e2b-sandbox
Build and run a coding-agent shootout in this repo — one task, N agents (claude, codex, opencode, amp, grok, droid, prime, muse), each in its own E2B sandbox, graded by a held-out test and compared on tokens, cost, wall clock and diff size. Takes one argument. `create` authors a new benchmark task: the brief (bench/BENCH.md), the held-out grader (bench/grade.sh), and the reusable measurement scripts (bench/usage.sh, bench/judge.sh, bench/README.md), then calibrates the grader by measuring its floor and its ceiling. `execute` drives an existing benchmark: fan out with e2b-box fleet, grade with e2b-bench, table with usage.sh, blind-judge with judge.sh, tear down. `quick` is `execute` on the fast task pair (bench/BENCH-quick.md + bench/grade-quick.sh) — ~5 minutes of agent time and a ~1s grader, for when you are testing the harness rather than the agents. Use this skill whenever the user mentions a bench, benchmark, shootout, race, "which agent is better", harness-bench, bench/BENCH.md, bench/grade.sh, held-out test, grading a fleet, best-of-n, or wants to compare coding agents on the same task, or says quick bench, fast bench, short bench, smoke bench, quick lap, or asks for a bench that does not take an hour — and also whenever they ask to add, change, calibrate, or score a benchmark task in this repo, or to run one for a demo recording. Prefer this over improvising e2b-fleet and e2b-bench calls by hand, because the held-out mechanics and the grader calibration are easy to get subtly wrong.
- 100/100
herdr-orchestration
compozy/agh
Orchestrate Claude and Codex worker TUIs from a controller agent through herdr panes and the herdr socket CLI. Use when delegating bounded tasks to herdr worker panes, running user-activated plan-first delegations (Claude Code plan mode, Codex Plan mode), waiting on native agent status (idle, working, blocked, done), or verifying worker reports. Workers launch as interactive TUIs via herdr agent start — never through headless runners (compozy exec, claude -p, codex exec). Not for cmux workspaces (see cmux-orchestration) and not for end-user herdr control.
- 100/100
here-automation
ComposioHQ/awesome-claude-skills
"Automate Here tasks via Rube MCP (Composio). Always search tools first for current schemas."
- 100/100
here-be-git
mkurman/zorai
Initialise a git repository with optional agent commit instructions and .gitignore. Use when users say "here be git", "init git", "initialise git", or otherwise indicate they want to set up version control in the current directory.
- 90/100
here.now
NousResearch/hermes-agent
Publish static sites to {slug}.here.now and store private files in cloud Drives for agent-to-agent handoff.
- 95/100
hermes-agent
NousResearch/hermes-agent
Configure, extend, or contribute to Hermes Agent.
- 100/100
hermes-agent-setup
superagi/hermes-agent
Help users configure Hermes Agent — CLI usage, setup wizard, model/provider selection, tools, skills, voice/STT/TTS, gateway, and troubleshooting. Use when someone asks to enable features, configure settings, or needs help with Hermes itself.
- 100/100
hermes-agent-skill-authoring
NousResearch/hermes-agent
Author in-repo SKILL.md: frontmatter, validator, structure.
- 100/100
hermes-atropos-environments
NousResearch/hermes-agent
Build, test, and debug Hermes Agent RL environments for Atropos training. Covers the HermesAgentBaseEnv interface, reward functions, agent loop integration, evaluation with tools, wandb logging, and the three CLI modes (serve/process/evaluate). Use when creating, reviewing, or fixing RL environments in the hermes-agent repo.
- 100/100
hermes-graphify-gsd-nonintrusive-workflow
seaworld008/Commonly-used-high-value-skills
Use when integrating Hermes Agent, graphify, and GSD into a local development workflow without modifying upstream repositories, especially when the user wants upgrade-safe wrappers, project-level workflow scripts, graph-aware planning, and a reusable setup that survives future upstream updates.
- 100/100
hermes-graphify-gsd-project-integration
seaworld008/Commonly-used-high-value-skills
Use when integrating Hermes Agent, graphify, and GSD into a specific repository, especially for adding project-local graph refresh scripts, AGENTS.md guidance, README workflow docs, gitignore entries, and a brownfield-friendly planning loop without modifying upstream tool repositories.
- 100/100
hermes-graphify-gsd-runtime-operator
seaworld008/Commonly-used-high-value-skills
Use when operating or debugging a repo-local Hermes + graphify + GSD autonomous runtime, especially when checking writer ownership, execution-surface eligibility, handoff/blocked state, stale cron or lease metadata, and whether the main project repo is still the only recommended writer surface.
- 100/100
hermes-history-ingest
Ar9av/obsidian-wiki
>
- 100/100
hermes-imports
affaan-m/ECC
Convert local Hermes operator workflows into sanitized ECC skills and release-pack artifacts. Use when preparing a Hermes workflow for public ECC reuse without leaking private workspace state, credentials, or local-only paths.
- 100/100
hermes-tweet
wshobson/agents
>
- 100/100
hero
QinghongLin/data2story-skill
Craft the COVER — the one animated <video> hero that opens the page above the headline, built from a Scout-verified still (or an abstract generated still) via a deterministic source ladder. The cover is animated by DEFAULT; a static <img> is only the recorded last rung. Owns the hero video + its static furniture; the Interaction Engineer owns the pick-a-side overlay, the Cinematographer stages the cover as cin_00. Reuses data-des=des_hero_video (no new provenance prefix). Outputs hero.json + assets/teaser.webm + _web.mp4 + .jpg poster.
- 100/100
hero-generator
kostja94/marketing-skills
When the user wants to design, optimize, or audit hero sections (above-the-fold main visual area). Also use when the user mentions "hero," "hero section," "hero area," "above the fold," "above the fold content," "landing hero," "main banner," "banner section," "first fold," "hero section design," "hero conversion," "split layout hero," "centered hero," or "hero alignment." For homepage, use homepage-generator.
- 100/100
heterogeneity-investigation
yogsoth-ai/de-anthropocentric-research-engine
Explain why different studies reach different conclusions — heterogeneity investigation protocol. Budget: 30 studies, 30 effect sizes, 50 web searches.
- 100/100
heterogeneity-source-analysis
yogsoth-ai/de-anthropocentric-research-engine
Identify and classify sources of between-study heterogeneity (clinical, methodological, statistical)
- 75/100
hetzner-cloud
TerminalSkills/skills
>-
- 80/100
hetzner-deploy
fcakyon/claude-codex-settings
This skill should be used when user asks to "deploy to Hetzner", "create Hetzner server", "manage Hetzner Cloud", "hcloud CLI", or works with Hetzner Cloud infrastructure including servers, networks, firewalls, load balancers, DNS zones, and volumes.
- 100/100
heuristic
educlopez/ui-craft
Produce a scored heuristic critique of the UI using Nielsen's 10 + 6 design laws + optional persona walkthroughs. Outputs a machine-parseable scorecard plus a 0-100 UsabilityScore (the judged companion to the deterministic UICraftScore). Invoke when the user asks for heuristic on their UI, or mentions 'heuristic' alongside design / UI / frontend work.
- 100/100
heuristics-and-checklists
lyndonkl/claude
Provides practical frameworks for fast decision-making through mental shortcuts (heuristics) and systematic error prevention through structured checklists. Guides through designing effective heuristics, creating checklists for complex procedures, and recognizing when shortcuts lead to biases. Use when making decisions under time pressure or uncertainty, preventing errors in complex procedures, designing decision rules or checklists, simplifying complex choices, or when user mentions heuristics, rules of thumb, mental models, checklists, error prevention, cognitive biases, satisficing, or standard operating procedures.
- 100/100
hex-grid-spatial
elizaOS/eliza
Hex grid spatial utilities for offset coordinate systems. Use when working with hexagonal grids, calculating distances, finding neighbors, or spatial queries on hex maps.
- 100/100
hex1b
microsoft/aspire
CLI tool for automating any terminal application — TUI apps, shells, CLI tools, REPLs, and more. Use when you need to launch a process in a virtual terminal, capture its screen output, inject keystrokes or mouse input, take screenshots, record sessions, or assert on what's visible.
- 100/100
hexagonal-architecture
affaan-m/ECC
Design, implement, and refactor Ports & Adapters systems with clear domain boundaries, dependency inversion, and testable use-case orchestration across TypeScript, Java, Kotlin, and Go services.
- 100/100
hexdocs-fetcher
oliver-kriska/claude-elixir-phoenix
Fetch HexDocs for Elixir libraries with HTML-to-markdown conversion. Use when looking up docs on hexdocs.pm — modules, functions, guides, changelogs.
- 100/100
hey
basecamp/hey-cli
|
- 100/100
heygen
zapier/connectors
Agent-callable HeyGen tools — generate AI avatar videos, translate and lip-sync videos, synthesize speech, and clone or browse voices and avatars. Use when the user mentions HeyGen or wants to create, translate, or check the status of AI videos, or to generate or clone a voice — including requests that don't name HeyGen, e.g. make an avatar video from a script, translate a video to Spanish, turn a script into a voiceover, or clone a voice from a recording.
- 100/100
HeyGen Automation
ComposioHQ/awesome-claude-skills
"Automate AI video generation, avatar browsing, template-based video creation, and video status tracking through HeyGen's platform via Composio"
- 95/100
heygen-api
TerminalSkills/skills
>-
- 95/100
heygen-avatar
heygen-com/skills
|
- 80/100
heygen-avatar-lite
aAAaqwq/AGI-Super-Team
Create AI digital human videos with HeyGen API. Free starter guide.
- 95/100
heygen-translate
heygen-com/skills
|
- 95/100
heygen-video
heygen-com/skills
|
- 100/100
heyreach-automation
ComposioHQ/awesome-claude-skills
"Automate Heyreach tasks via Rube MCP (Composio). Always search tools first for current schemas."
- 100/100
heyzine-automation
ComposioHQ/awesome-claude-skills
"Automate Heyzine tasks via Rube MCP (Composio). Always search tools first for current schemas."
- 100/100
hf-broker
huggingface/mlclaw
Use ML Claw's HF Broker for protected Hugging Face repository and bucket reads, writes, temporary grants, recovery, and revocation. Use instead of asking for or exposing a Hugging Face access token.
- 95/100
hf-cli
huggingface/skills
Hugging Face Hub CLI (`hf`) for downloading, uploading, and managing models, datasets, spaces, buckets, repos, papers, jobs, and more on the Hugging Face Hub. Use when: handling authentication; managing local cache; managing Hugging Face Buckets; running or scheduling jobs on Hugging Face infrastructure; managing Hugging Face repos; discussions and pull requests; browsing models, datasets and spaces; reading, searching, or browsing academic papers; managing collections; querying datasets; configuring spaces; setting up webhooks; or deploying and managing HF Inference Endpoints. Make sure to use this skill whenever the user mentions 'hf', 'huggingface', 'Hugging Face', 'huggingface-cli', or 'hugging face cli', or wants to do anything related to the Hugging Face ecosystem and to AI and ML in general. Also use for cloud storage needs like training checkpoints, data pipelines, or agent traces. Use even if the user doesn't explicitly ask for a CLI command. Replaces the deprecated `huggingface-cli`.
- 100/100
hf-cloud-aws-context-discovery
huggingface/skills
Discover the user's local AWS context (active profile, region, account ID, caller identity) at the start of any AWS task. Use this skill before any other AWS work — deploying to SageMaker, creating resources, calling AWS APIs, or anything that touches an AWS account. Use it especially when the user has not specified a region or profile explicitly, when they say things like "use my AWS account", "deploy to AWS", "use my profile", or when about to make any AWS CLI or SDK call. Never guess the region or account ID — always use this skill to read it from the local configuration first.
- 100/100
hf-cloud-python-env-setup
huggingface/skills
Set up an isolated Python environment for SageMaker / AWS work, with the right Python version and current boto3. Use this skill whenever Python code will be executed for a SageMaker deployment, training job, or any AWS automation — including when about to run `pip install`, when about to invoke `boto3`, when creating or activating a virtualenv, or when the user asks to "set up the environment". Never use system Python and never `pip install` into it. Always isolate. This skill prevents the most common failure modes: wrong Python version, dependency conflicts, and stale SDKs.
- 100/100
hf-cloud-sagemaker-deployment-planner
huggingface/skills
Plan and coordinate the deployment of a model to Amazon SageMaker AI. Use this skill whenever the user wants to deploy, host, serve, or expose a model on SageMaker or AWS — including phrases like "deploy a model", "host this LLM on AWS", "serve this embedding model", "deploy a reranker", "deploy a text-to-image / diffusion model", "host this for async inference", "create an endpoint", "serve my fine-tuned model", or any request that involves making a model available for inference on AWS. Use this even when the user is vague (e.g. "I just want to get this running on AWS, you figure it out"). Works for text-generation LLMs, embedding models, rerankers, classifiers, text-to-image / diffusion models — picks the right serving stack and chooses between real-time and async inference. This is the entry-point skill for SageMaker deployment work — it asks clarifying questions, picks a deployment pathway, and coordinates the other deployment skills.
- 100/100
hf-cloud-sagemaker-iam-preflight
huggingface/skills
Ensure a usable SageMaker execution role exists before deploying or training. Use this skill whenever about to create a SageMaker endpoint, model, training job, or any resource that requires an execution role. Use it especially when the user has not provided a role ARN explicitly, when scripts are about to call `iam:CreateRole`, or when an AccessDenied error mentions an IAM action. Never blindly call `iam:CreateRole` — always check for existing roles first. This skill prevents the most common SageMaker deployment failure: trying to create IAM resources from an SSO principal that has no IAM write permissions.
- 100/100
hf-cloud-sagemaker-production-defaults
huggingface/skills
Create a SageMaker endpoint (real-time, real-time scale-to-zero, or async) with autoscaling, CloudWatch alarms, and tagging enabled by default. Use this skill whenever about to create a SageMaker endpoint, write deployment code that calls `create_endpoint`, or finalize a deployment after the image URI and IAM role are known. Provides deploy.py for real-time endpoints, deploy_ic.py for real-time endpoints that scale to zero instances via inference components, and deploy_async.py for async endpoints (also scale-to-zero). This is the last step in the SageMaker deployment workflow. Never generate a bare `create_endpoint` call without these defaults — endpoints without autoscaling or alarms are demos, not deployments.
- 95/100
hf-cloud-serving-image-selection
huggingface/skills
Pick the right serving container for a SageMaker model deployment and find its current image URI. Use this skill whenever about to deploy a model to a SageMaker endpoint and an image URI needs to be chosen — including when the user says "deploy this LLM", "host this HuggingFace model", "serve this fine-tuned model", "deploy this embedding model", "host a reranker", "serve a sentence-transformers model", or when about to hardcode any container URI in deployment code. HuggingFace-curated Deep Learning Containers are ALWAYS preferred: HuggingFace vLLM (LLMs and generative rerankers), HuggingFace vLLM-Omni (multimodal), TEI (embeddings/cross-encoder rerankers), HF Inference Toolkit (other transformers). Generic images (AWS vLLM, DJL-LMI, SGLang) are used only when no HuggingFace image is compatible — never merely because they carry a newer version. Never hardcode a container URI from memory and never default to TGI. Prevents stale-image failures and wrong-region URIs.
- 100/100
hf-mcp
huggingface/skills
Use Hugging Face Hub via MCP server tools. Search models, datasets, Spaces, papers. Get repo details, fetch documentation, run compute jobs, and use Gradio Spaces as AI tools. Available when connected to the HF MCP server.
- 100/100
hf-mem
huggingface/skills
Hugging Face CLI to estimate the required memory to load Safetensors or GGUF model weights for inference from the Hugging Face Hub
- 100/100
hf-release-notes
huggingface/huggingface_hub
Generate Hugging Face Hub (huggingface_hub) release notes from cached PR JSON files. Use when asked to draft release notes from PR files.
- 100/100
hf-space-deployer
huggingface/research-agent
Deploy fast-agent MCP Servers to Hugging Face Spaces using Docker. Use when the user wants to deploy an "agent card" as an MCP Server. Includes templates and CLI commands for deploying agent cards with custom tools to HF Spaces.
- 85/100
hf-space-recovery
huggingface/OpenEnv
Diagnose and recover failing or stuck Hugging Face Space deployments for OpenEnv environments. Use when deploying envs from `envs/` to the Hub (`openenv` namespace with version suffixes), when Spaces are in `BUILDING`/`APP_STARTING`/`RUNTIME_ERROR`, or when release collections need to be reconciled after targeted redeploys.
- 100/100
hft-quant-expert
aAAaqwq/AGI-Super-Team
Quantitative trading expertise for DeFi and crypto derivatives. Use when building trading strategies, signals, risk management. Triggers on signal, backtest, alpha, sharpe, volatility, correlation, position size, risk.
- 100/100
hgnc-api
aipoch/medical-research-skills
Access the HGNC (HUGO Gene Nomenclature Committee) database to search for and retrieve gene information including symbols, names, IDs, and other metadata.
- 100/100
hi-c-analysis-compartment-analysis
swaruplab/operon
Detects A/B chromatin compartments from balanced Hi-C contact matrices via eigenvector decomposition of the distance-normalized, Pearson-correlated cis matrix with cooltools (eigs_cis), then orients (phases) the compartment eigenvector against a GC or gene-density track so the active (A) sign is not arbitrary. Covers the eigenvector-is-a-choice problem (per-arm view_df to remove the centromere gradient; picking the eigenvector by max correlation with activity, not by eigenvalue), GC phasing with bioframe.frac_gc, resolution choice (100kb-1Mb), saddle plots and saddle_strength for compartmentalization strength, the cohesin-loss-strengthens-compartments result, subcompartments (SNIPER/Calder/dcHiC), and cross-condition compartment switching. Use when calling A/B compartments, computing E1/eigenvectors, phasing the eigenvector, building saddle plots, choosing a compartment resolution, quantifying compartment strength, or comparing compartmentalization across conditions.
- 100/100
hi-c-analysis-contact-pairs
swaruplab/operon
Turns Hi-C/Micro-C FASTQ into a deduplicated, filtered .pairs file with pairtools and decides whether the library worked. Covers the bwa mem -SP5M / bwa-mem2 / chromap --preset hic alignment idiom (mates mapped as independent single-end reads), pairtools parse vs parse2 and the walks-policy choice (5unique pairwise vs all for Pore-C/Micro-C concatemers), pair-type classification (keep UU and rescued UC), dedup (PCR vs optical/by-tile), select by pair_type/MAPQ/distance, restriction-fragment handling (restrict, Arima dual-enzyme, Micro-C/DNase fragment-free), and allele-specific phasing (pairtools phase to two coolers). The library-QC decision uses % long-range cis as the one-number quality metric, trans as the noise floor, orientation balance as fragment-map-free dangling-end/self-circle QC, and % duplicates as a complexity proxy. Use when processing Hi-C/Micro-C/Omni-C reads into pairs, judging library quality, handling multi-enzyme or restriction-agnostic protocols, or generating allele-specific contacts.
- 100/100
hi-c-analysis-hic-data-io
swaruplab/operon
Loads, converts, and manipulates Hi-C contact matrices in cooler format (.cool/.mcool/.scool) and Juicer .hic, using cooler (Python + CLI), hic2cool, and hictk. Covers the single-resolution mcool URI (file.mcool::/resolutions/<bp>), the load-bearing divisive-vs-multiplicative weight-naming rule (KR/VC/VC_SQRT auto-divisive vs cooler's multiplicative weight), what survives .hic<->.cool conversion (FRAG matrices and norm vectors do not), raw-vs-balanced coarsening, the .pairs upper-triangle/chromsize-order contract, and chrom-naming/bin-table provenance. Use when loading a cooler, converting .hic to .mcool, selecting a resolution, building a cooler from pairs or a matrix, coarsening/zoomifying, importing Juicer norm vectors, or debugging all-NaN balanced matrices and chr1-vs-1 empty fetches.
- 100/100
hi-c-analysis-hic-differential
swaruplab/operon
Compares Hi-C contact maps between conditions across the right scale -- differential bin-pair contacts (multiHiCcompare, diffHic), differential A/B compartments (dcHiC), differential TAD boundaries (delta insulation), and differential loops (diffloop, DiffHiChIP) -- with distance-stratified between-sample normalization, replicate-aware NB-GLM FDR, HiCRep SCC reproducibility gating, and CNV correction for cancer/aneuploid samples. Use when comparing Hi-C between treatment and control, finding differential contacts/compartments/boundaries/loops, normalizing two maps of unequal depth, choosing a replicate-aware test, gating replicates with SCC, or correcting copy-number artifacts before a tumor-vs-normal comparison.
- 100/100
hi-c-analysis-hic-visualization
swaruplab/operon
Renders Hi-C contact matrices honestly and reproducibly with matplotlib, cooltools, HiCExplorer, pyGenomeTracks, FAN-C, CoolBox, and plotgardener. Covers the raw/ICE-balanced/observed-over-expected transform choice, LogNorm vs symmetric-diverging colormaps with vmax/percentile clipping, resolution-to-feature matching (compartments 100-500kb, TADs 10-40kb, loops 5-10kb), square vs rotated-triangle track-stacking, NaN/white-stripe handling, virtual 4C, APA/saddle/on-diagonal pileups, two-condition side-by-side and log2-ratio maps, and interactive (HiGlass) vs scripted-static publication figures. Use when plotting a contact matrix, choosing a normalization or color scale, building a multi-track Hi-C figure, making a virtual 4C profile, piling up loops/boundaries, or comparing two conditions.
- 100/100
hi-c-analysis-hichip-plac-loops
swaruplab/operon
Calls significant loops from protein-directed and targeted 3C assays (HiChIP, PLAC-seq, Capture Hi-C/PCHi-C, ChIA-PET) where the contact background is peak-anchored and coverage-biased, so generic Hi-C loop callers (cooltools dots, Juicer HiCCUPS) use the wrong null. Covers FitHiChIP (config-driven coverage+distance-decay spline regression, peak-to-peak vs peak-to-all foreground, loose vs stringent background, coverage vs ICE bias), MAPS (positive Poisson regression on bias factors for PLAC-seq/HiChIP), hichipper (restriction-site-distance bias model + library QC), CHiCAGO (Delaporte two-component Brownian+technical background for asymmetric bait x other-end Capture Hi-C), the with/without separate-ChIP anchor decision, and differential loops via diffloop. Use when calling loops from HiChIP/PLAC-seq/Capture Hi-C, choosing FitHiChIP/MAPS/CHiCAGO, picking peak-to-all vs peak-to-peak, setting the loop FDR, supplying ChIP peaks as anchors, QCing a HiChIP library, or comparing loops between conditions.
- 100/100
hi-c-analysis-loop-calling
swaruplab/operon
Detects focal chromatin loops (point interactions / corner-dots) in balanced Hi-C and Micro-C contact maps and aggregates/validates a loop set. Covers de-novo calling with cooltools dots (HiCCUPS-style 4-background local enrichment with lambda-chunked FDR), chromosight (template-correlation), and Mustache (scale-space blob detection); aggregate peak analysis (APA) via cooltools pileup for confirmation; the depth/resolution prerequisite (de-novo needs ~5-10kb resolution = hundreds of millions to billions of valid pairs); consensus across callers and convergent-CTCF support as validation; and differential loops via union anchors plus chromosight quantify. Use when calling chromatin loops or dots from a cooler, deciding whether a map is deep enough to call de-novo vs running APA on known CTCF/cohesin anchors, building an aggregate peak pileup, comparing loops across conditions, or validating loop calls. For HiChIP/PLAC-seq/PCHi-C protein-anchored data use FitHiChIP/MAPS, not dots.
- 100/100
hi-c-analysis-matrix-operations
swaruplab/operon
Balances Hi-C contact matrices (ICE via cooler.balance_cooler, KR/SCALE/VC context), computes distance-decay expected with cooltools (expected_cis per-diagonal P(s), expected_trans scalar), builds observed/expected (O/E) matrices, and diagnoses polymer state from the P(s) log-derivative. Covers the within-matrix-vs-cross-sample distinction (balancing is NOT a normalizer), the equal-visibility assumption that CNV/aneuploidy violates (use raw counts for copy-number), cis-only balancing, mad_max/blacklist masking before balancing, multiplicative cooler weights vs divisive juicer weights, and the resolution-vs-depth budget. Use when balancing a .cool/.mcool, computing expected or P(s), making O/E matrices for compartments/loops, deciding ICE vs KR vs SCALE, choosing a resolution for a given depth, or troubleshooting NaN/all-NaN balanced matrices; route cross-sample comparison to hic-differential.
- 100/100
hi-c-analysis-tad-detection
swaruplab/operon
Detects TAD boundaries from balanced Hi-C contact matrices via the diamond-window insulation score (cooltools insulation) and HiCExplorer hicFindTADs, returning a continuous log2 insulation track, valley-prominence boundary_strength, and Li/Otsu-thresholded is_boundary flags across a list of window sizes. Covers the multi-scale window sweep (sub-TAD to compartment-domain), why the boundary is reproducible but the domain partition is not, cross-condition comparison via differential SCORE not differential partition, and the insulation-vs-compartment orthogonality. Use when calling TADs or domain boundaries, computing insulation scores, choosing a window size, ranking boundary strength, comparing boundaries across conditions, or annotating CTCF-backed boundaries; route domain rendering to hic-visualization and boundary-feature overlap to genome-intervals.
- 100/100
hierarchical-agent-memory
diegosouzapw/awesome-omni-skills
Hierarchical Agent Memory (HAM) workflow skill. Use this skill when the user needs Scoped CLAUDE.md memory system that reduces context token spend. Creates directory-level context files, tracks savings via dashboard, and routes agents to the right sub-context and the operator should preserve the upstream workflow, copied support files, and provenance before merging or handing off.
- 100/100
hig-components-content
raintree-technology/hig-doctor
>-
- 100/100
hig-components-content-v2
diegosouzapw/awesome-omni-skills
Apple HIG: Content Components workflow skill. Use this skill when the user needs Apple Human Interface Guidelines for content display components and the operator should preserve the upstream workflow, copied support files, and provenance before merging or handing off.
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