Skills.
Give your AI a better way to work.
A skill is a set of written instructions that teaches an AI how to do one job the way it should be done: review a pull request, plan a migration, write the release notes.
Install one here and it travels with your account into Claude, Claude Code, Cursor and every other client you sign in with.
Category: AI & models
8,898 results · page 118 of 297
- View details
meta-ads-optimizerSkillAI & models
Audits and rewrites Meta (Facebook/Instagram) ad campaigns: structure, audiences, creatives, CBO, attribution. Use when the user asks for meta ads optimizer work, or mentions meta, ads, optimizer.
Ready to connect★ 307
- View details
od-gsap-coreSkillAI & models
Core GSAP API with gsap.to(), from(), fromTo(), easing, duration, stagger, and defaults Use when the user asks for gsap core work, or mentions od, gsap, core.
Ready to connect★ 307
- View details
pcap-triage-analystSkillAI & models
Triages a packet capture summary, surfaces suspicious flows and IOCs, names the likely technique, and recommends the next investigative step. Use when the user asks for pcap triage analyst work, or mentions pcap, triage, analyst.
Ready to connect★ 307
- View details
prompt-injection-testerSkillAI & models
Designs adversarial prompts and red-team scenarios to probe LLM applications for prompt injection, data exfiltration and jailbreak weaknesses, then scores the results. Use when the user asks for prompt-injection & llm robustness tester work, or mentions prompt, injection, tester.
Ready to connect★ 307
- View details
rag-system-architectSkillAI & models
Designs production retrieval-augmented generation systems: chunking, embeddings, vector store, reranking, eval. Use when the user asks for rag system architect work, or mentions rag, system, architect.
Ready to connect★ 307
- View details
recon-attack-surfaceSkillAI & models
Plans and runs authorized reconnaissance to enumerate a target's external attack surface (DNS, subdomains, ports, web tech) and produces a prioritized report. Use when the user asks for recon & attack surface mapper work, or mentions recon, attack, surface.
Ready to connect★ 307
- View details
integrate-with-yalcSkillAI & models
Points at the user's existing Claude Code repo, analyses what's already there, and produces a plan for how to make it work alongside YALC without conflicts. Covers workspace layout, skill trigger collisions, context migration, and orchestration examples. Read-only by default — a separate apply step
Ready to connect★ 304
- View details
deidentifySkillAI & models
De-identify clinical research data before LLM-assisted analysis. Standalone Python CLI detects PHI via regex + heuristics with 10 country locale packs (kr, us, jp, cn, de, uk, fr, ca, au, in). Interactive terminal review. No LLM touches raw data — the script runs locally without any network or AI ca
Ready to connect★ 300
- View details
explainabilitySkillAI & models
Produce or audit the interpretability/explainability analysis of a medical-imaging model — Grad-CAM / Grad-CAM++ / attention-rollout / saliency / integrated-gradients — so it clears the rigor bar a reviewer expects: mandatory Adebayo sanity checks (model- and data-randomisation), a quantitative loca
Ready to connect★ 300
- View details
orchestrate:precommitSkillAI & models
Add pre-commit hooks, linting, CLAUDE.md, and foundational .claude/ setup to a target repo
Ready to connect★ 302
- View details
publish-skillSkillAI & models
Convert a personal agent skill into a distributable, open-source-ready skill. Runs PII audit, generalization, license compatibility check, cross-platform adapter review, and packaging workflow.
Ready to connect★ 300
- View details
session:postSkillAI & models
Post Claude Code session stats to a GitHub PR or issue comment
Ready to connect★ 302
- View details
setup-medsciSkillAI & models
Diagnostic checklist for the MedSci Skills runtime. Verifies Python, R, Node, Claude Code, Git, Zotero, and configured MCP servers, and prints a pass/fail table with links to the right setup doc for any missing component. Read-only — does not install anything.
Ready to connect★ 300
- View details
skillsSkillAI & models
Skill management - create, validate, and improve Claude Code skills
Ready to connect★ 302
- View details
causalSkillAI & models
Causal inference toolkit for when experiments are not possible: estimate treatment effects from observational data with assumption checks and mandatory caveats. Invoke as /causal. Trigger on "causal", "caused", "impact of", "effect of", "attribution", "counterfactual", "difference-in-differences", "
Ready to connect★ 299
- View details
evaluate-graderSkillAI & models
Compare a narrow model grader with frozen human labels and inspect disagreement, bias probes, and repeated scoring stability. Use when building or changing a model-based evaluator.
Ready to connect★ 299
- View details
paceSkillAI & models
Change how visibly Claude surfaces analytical work during L3+ analyses. Three modes — guided (announce each phase and pause for /continue), narrated (announce each phase and run end-to-end), autopilot (silent end-to-end, final output only). Use this skill whenever the user invokes `/pace`, `/pace gu
Ready to connect★ 299
- View details
ai-productSkillAI & models
Every product will be AI-powered. The question is whether you'll build it right or ship a demo that falls apart in production. This skill covers LLM integration patterns, RAG architecture, prompt ...
Ready to connect★ 297
- View details
autonomous-agentsSkillAI & models
Autonomous agents are AI systems that can independently decompose goals, plan actions, execute tools, and self-correct without constant human guidance. The challenge isn't making them capable - it'...
Ready to connect★ 297
- View details
avalonia-viewmodels-zafiroSkillAI & models
Optimal ViewModel and Wizard creation patterns for Avalonia using Zafiro and ReactiveUI.
Ready to connect★ 297
- View details
analyze-training-run-irisSkillAI & models
Detailed health check for a Levanter/executor TRAINING run on the marin Iris cluster (e.g. the delphi midtraining runs) — step progress vs target, loss/throughput, preemption + MAJOR step-gap detection, and checkpoint cadence. Use for an executor coordinator (`<run>-coord`) plus its nested `<run>-co
Ready to connect★ 294
- View details
crud-purge-below-gate-evalsSkillAI & models
Guardrailed DELETE of auto-registered eval `sandbox_jobs` rows that DID score but FAILED the harvest gate — partial evals (valid-complete <90% or non-benign infra-error >10%). These are the "DE-REGISTER candidate" rows the flawed_summ harvest defers. DISTINCT from `crud-purge-stale-eval-placeholders
Ready to connect★ 294
- View details
eval-agentic-cleanupSkillAI & models
Audit + recover a finished agentic eval. ALWAYS start with the read-only, idempotent completeness/health audit (§0): job finished? score present + non-zero + not obviously broken? HF traces present + linked? trial count ≈ n_rep × benchmark_size? — it writes nothing and recommends an action per check
Ready to connect★ 294
- View details
eval-agentic-launchSkillAI & models
Launch agentic Harbor evals through the OT-Agent unified eval listener (eval/unified_eval_listener.py) on any cluster: select models (query_unevaled_models.py / priority lists), wire the pinggy served-model tunnel, submit with the right preset + flags in tmux, then VERIFY the launch actually works v
Ready to connect★ 294
- View details
eval-standard-cleanupSkillAI & models
Consolidate FINISHED standard / lm_eval (evalchemy) math-suite eval jobs — the Delphi #6279 MATH-500 / AIME24 / gsm8k grid launched via eval-standard-launch — into the SCORES.md tracker. Per job: confirm a NON-EMPTY seed42 result (a crash leaves it empty — don't record it as a score), rsync the resu
Ready to connect★ 294
- View details
eval-standard-launchSkillAI & models
Launch the fixed Delphi #6279 RL-scaling-laws downstream MATH eval suite (MATH-500 / AIME24 / gsm8k via evalchemy + lm_eval) on CINECA Leonardo, for completed SFT / RL / base checkpoints. Covers finding which cells are newly-completed-but-uneval'd, the offline pre-download, the delphi_eval.sbatch in
Ready to connect★ 294
- View details
rl-agentic-job-cleanupSkillAI & models
Preserve + publish a finished RL (SkyRL/GRPO) training checkpoint after the job terminates (completed at max_steps OR early-stopped/scancelled) on an HPC cluster (Jupiter/Leonardo/Perlmutter). Covers: cancel pending retries, pick the BEST checkpoint by trailing-5 EMA of reward across the full restar
Ready to connect★ 294
- View details
rl-agentic-launch-jupiterSkillAI & models
Launch / relaunch agentic RL (SkyRL terminal_bench + Harbor + Daytona) on JSC Jupiter (GH200). Covers the dense 8B/32B FSDP2 arms (seqnorm, TIS, shaped, symclip, lrboost, loopshape) and the MoE/80B Megatron arms (Qwen3-Coder-30B-A3B, Qwen3-Next-80B-A3B) — the exact `python -m hpc.launch --job_type r
Ready to connect★ 294
- View details
rl-standard-job-cleanupSkillAI & models
Preserve + publish a finished STANDARD (non-agentic GRPO) SkyRL RL checkpoint — the Delphi/rlvr/dapo math-and-reasoning cells launched via rl-standard-launch-leonardo (raw sbatch of hpc/skyrl_standard/leonardo/*, logger=console, NO Harbor/Daytona/trace_jobs). Covers: cancel pending retries, pick the
Ready to connect★ 294
- View details
sft-launchSkillAI & models
Launch SFT via `python -m hpc.launch --job_type sft` on any cluster (JSC Jupiter GH200, CINECA Leonardo A100, TACC Vista GH200), with EITHER backend — LLaMA-Factory (default) or axolotl (`--sft_backend axolotl`) — including Delphi tool-calling models (delphi template, tokenizer prep, jinja-as-ground
Ready to connect★ 294
What is a skill?
A skill is plain text, usually a SKILL.md file and the scripts it refers to, written for an AI rather than for a person. It carries the steps, the house rules and the examples a good answer needs, so you stop pasting the same briefing into every new chat.
53,789 of the 54,221 skills listed here can be served through ahel today, and they come from public repositories. Each one has its own page with the instructions themselves on it, so you can read what a skill will tell your AI to do before you install it.
Install one and every AI you use gets it
Installing a skill adds it to your gateway and turns it on in the same step. Claude Code surfaces it as a slash command; any client can read the full instructions with the skill_read tool.
Nothing is copied into a project folder. The instructions are served from your account, so the same skill is there in every AI you connect, and turning it off removes it from all of them at once.