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
9,019 results · page 144 of 301
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config-syncSkillAI & models
Sync configuration changes across the settings-opencode repo and live harness directories (OpenCode and Claude Code). Invoke when adding, updating, or removing agents, rules, hooks, commands, prompts, skills, or harness config. Keywords: "add agent", "change rule", "update skill", "modify config", "
Ready to connect★ 172
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harness-paritySkillAI & models
Use whenever you add, edit, rename, or delete any harness artifact — a skill, agent, command, rule, or instruction — in either .claude/ or .opencode/. Replicate the equivalent change in the other harness with the correct frontmatter and registration translation, so the two trees stay in parity.
Ready to connect★ 172
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strategic-compactSkillAI & models
Make compaction safe for fully autonomous multi-phase work. The agent prepares durable state so auto-compaction never requires user input and never breaks flow.
Ready to connect★ 172
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skill-conductorSkillAI & models
Create, edit, evaluate, and package agent skills. Use when building a new skill from scratch, improving an existing skill, fixing a skill that never triggers or fires unreliably, running evals to test a skill, benchmarking skill performance, optimizing a skill's description, reviewing third-party sk
Ready to connect★ 170
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habit-hooks-promptingSkillAI & models
Write or revise a habit-hooks coaching prompt. Use when a linter / knip / jscpd rule fires and the agent's default fix is wrong or shallow, or when adding a project-local override prompt. Keeps prompts short and outcome-focused using the ROSE pattern.
Ready to connect★ 170
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wioSkillAI & models
Testing workflow skill for finding high-value test candidates, writing focused tests, generating realistic workloads, reviewing test value, and diagnosing test-suite health. Use for prompts about what to test next, adding or improving tests, reviewing whether a test is worth keeping, low-signal or f
Ready to connect★ 170
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blue-teamSkillAI & models
Use when the user has concrete failing cases in code or a guardrail/classifier/filter/prompt/API they own — a red-team failure catalogue OR a CI/CD test-failure report (failing pytest/JUnit tests) — and wants the target patched until those failures are closed without breaking what already works. It
Ready to connect★ 169
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hypothesis-genSkillAI & models
Use when the user wants to generate and literature-vet a pool of novel, testable research hypotheses for a question or domain. A multi-agent loop: a Generator proposes candidate hypotheses, a LiteratureScout grounds each in real retrieved literature (already known? closest prior work? what gap does
Ready to connect★ 169
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ml-autoresearchSkillAI & models
Use when the user wants an autonomous ML research loop that does more than blindly try changes. After every training run the agent analyses what actually happened inside the model — gradients, activations, embeddings, errors, data — and grounds the next change in that evidence. A `<literature>` on/o
Ready to connect★ 169
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plan-loopSkillAI & models
Use when the user has a coding or engineering prompt and wants it refined into a detailed, executable plan before any code is written — the planning stage of a prompt → plan → execute → debug pipeline. It decomposes the prompt from first principles (objective, end state, environment, building blocks
Ready to connect★ 169
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power-analysisSkillAI & models
Use when the user is planning a two-arm comparison (an A/B test, a simple RCT, a behavioral study, or a two-model/two-config evaluation) and needs to size it and preregister it before collecting data — finding the per-group sample size that hits target statistical power for the smallest effect worth
Ready to connect★ 169
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prompt-optimizeSkillAI & models
Use when the user has a prompt that feeds a system they can already score, and wants that prompt automatically improved to raise the score against their own evaluation command. Makes one targeted quality edit per iteration — clarity, context, specificity, structure, examples, decomposition, guardrai
Ready to connect★ 169
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purple-teamSkillAI & models
Use when the user wants to automatically harden a guardrail, classifier, content filter, prompt, or API they own by running attack and defense together as a closed loop, not just one or the other. It orchestrates the red-team and blue-team loops as independent agents: red finds distinct failure clas
Ready to connect★ 169
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research-proposalSkillAI & models
Use when the user has a research proposal (problem + proposed methodology + planned experiments) and wants it iteratively strengthened until it clears a passing grade. ScholarEval grades the proposal against the literature (Soundness + Contribution), a Judge scores that feedback 0-100 on a fixed rub
Ready to connect★ 169
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research-questionSkillAI & models
Use when the user has a vague topic or area of interest and wants it sharpened into a few strong, novel, feasible research questions. Drafts candidate questions, scores each against a fixed rubric (Specific, Answerable, Novel, Feasible, Significant) with a light literature/web novelty check, and rev
Ready to connect★ 169
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scientific-figureSkillAI & models
Use when the user has scientific data (or a prompt alluding to scientific data) and wants a publication-quality figure made from it. A generator drafts and renders a figure that lands a frozen communication goal; an adversarial critic critiques it hard and grades it 1-5 per axis against a fixed rubr
Ready to connect★ 169
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tournament-autoresearchSkillAI & models
Use when the user wants an autonomous ML research loop that pressure-tests competing ideas before spending compute — several research subagents each propose one architecture change, a self-calibrating Judge critiques them against a rubric, the proposers refine, and the Judge picks the single change
Ready to connect★ 169
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codebase-intelSkillAI & models
Unified codebase intelligence. Handles all questions about structure, logic, risk, and dependencies. Combines natural-language Q&A with deterministic lookups and pre-edit blast radius checks.
Ready to connect★ 168
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module-audit-agentSkillAI & models
Use when asked to audit a module, check its health, or assess whether it should be refactored. Runs structural query, risk check, and test generation automatically.
Ready to connect★ 168
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onboard-dev-agentSkillAI & models
Use when a dev is new to the project, asks for an overview, or wants to get oriented quickly. Fills graph gaps then runs a guided codebase interview.
Ready to connect★ 168
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skill-generalizerSkillAI & models
Use when turning local, private, or personal Agent Skills into publishable skills for GitHub, marketplaces, teams, or public sharing, especially when private paths, personal habits, credentials, internal hosts, or user-specific context must be removed.
Ready to connect★ 167
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skill-minerSkillAI & models
Use when mining coding-agent session history, archived transcripts, memories, or repeated local work to discover recurring workflows that should become new Agent Skills.
Ready to connect★ 167
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skill-personalizerSkillAI & models
Use when auditing or adapting newly created, downloaded, forked, installed, or community Agent Skills to the user's tools, habits, directories, session history, and preferred workflows, especially when triggers feel wrong, noisy, or too generic.
Ready to connect★ 167
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disease-reversal-predictionSkillAI & models
Predict a molecule's ability to reverse disease states using DLEPS (Disease-Ligand Embedding Projection Score) for drug repositioning and discovery.
Ready to connect★ 167
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forward-implementation-firstSkillAI & models
Keeps an agent building and validating real output instead of servicing its own bookkeeping. Use for multi-stage pipelines, capability roadmaps, long-running implementation loops, migrations, staged data or build runs, and any run where administrative hashes, locks, receipts, dashboards, certificati
Ready to connect★ 166
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quark-skill-creatorSkillAI & models
Author or restructure a Quark Agent Skill so it conforms to this project's template, contracts, and layer rules. Use when a maintainer says "create a new skill", "add a skill for X", "scaffold a skill", "draft a SKILL.md", or when an existing skill needs a structural rewrite to match the format cont
Ready to connect★ 166
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quark-torch-eval-runnerSkillAI & models
Manually verify that the Quark Agent Skills system behaves correctly across the four contract categories (routing, planning, artifact, recovery). Use when maintainers need to confirm that routing, planning, artifact generation, or error recovery skills still work as expected. Trigger for "verify the
Ready to connect★ 166
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quark-torch-exportSkillAI & models
Prepare export and downstream evaluation handoff for a planned or completed Quark Torch PTQ run. Input is a PyTorch / HuggingFace transformers model; output formats include HF safetensors, GGUF, and ONNX. Trigger for "export model", "save quantized model", "convert to GGUF", "export to HuggingFace f
Ready to connect★ 166
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quark-torch-llm-ptq-evalSkillAI & models
End-to-end Torch LLM PTQ recipe for AMD Quark — for PyTorch / HuggingFace transformers models (safetensors input): quantize, then validate, then evaluate accuracy, in one flow. Delegates the PTQ path (intake, planning, manifest, execution) to the quark-torch-ptq workflow, runs mandatory structural v
Ready to connect★ 166
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.
54,764 of the 55,196 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.