Bkit Explore
ww-w-ai/bkit-claude-code
Browse installed bkit skills, agents, and evals via lib/discovery/explorer.js (filesystem scan, no subprocess).
A skill your agent uses when creating, reviewing, or editing Agent Skills-format skills, or when implementing skill discovery and loading in an agent client.
$ npx skills add magnus919/agent-skills --skill agent-skills -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install magnus919/agent-skills agent-skills --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/magnus919/agent-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/agent-skills .claude/skills/agent-skills && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "agent-skills" agent skill from https://github.com/magnus919/agent-skills/tree/main/agent-skills into .claude/skills/agent-skills/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "agent-skills", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/magnus919/agent-skills/tree/main/agent-skillsType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add magnus919/agent-skills --skill agent-skills -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install magnus919/agent-skills agent-skills --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/magnus919/agent-skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/agent-skills .agents/skills/agent-skills && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "agent-skills" agent skill from https://github.com/magnus919/agent-skills/tree/main/agent-skills into .agents/skills/agent-skills/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "agent-skills", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add magnus919/agent-skills --skill agent-skills -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install magnus919/agent-skills agent-skills --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/magnus919/agent-skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/agent-skills .cursor/skills/agent-skills && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "agent-skills" agent skill from https://github.com/magnus919/agent-skills/tree/main/agent-skills into .cursor/skills/agent-skills/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "agent-skills", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/magnus919/agent-skills.git --path agent-skills--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add magnus919/agent-skills --skill agent-skills -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install magnus919/agent-skills agent-skills --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/magnus919/agent-skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/agent-skills .gemini/skills/agent-skills && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "agent-skills" agent skill from https://github.com/magnus919/agent-skills/tree/main/agent-skills into .gemini/skills/agent-skills/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "agent-skills", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install magnus919/agent-skills agent-skillsInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add magnus919/agent-skills --skill agent-skills -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/magnus919/agent-skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/agent-skills .github/skills/agent-skills && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "agent-skills" agent skill from https://github.com/magnus919/agent-skills/tree/main/agent-skills into .github/skills/agent-skills/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "agent-skills", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add magnus919/agent-skills --skill agent-skills -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install magnus919/agent-skills agent-skills --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/magnus919/agent-skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/agent-skills .opencode/skills/agent-skills && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "agent-skills" agent skill from https://github.com/magnus919/agent-skills/tree/main/agent-skills into .opencode/skills/agent-skills/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "agent-skills", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
agent-skillsA skill your agent uses when creating, reviewing, or editing Agent Skills-format skills, or when implementing skill discovery and loading in an agent client.
Agent Skills is an agent skill from magnus919/agent-skills. Use this skill when creating, reviewing, or editing Agent Skills-format skills, or when implementing skill discovery and loading in an agent client. It covers directory structure, SKILL.md metadata, progressive disclosure, evals, and repository conventions. Do not use this skill for general software work that does not involve the Agent Skills format or lifecycle.
Its SKILL.md is about 3k tokens, which your agent loads only when the skill is triggered. The skill folder holds 13 other files, including reference files (for example `README.md`, `evals/evals.json` and `references/best-practices.md`).
It sits in AI & LLM Engineering, covering LLM evaluation and Skill management. The repository describes itself as: Curated collection of AI agent skills for Hermes and other agent frameworks. The licence is MIT.
7 steps, taken from the first numbered list in SKILL.md.
Read from SKILL.md and the folder at commit 22b4723. It shows what the files ask for, not the result of running them.
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Shell commands in SKILL.md call:
rubyFrom the folder's file list and the shell code blocks in SKILL.md.
Links to these hosts (documentation or services it may open):
agentskills.iogithub.comFrom URLs in SKILL.md, links to its own repository left out.
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Agent Skills loads about 3k tokens when it runs, and up to ~34k if it reads all its reference files. Until then it costs about 95 tokens; SKILL.md has 1,455 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
The full file from magnus919/agent-skills at commit 22b4723, republished under its MIT licence (© magnus919). 1,455 words, ~3,024 tokens.
.claude/skills/agent-skills/SKILL.md (or your agent's skills folder). This skill also uses 11 other files; get the full folder from GitHub.This skill documents the Agent Skills open format — a standardized way to give AI agents new capabilities and expertise. Follow this workflow when creating or editing skills in this repository.
Authoritative source: agentskills.io/specification. The bundled specification is a working snapshot; check the authoritative source when currentness matters.
A skill is a directory containing, at minimum, a SKILL.md file:
skill-name/
├── SKILL.md # Required: metadata + instructions
├── evals/ # Required for new skills in this repository
├── scripts/ # Optional: executable code
├── references/ # Optional: documentation
├── assets/ # Optional: templates, resources
└── ... # Any additional files or directoriesSKILL.md metadata or directory structure.SKILL.md; put conditional detail in focused reference files and state exactly when to read each one.description that says what the skill does, when it applies, and when it does not apply. For skills with meaningful overlap, name the nearest alternative or prerequisite in a ## When not to use section. Test the boundary with at least three should-trigger prompts and two should-not-trigger near-misses; keep these harness-specific trigger checks separate from portable output-quality evals. Read optimizing descriptions for trigger design.evals/evals.json with at least five representative output-quality cases. Each case needs a realistic prompt, an expected outcome, and observable assertions. Include edge cases that exercise risky or ambiguous behavior. Read evaluating skills for the eval format and iteration workflow.README.md: title, Why Install This Skill, What You Get, Quick Start (unless genuinely reference-only), Triggers, and Requirements. Keep it human-facing, concise, and free of agent-only instructions.evals/evals.json with at least five output-quality cases, and check that their expected outcomes and assertions test meaningful behavior. For an existing skill without evals, flag the gap but do not block the review solely for that legacy absence. Read evaluating skills before declaring the work complete.When implementing skill discovery, activation, or context management in an agent product, read client implementation guidance. Do not apply client conventions such as search paths as universal format requirements.
The SKILL.md file must contain YAML frontmatter followed by Markdown body content.
| Field | Required | Constraints |
|---|---|---|
name | Yes | Max 64 chars. Lowercase letters, numbers, and hyphens only. Must not start or end with a hyphen. Must match the parent directory name. |
description | Yes | Max 1024 chars. Non-empty. Describes what the skill does and when to use it. |
license | No | License name or reference to a bundled license file. |
compatibility | No | Max 500 chars. Indicates environment requirements. |
metadata | No | Arbitrary key-value mapping. |
allowed-tools | No | Space-separated string of pre-approved tools. (Experimental) |
name field rulesa-z, 0-9) and hyphens (-)--)description field rulescompatibility field rulesmetadata field rulesThe Markdown body has no format restrictions beyond being helpful to the agent. Recommended sections:
Keep SKILL.md under 500 lines and 5000 tokens. Move detailed reference material to separate files in references/.
Agents load skills in three stages:
name and description loaded at startup for all skillsSKILL.md loaded when activatedscripts/, references/, assets/ loaded on demandscripts/Executable code agents can run. Scripts should:
scripts/extract.py)references/Additional documentation loaded on demand. Keep individual files focused — agents load these when instructed, so smaller files save context.
references/ must be at or under 60,000 characters. When a reference grows past the cap, split it into focused files (e.g., references/<topic>-a.md, references/<topic>-b.md) and update SKILL.md so each new file is reachable and the load-on-demand instructions name the right file.assets/Static resources: templates, images, data files, schemas.
evals/Portable output-quality cases for the skill. New skills in this repository must include evals/evals.json with at least five cases; trigger-only checks belong in the harness-specific test set instead of this file.
Use relative paths from the skill root when referencing other files:
See [the specification](references/specification.md) for details.
Run a bundled script:
scripts/<script-name>Keep file references one level deep from SKILL.md. Avoid deeply nested reference chains.
The description field is the primary mechanism for automatic skill selection. Clients can also support explicit activation. Follow these principles:
Feed domain-specific context into skill creation. Skills grounded in real project artifacts (runbooks, API specs, code review comments, actual failure cases) outperform ones synthesized from generic knowledge.
Focus on what the agent wouldn't know without the skill: project-specific conventions, domain-specific procedures, non-obvious edge cases. Don't explain general concepts the agent already knows.
scripts/ over instructions the agent improvises on each run. A test only catches what you already thought to check; a script takes the guess out of the loop entirelyScope skills like functions: one coherent unit of work that composes well with other skills. Too narrow → multiple skills needed for one task. Too broad → hard to activate precisely.
The highest-value content is often environment-specific corrections — things the agent will get wrong unless told otherwise. When an agent makes a mistake, add the correction to the gotchas section.
When output needs a specific format, provide a template inline or in assets/. Agents pattern-match well against concrete structures.
Skills are executable capability: when a skill activates, its instructions and scripts run with the agent's permissions — shell access, file system, and credentials. Before running a skill you did not author (from a registry, a colleague, or an LLM generation), read vetting third-party skills and treat it like any other dependency: inspect provenance, read the body and every script, and check what the skill reaches out to.
Use the skills-ref reference library to validate skills:
skills-ref validate ./my-skillThis checks that SKILL.md frontmatter is valid and follows all naming conventions.
For this repository, also run the bundled whole-repository checker:
ruby scripts/validate-skills.rbIt checks canonical top-level and bundle skills for frontmatter, supported fields, line limits, local links, and required README sections. Vendored profile skills under agent-council/profiles/skills/ are intentionally excluded because they follow the source repository's conventions.
If skills-ref is unavailable, do not claim a successful validator run. Perform and report the equivalent structural checks manually, or install and run the reference validator when the task permits it.
© magnus919, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
SKILL.md and 11 other files (references) in agent-skills of magnus919/agent-skills.
Open the folder on GitHubat commit 22b4723
Agent Skills next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Agent Skills this skillmagnus919/agent-skills | 115 | — | ~3k | Automated safety check: Pass | MIT | |
| Bkit Exploreww-w-ai/bkit-claude-code | 601 | — | ~1.1k | Automated safety check: Pass | Apache-2.0 | |
| LLM Benchmarking with lm-evaluation-harnessOrchestra-Research/AI-Research-SKILLs | 13k | 8 repos | ~3k | Automated safety check: Pass | MIT | |
| Hugging Face Local Model Evalshuggingface/skills | 11k | 2 repos | ~1.6k | Automated safety check: Pass | Apache-2.0 | |
| Looperksimback/looper | 710 | — | ~2.7k | Automated safety check: Notes | MIT | |
| Agent Eval Engineeringlangchain-ai/langchain-skills | 1.3k | — | ~4k | Automated safety check: Pass | MIT |
ww-w-ai/bkit-claude-code
Browse installed bkit skills, agents, and evals via lib/discovery/explorer.js (filesystem scan, no subprocess).
Orchestra-Research/AI-Research-SKILLs
Runs lm-evaluation-harness to benchmark language models on academic suites such as MMLU, GSM8K and HumanEval, compare models and track training checkpoints.
huggingface/skills
Runs evaluations of Hugging Face Hub models on local hardware with inspect-ai or lighteval, and helps choose between vLLM, Transformers and accelerate backends.
ksimback/looper
Scaffold a well-designed agent loop with best-practice coaching and a cross-model review council.
langchain-ai/langchain-skills
Builds agent evaluations in stages: inspect the repository and traces, agree a Task Spec with you, then build, audit and run a Harbor task with an independent verifier.
GoogleCloudPlatform/vertex-ai-samples
Evaluate and improve GenAI models and agents using the Google GenAI Evaluation SDK.
magnus919/agent-skills
Organize durable agent research outputs as summaries, analysis, and evidence dossiers.
magnus919/agent-skills
Build portable, first-person colored ASCII city engines and small GIS-derived city packs.
magnus919/agent-skills
Manage color workflows with ICC profiles, working spaces, gamut mapping, and color science.
magnus919/agent-skills
A skill your agent uses for PhD-level expertise in data science, statistics, and machine learning: rigorous statistical analysis, experimental design, causal inference, advanced modeling, research…
magnus919/agent-skills
Use Docker Compose to define, run, debug, and harden multi-container applications.
magnus919/agent-skills
Design, review, simulate, and verify FPGA logic using explicit RTL contracts, clock and reset models, CDC analysis, timing constraints, and reproducible implementation evidence.
Categories
A skill your agent uses when creating, reviewing, or editing Agent Skills-format skills, or when implementing skill discovery and loading in an agent client. Agent Skills is an agent skill from magnus919/agent-skills. Use this skill when creating, reviewing, or editing Agent Skills-format skills, or when implementing skill discovery and loading in an agent client.
Agent Skills fits situations like: editing Agent Skills-format skills; implementing skill discovery and loading in an agent client; general software work that does not involve the Agent Skills format.
Run `npx skills add magnus919/agent-skills --skill agent-skills -a claude-code`. Or copy the skill folder (agent-skills in magnus919/agent-skills) into .claude/skills/agent-skills in your project. Claude Code loads it when a task matches its description.
Run `npx skills add magnus919/agent-skills --skill agent-skills -a codex`. Or copy the skill folder (agent-skills in magnus919/agent-skills) into .agents/skills/agent-skills in your project. Codex loads it when a task matches its description.
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add magnus919/agent-skills --skill agent-skills -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/agent-skills, .gemini/skills/agent-skills, .github/skills/agent-skills and .opencode/skills/agent-skills in your project.
Going by SKILL.md and its folder, Agent Skills needs the command-line tools its instructions call (ruby).
SKILL.md names 2 domains. As links in the text: agentskills.io and github.com. This is read from the text; nothing was executed.
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.
Agent Skills is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.
About 3k tokens (SKILL.md is roughly 12k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 31k tokens, read only when the agent opens those files.
Skills that share tags, products or a category with Agent Skills: Bkit Explore (ww-w-ai/bkit-claude-code, 601 stars), LLM Benchmarking with lm-evaluation-harness (Orchestra-Research/AI-Research-SKILLs, 13k stars), Hugging Face Local Model Evals (huggingface/skills, 11k stars) and Looper (ksimback/looper, 710 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
magnus919 (a GitHub user) maintains it in magnus919/agent-skills, which has 115 GitHub stars. The repository holds 131 skills in this directory. The repository was last updated on October 10, 2026.
Source: magnus919/agent-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.