Agent skill

Browse And Evaluate

by MoizIbnYousaf in MoizIbnYousaf/ai-agent-skills

A skill your agent uses when exploring the ai-agent-skills catalog to find, compare, and evaluate skills before installing.

MITAuto-check passed

Install Browse And Evaluate

skills CLI
$ npx skills add MoizIbnYousaf/ai-agent-skills --skill browse-and-evaluate -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install MoizIbnYousaf/ai-agent-skills browse-and-evaluate --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/MoizIbnYousaf/ai-agent-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/browse-and-evaluate .claude/skills/browse-and-evaluate && rm -rf skills-src

Use ~/.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/

Facts

Skill name
browse-and-evaluate
GitHub stars
1.1k
Token cost
~453 tokens
SKILL.md length
160 words
Files
1
Skills in repo
15
Repo updated
First seen
Licence
MIT

At a glance

A skill your agent uses when exploring the ai-agent-skills catalog to find, compare, and evaluate skills before installing.

  • Works in 5 steps: Search or browse the catalog. → Get details on a candidate. → Preview the skill content. → …
  • Exploring the ai-agent-skills catalog to find
  • SKILL.md covers Goal, Guardrails, Workflow and Gotchas
  • Calls npx

What it does

Browse And Evaluate is an agent skill from MoizIbnYousaf/ai-agent-skills. Use when exploring the ai-agent-skills catalog to find, compare, and evaluate skills before installing. Always use --fields to limit output size and --dry-run before committing to an install.

Its SKILL.md is about 450 tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

The repository describes itself as: Universal skill installer and package manager for AI coding agents. One command, 12+ runtimes. npx ai-agent-skills. The licence is MIT.

When your agent uses it

  • Exploring the ai-agent-skills catalog to find
  • Evaluate skills before installing

Example prompts

  • “/browse-and-evaluate”

Requirements

  • Node.js

Workflow steps

5 steps, taken from the first numbered list in SKILL.md.

  1. Search or browse the catalog.
  2. Get details on a candidate.
  3. Preview the skill content.
  4. Dry-run the install.
  5. Install only after reviewing the dry-run output.

What it can do on your machine

Read from SKILL.md and the folder at commit 6d95c78. It shows what the files ask for, not the result of running them.

  • Tool permissions

    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.

  • Runs code

    Shell commands in SKILL.md call:

    • npx

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md. Its commands use npx, which can reach the network depending on how they are called.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Browse And Evaluate loads about 453 tokens when it runs. Until then it costs about 53 tokens; SKILL.md has 160 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~53
When it runs · the whole SKILL.md, loaded when a task matches
~453

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.

Safety

Auto-check passed

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.

SKILL.md

The full file from MoizIbnYousaf/ai-agent-skills at commit 6d95c78, republished under its MIT licence (© MoizIbnYousaf). 160 words, ~453 tokens.

Download SKILL.mdSave it as .claude/skills/browse-and-evaluate/SKILL.md (or your agent's skills folder).
name
browse-and-evaluate
description
Use when exploring the ai-agent-skills catalog to find, compare, and evaluate skills before installing. Always use --fields to limit output size and --dry-run before committing to an install.
category
workflow
version
4.1.0

Browse And Evaluate

Goal

Find the right skill for a task without flooding the context window or installing blindly.

Guardrails

  • Always use --fields on list/search/info to keep output small. Default: --fields name,tier,workArea,description.
  • Always use --dry-run before installing anything.
  • Never install more than 3 skills at once without explicit user confirmation.
  • Prefer --format json in non-interactive pipelines. The CLI defaults to JSON when stdout is not a TTY.
  • Use --limit when browsing large catalogs. Start with --limit 10.

Workflow

  1. Search or browse the catalog.
bash
npx ai-agent-skills search <query> --fields name,tier,workArea,description --limit 10
  1. Get details on a candidate.
bash
npx ai-agent-skills info <skill-name> --fields name,description,tags,collections,installCommands
  1. Preview the skill content.
bash
npx ai-agent-skills preview <skill-name>
  1. Dry-run the install.
bash
npx ai-agent-skills install <skill-name> --dry-run
  1. Install only after reviewing the dry-run output.
bash
npx ai-agent-skills install <skill-name>

Gotchas

  • The preview command sanitizes skill content to strip prompt injection patterns. If content looks truncated, check if suspicious patterns were removed.
  • Collection installs pull multiple skills. Always --list or --dry-run a collection before installing.
  • Upstream (non-vendored) skills require a network fetch at install time. Use --dry-run to verify the source is reachable.

© MoizIbnYousaf, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in skills/browse-and-evaluate of MoizIbnYousaf/ai-agent-skills.

Open the folder on GitHubat commit 6d95c78

Compare with similar skills

Browse And Evaluate 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.

Browse And Evaluate compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Browse And Evaluate this skillMoizIbnYousaf/ai-agent-skills1.1k—~453Automated safety check: PassMIT
Exploring LLM EvaluationsPostHog/posthog40k—~5.7kAutomated safety check: PassCustom licence
Explorersupabase/supabase111k—~845Automated safety check: PassApache-2.0
Arize Evaluatorgithub/awesome-copilot40k1 repos~8.1kAutomated safety check: NotesMIT
LLM Evaluationdavila7/claude-code-templates33k12 repos~3.5kAutomated safety check: PassMIT
Agent Evaluation Reportingsickn33/agentic-awesome-skills47k1 repos~2.1kAutomated safety check: PassMIT

Similar skills

  • Official

    Investigate AI observability evaluations — hog (deterministic code-based), llmjudge (LLM-prompt-based), and sentiment (user-message sentiment).

    40k GitHub stars~5.7k tokensUpdated yesterday
    AI & LLM EngineeringAuto-check passed
  • Explorer

    supabase/supabase

    Official

    Build and modify Studio Explorer surfaces, including notebooks, chats, SQL snippets, query cells, and their shared toolbar patterns.

    111k GitHub stars~845 tokensUpdated yesterday
    DatabasesAuto-check passed
  • Arize Evaluator

    github/awesome-copilot

    Official

    Handles LLM-as-judge evaluation workflows on Arize including creating/updating evaluators, running evaluations on spans or experiments, managing tasks, trigger-run operations, column mapping, and…

    40k GitHub starsUsed in 1 repo~8.1k tokens
    AI & LLM EngineeringAuto-check: notes
  • LLM Evaluation

    davila7/claude-code-templates

    Master comprehensive evaluation strategies for LLM applications, from automated metrics to human evaluation and A/B testing.

    33k GitHub starsUsed in 12 repos~3.5k tokens
    AI & LLM EngineeringAuto-check passed
  • Agent Evaluation Reporting

    sickn33/agentic-awesome-skills

    A skill your agent uses when summarizing agent evaluations where autonomous, assisted, failed, timed-out, or invalid outcomes must remain distinct and comparable.

    47k GitHub starsUsed in 1 repo~2.1k tokens
    Agent WorkflowsAuto-check passed
  • Agent Evaluation

    sickn33/agentic-awesome-skills

    Evaluate agent behavior with versioned cases and explicit verifiers.

    47k GitHub starsUsed in 1 repo~2k tokens
    Agent WorkflowsAuto-check passed

More from MoizIbnYousaf/ai-agent-skills

All 15 skills in this repo
  • Database Design

    MoizIbnYousaf/ai-agent-skills

    Database schema design, optimization, and migration patterns for PostgreSQL, MySQL, and NoSQL databases.

    1.1k GitHub starsUsed in 1 repo~1.2k tokens
    Auto-check passed
  • LLM Application Dev

    MoizIbnYousaf/ai-agent-skills

    Building applications with Large Language Models - prompt engineering, RAG patterns, and LLM integration.

    1.1k GitHub starsUsed in 1 repo~1.3k tokens
    Auto-check passed
  • Audit Library Health

    MoizIbnYousaf/ai-agent-skills

    A skill your agent uses when checking the overall health of a skills library.

    1.1k GitHub stars~518 tokensUpdated 19 days ago
    Auto-check passed
  • Backend Development

    MoizIbnYousaf/ai-agent-skills

    Backend API design, database architecture, microservices patterns, and test-driven development.

    1.1k GitHub stars~853 tokensUpdated 19 days ago
    Auto-check passed
  • Code Documentation

    MoizIbnYousaf/ai-agent-skills

    Writing effective code documentation - API docs, README files, inline comments, and technical guides.

    1.1k GitHub stars~1.4k tokensUpdated 19 days ago
    Auto-check passed
  • Curate A Team Library

    MoizIbnYousaf/ai-agent-skills

    A skill your agent uses when building a managed team skills library for a real stack.

    1.1k GitHub stars~973 tokensUpdated 19 days ago
    Auto-check passed

Questions about Browse And Evaluate

What does Browse And Evaluate do?

A skill your agent uses when exploring the ai-agent-skills catalog to find, compare, and evaluate skills before installing. Browse And Evaluate is an agent skill from MoizIbnYousaf/ai-agent-skills. Use when exploring the ai-agent-skills catalog to find, compare, and evaluate skills before installing.

When should I use Browse And Evaluate?

Browse And Evaluate fits situations like: exploring the ai-agent-skills catalog to find; evaluate skills before installing.

How do I install Browse And Evaluate in Claude Code?

Run `npx skills add MoizIbnYousaf/ai-agent-skills --skill browse-and-evaluate -a claude-code`. Or copy the skill folder (skills/browse-and-evaluate in MoizIbnYousaf/ai-agent-skills) into .claude/skills/browse-and-evaluate in your project. Claude Code loads it when a task matches its description.

How do I install Browse And Evaluate in Codex?

Run `npx skills add MoizIbnYousaf/ai-agent-skills --skill browse-and-evaluate -a codex`. Or copy the skill folder (skills/browse-and-evaluate in MoizIbnYousaf/ai-agent-skills) into .agents/skills/browse-and-evaluate in your project. Codex loads it when a task matches its description.

Can I use Browse And Evaluate in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add MoizIbnYousaf/ai-agent-skills --skill browse-and-evaluate -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/browse-and-evaluate, .gemini/skills/browse-and-evaluate, .github/skills/browse-and-evaluate and .opencode/skills/browse-and-evaluate in your project.

What does Browse And Evaluate need to run?

Going by SKILL.md and its folder, Browse And Evaluate needs the command-line tools its instructions call (npx). Our summary lists: Node.js.

Does Browse And Evaluate access the network?

SKILL.md contains no URLs. Its commands use npx, which can reach the network depending on how they are called. This is read from the text; nothing was executed.

Is Browse And Evaluate safe to install?

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.

What licence does Browse And Evaluate use?

Browse And Evaluate is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Browse And Evaluate use?

About 453 tokens (SKILL.md is roughly 1.8k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Browse And Evaluate?

Skills that share tags, products or a category with Browse And Evaluate: Exploring LLM Evaluations (PostHog/posthog, 40k stars), Explorer (supabase/supabase, 111k stars), Arize Evaluator (github/awesome-copilot, 40k stars) and LLM Evaluation (davila7/claude-code-templates, 33k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Browse And Evaluate?

MoizIbnYousaf (a GitHub user) maintains it in MoizIbnYousaf/ai-agent-skills, which has 1,149 GitHub stars. The repository holds 15 skills in this directory. The repository was last updated on September 21, 2026.

Source: MoizIbnYousaf/ai-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.