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You use Claude Code or Cursor. This tutorial installs one skill from the public registry — a skill with a measured, verified benchmark, not just stars — and shows it firing in your next session. No account, no SDK, no API key, under 5 minutes. A skill is a SKILL.md file: instructions your agent reads when a matching task comes up (a triage policy, an extraction schema, a commit-message convention). It’s an open format your runtime already understands — DecimalAI’s registry adds the part no file format can: evidence that the skill actually works.
1

Read the scorecard (1 minute)

Open the skill’s public page — no login:app.decimal.ai/skills/playwright-cliBefore installing anything, read the two surfaces that make this registry different:
  • Verified lift — at the time of writing: +79 points. With the skill loaded the benchmark agent passed 24 of 24 cases; without it, about 21% (5 of 24). That’s a with-vs-without A/B run (an ablation) executed by the hosted runner, not self-reported by the author — and the live scorecard, not this page, is the canonical copy of today’s numbers. Read both pass rates rather than the gap alone: 21% → 100% and 90% → 97% are both real improvements and are not the same purchase.
  • The fine print that keeps the number honest — the model it was measured on (gemini-3.6-flash), the benchmark date, the grading method (LLM-judged against per-case expectations), and the cost: at the time of writing this skill spends about 126% more tokens for that lift, because it puts a command reference in the prompt. Lift is model-relative and never free; the registry shows you the evidence instead of asking you to trust a score.
  • Two different axes, one page — you may see a SkillScore marked provisional right next to a verified benchmark. Not a contradiction: provisional describes the composite SkillScore (it rests on a single signal so far), while verified describes how the benchmark itself was produced (executed by the hosted runner rather than self-reported).
Also check the safety band: this skill is Passed — a static scan (secrets, remote-code execution, hidden unicode), an AI intent review, and a content review all came back clean. How skills are vetted covers what that does and doesn’t guarantee.
Why this skill for the demo: playwright-cli documents one specific tool’s exact subcommands and flags — and a model that has never seen that tool mostly cannot guess them. That is why the no-skill arm passes only about one case in five, and it is why you can tell the skill fired: the answer either names the right command or it doesn’t. It’s a worked example of the general pattern — skills earn lift by supplying knowledge the model can’t have.
Prefer to stay in your editor? Once, in any MCP client:
Then read the same scorecard by asking — “show me the benchmark evidence and safety scan for playwright-cli” — instead of opening the page. It’s read-only, so you still install with the commands in the next step. See Use skills without the SDK.
2

Install it (pick one of two)

Both routes are anonymous and end in the same place: a SKILL.md on disk where your runtime auto-discovers it.
The DecimalAI CLI pulls skills anonymously — no API key:
Writes .claude/skills/playwright-cli/SKILL.md — plus the skill’s eval.yaml test suite, so you can re-run the benchmark yourself. Read-only: no fork is created, nothing is tracked.
3

Watch it fire

Start a new Claude Code (or Cursor) session in the project — skills are discovered at session start. Then paste a task the skill was built for:
That is case-11 of the skill’s own eval.yaml, verbatim — one of the 19 of 24 cases that fail without the skill and pass with it. Note what it doesn’t say: it never names the tool. That’s the point. The benchmark’s recorded no-skill answer doesn’t know this tool has an attach command at all, so it offers commands for four other programs — agent-browser connect, npx playwright codegen --attach-to-browser=…, chrome-remote-interface inspect, puppeteer connect — and never reaches the right one. Confident, plausible, and nothing attaches.
What you should see:
  • The transcript shows the agent reading the skill (Claude Code surfaces the skill it loaded, or you’ll see it open .claude/skills/playwright-cli/SKILL.md).
  • The answer is the one line the skill documents: playwright-cli attach --cdp=http://localhost:9222.
  • If you get a menu of other tools’ commands instead, the skill didn’t load: check the file path and frontmatter, start a fresh session, or name it explicitly — “use the playwright-cli skill.” Naming it doesn’t weaken the check: the recorded no-skill run did consider Playwright and still answered npx playwright codegen --attach-to-browser=…. Knowing which tool you mean was never the hard part; knowing attach --cdp= is.
Why this case and not the Windows & one. The tempting demo is “escape & as ^& so cmd.exe doesn’t truncate the URL” — and it proves nothing. That’s case-04, and the scorecard records its outcome as pass_kept: the no-skill run scored 1/1 on the exact expectation you’d have been told to check for. &-as-command-separator is generic shell behaviour, not this tool’s quirk — the skill’s own text says “cmd.exe and PowerShell treat & as a command separator” — so the base model already has it. Five of the 24 cases are like that. A demo drawn from those five shows you a skill firing on knowledge the model didn’t need; picking from the 19 that flip is the difference between a demo and evidence.

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What just happened

You installed a plain-markdown skill your runtime already knows how to read, and you picked it off a scorecard instead of a download count. You also saw the shape of the trade: at the time of writing, the skill bought +79 points of correctness by spending a bit over twice the tokens. Both halves are on the scorecard — that’s the point of measuring rather than starring.

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Next steps

All the no-SDK routes

Web copy-paste, CLI pull, raw URLs, and the MCP server — every route from the registry to your agent, one page.

Build a whole agent from skills

Assemble a customer-operations agent from measured registry skills — and wire it so usage counts.

Browse the registry

Every published skill, ranked by measured effectiveness. No login to browse.

How the numbers are made

skillevaluation is the open spec + runner behind every verified lift number. Re-run any benchmark yourself.