Claude Quickstarts is a collection of starter projects for building applications with the Claude API, including customer support, financial analysis, and computer-use examples. Developers use them as foundations to customize for their own deployable applications, and the catalogue add-ons provide workflows for working with these quickstarts.
Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add anthropics/claude-quickstarts --skill first-rungit clone --depth 1 https://github.com/anthropics/claude-quickstartsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/anthropics/claude-quickstarts/first-run)<a href="https://agentmods.dev/skills/anthropics/claude-quickstarts/first-run"><img src="https://agentmods.dev/badge/skills/anthropics/claude-quickstarts/first-run.svg" alt="Measured on agentmods" height="20"></a>- Snyk warn
- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to high
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- high Privilege Escalation · line 28 Code accesses credential files (SSH keys, AWS credentials, etc.). This could indicate credential theft attempts.Fix: Remove references to credential paths. Use environment variables or secrets managers. For docs, use placeholder paths (e.g., /path/to/config). Never load .env or token files in production code paths.
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00029 | $0.00800 |
| Opus 5 | $0.00015 | $0.00400 |
| Sonnet 5 | $0.00006 | $0.00160 |
| Haiku 4.5 | $0.00003 | $0.00080 |
Grade A, and why
first-run scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 8d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 76 lines — stays where its author put it; the contents beside it link to each section on GitHub.
First run
Walk the user through running this demo for the first time. Be conversational and pause for confirmation between phases; the goal is that they understand what each step does, not just that the commands succeed.
0. Orient
Briefly say what is about to happen: you will check their setup, run one safe browser-only task that does not touch their mouse or keyboard, and then open the trajectory viewer so they can see what the model saw.
1. Environment check
Never read the contents of
.env. Do notcat,grep(without-q),Read, or otherwise display it — the user's API key must never appear in this conversation or in your context. Only check for its presence.
- Confirm a virtual environment is active and dependencies are installed:
python -c "import computer_use, playwright; print('ok')". If that import fails, point them at the Installation section ofREADME.mdand stop. - Confirm
.envexists and the API key is set without ever printing it:[ -f .env ] && grep -q '^ANTHROPIC_API_KEY=.' .env && echo 'API key: set' || echo 'API key: missing'If missing, copy.env.exampleto.envand ask the user to open it in their own editor and paste their key into it (do not ask them to paste the key into chat, and do not edit.envfor them). Wait until they confirm. - Run the macOS permission preflight non-fatally:
python -c "from computer_use.preflight import check_and_warn; check_and_warn(require=False)"and explain any warnings. These permissions are only needed for the desktopcomputertool, which the first task does not use, so it is fine to continue without them for now.
2. Run a safe browser-only task
Explain that this task uses only the headless browser tool, so nothing on their screen will move. Then run:
CU_ENABLE_COMPUTER_USE_TOOLS=false python -m computer_use \
"Navigate to https://en.wikipedia.org/wiki/Special:Random three times, \
take a screenshot each time, then summarize what you saw."
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 8d ago First seen · 76 lines · 29 tokens per session scan A e29759d67b95
first-run is a skill published in the GitHub repository anthropics/claude-quickstarts (17,620 stars, last pushed 3d ago), licensed MIT. It adds 29 tokens to every session and 800 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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