Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/slamb2k/mad-skillsnpx agentmods add skills/slamb2k/mad-skills/play-tightWrote 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/slamb2k/mad-skills/play-tight)<a href="https://agentmods.dev/skills/slamb2k/mad-skills/play-tight"><img src="https://agentmods.dev/badge/skills/slamb2k/mad-skills/play-tight/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/slamb2k/mad-skills/play-tight"><img src="https://agentmods.dev/badge/skills/slamb2k/mad-skills/play-tight.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
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 →
- medium Rogue Agent · line 244 Skill establishes unauthorized persistence across sessions via cron jobs, startup scripts, or state files. Session persistence allows an attacker to maintain access beyond the current interaction.Fix: Remove any persistence mechanisms (cron jobs, startup scripts, state files). Skills should not maintain state across sessions without explicit user consent.
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 | $0.00071 | $0.02971 |
| Opus 5 | $0.00036 | $0.01486 |
| Sonnet 5 | $0.00014 | $0.00594 |
| Haiku 4.5 | $0.00007 | $0.00297 |
Grade A, and why
play-tight 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 10d 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 — 440 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Play-Tight
Play-Tight provides context-efficient browser automation using Playwright scripts executed via bash, with an optional subagent pattern for isolating verbose browser responses. The skill replaces the verbose Playwright MCP server with optimized scripts and subagent patterns to minimize context window pollution, saving context for actual engineering processes.
When to Use This Skill
Use Play-Tight when you need to:
- Verify elements exist on web pages (buttons, forms, links)
- Extract text content or structured data from websites
- Check status of web dashboards (CI/CD, monitoring, PRs)
- Take screenshots of pages or specific elements
- Automate repetitive browser tasks
- Validate web application behavior
Automatic Browser Detection
IMPORTANT: Before using any Playtight script, automatically check if Playwright browsers are installed.
Detection Process
- Check for browser installation by running:
node -e "const { chromium } = require('playwright'); chromium.executablePath()" 2>&1
-
If the check fails (exit code non-zero or error message):
- Inform the user that Playwright browsers need to be installed
- Offer to run the installation: "I can install the required browsers by running
npm run install-browsersin the scripts directory. Would you like me to do that?" - If user agrees, run:
cd ~/.claude/plugins/mad-skills/play-tight/scripts && npm run install-browsers -
If npm dependencies are missing (error about 'playwright' module not found):
- First install npm dependencies:
cd ~/.claude/plugins/mad-skills/play-tight/scripts && npm install - Then install browsers:
npm run install-browsers
- First install npm dependencies:
Example Detection Flow
# First attempt to use a script
node scripts/check-element.js https://example.com h1
# If error mentions "browserType.launch: Executable doesn't exist"
# Or "Cannot find module 'playwright'"
# Then detect and offer installation:
"I see that Playwright browsers aren't installed yet. I can install them now by running 'npm run install-browsers'. This will download Chromium (~100MB). Would you like me to proceed?"
# On user approval:
cd ~/.claude/plugins/mad-skills/play-tight/scripts && npm install && npm run install-browsers
What ships with it
7 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 10d ago First seen · 440 lines · 71 tokens per session scan A bfd2ef355daf
play-tight is a skill published in the GitHub repository slamb2k/mad-skills (5 stars, last pushed 4d ago), licensed MIT. It adds 71 tokens to every session and 2,971 once invoked, about $0.0004 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 2026-08-31.
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