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 manishiitg/coding-agent-loop --skill basic-browser-setupgit clone --depth 1 https://github.com/manishiitg/coding-agent-loopWrote 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/manishiitg/coding-agent-loop/basic-browser-setup)<a href="https://agentmods.dev/skills/manishiitg/coding-agent-loop/basic-browser-setup"><img src="https://agentmods.dev/badge/skills/manishiitg/coding-agent-loop/basic-browser-setup/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/manishiitg/coding-agent-loop/basic-browser-setup"><img src="https://agentmods.dev/badge/skills/manishiitg/coding-agent-loop/basic-browser-setup.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00043 | $0.00729 |
| Opus 5.5 | $0.00017 | $0.00292 |
| Sonnet 5.5 | $0.00009 | $0.00146 |
| Haiku 4.5 | $0.00004 | $0.00073 |
Grade A, and why
basic-browser-setup 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 1mo 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 — 54 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Basic Browser Setup
Outcome
Create a reusable browser QA foundation with managed browser access, canonical locator helpers, a saved smoke test, video plus console/network evidence, durable application knowledge, and a live report.
When to use
Use when onboarding an application or repairing an incomplete browser QA foundation. Preserve a compatible existing setup and an explicitly chosen Playwright alternative.
Discovery and user direction
Inspect the current workflow, goals, metrics, configuration, capabilities, stores, reports, and triggers before proposing changes. Summarize reusable design and gaps, then ask focused questions for unresolved customer choices such as scope, success, approvals, thresholds, ownership, and budgets. Record the answers as customer direction. Installation alone does not approve workflow changes or execution. Default to one small-team workflow; split only for incompatible access or lifecycle boundaries.
Required inputs
Resolve the application and environment, authorized account roles, authentication approach, approved smoke expectation, test-data and cleanup boundaries, test project, recording policy, and reporting preference. Keep missing required access or behavior as an explicit blocker.
Plan and AgentWorks tools
Inspect the existing workflow first. Use the managed browser for discovery and a scripted step for the repeatable smoke runner. Add agentic investigation or a readiness branch only when it protects a real judgment, retry, or downstream boundary. Follow the shared plan/tool guide and current builder-reference schemas.
Knowledge and persistence
Save executable selectors in shared test helpers. Record verified selectors, authentication quirks, routes, and setup in application knowledgebase notes with code/evidence links. Persist profile/run data in the workflow DB and videos, console/network logs, screenshots, and traces under durable assets.
Validation and reporting
Run the saved smoke test from a fresh context. Readiness requires approved assertions, complete machine-readable results, policy-required video and console/network evidence status, source/config revisions, and a verified live dashboard over durable data.
What ships with it
5 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.
- 1mo ago First seen · 54 lines · 43 tokens per session scan A 576cfe1dd150
basic-browser-setup is a skill published in the GitHub repository manishiitg/coding-agent-loop (13 stars, last pushed 19d ago), licensed MIT. It adds 43 tokens to every session and 729 once invoked, about $0.0002 per session on Opus 5.5. 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 2026-09-14.
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Generate Playwright UI tests and visual smoke reports for delivery POC frontends.
qa-systematic
Systematic web application QA testing with issue taxonomy, health scoring, and regression tracking. Triggers on: "QA this", "test the app", "smoke test", "run QA", "systematic test", "regression test", "full QA", "/qa-systematic".