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 agentmods add skills/ai-driven-dev/framework/11-browser-qanpx skills add ai-driven-dev/framework --skill 11-browser-qagit clone --depth 1 https://github.com/ai-driven-dev/frameworkWrote 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/ai-driven-dev/framework/11-browser-qa)<a href="https://agentmods.dev/skills/ai-driven-dev/framework/11-browser-qa"><img src="https://agentmods.dev/badge/skills/ai-driven-dev/framework/11-browser-qa.svg" alt="Measured on agentmods" 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 | $0.00055 | $0.00306 |
| Opus 5 | $0.00028 | $0.00153 |
| Sonnet 5 | $0.00011 | $0.00061 |
| Haiku 4.5 | $0.00006 | $0.00031 |
Grade A, and why
11-browser-qa 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 yesterday.
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.
What it actually says
Browser QA
flowchart LR
prerequisites["prerequisites"] --> scope["load-scope"] --> prepare["prepare-run"] --> run["run-scenarios"]
Actions
Read only the next action's file before running it.
| # | Action | Does |
|---|---|---|
| 00 | prerequisites |
Verify the browser runner and media dependencies |
| 01 | load-scope |
Lock one happy path and a bounded set of sourced edge cases |
| 02 | prepare-run |
Resolve the shortest deterministic path to executable runs |
| 03 | run-scenarios |
Record, normalize, verify, reset, and report every scenario |
Transversal rules
- Run against a reviewed change and never patch the application.
- Never spawn agents. Batch independent reads and tool checks, but keep state-changing browser work sequential.
- Do not narrate action transitions, searches, fixtures, selectors, or successful checks. Report only a blocker, a required decision, or the final verdict and paths.
What ships with it
6 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.
- yesterday First seen · 30 lines · 55 tokens per session scan A d6eaa84f7d95
11-browser-qa is a skill published in the GitHub repository ai-driven-dev/framework (453 stars, last pushed yesterday), licensed MIT. It adds 55 tokens to every session and 306 once invoked, about $0.0003 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 2026-09-03.
Other skills, from other repositories
run-dashboard-e2e-local-changes
Run Playwright E2E (tests/e2e/) against the docker/ all-in-one harness so it reflects LOCAL code changes, not a stale cached image.
browser-qa
Validate web applications through the embedded browser with responsive, interaction, console, and screenshot checks.
webapp-testing
Web application testing principles. E2E, Playwright, deep audit strategies.
composio-webapp-testing
Skill "composio-webapp-testing" from KornLabs/truss, covering web application testing, decision tree: choosing your approach, example: using withserver.py, reconnaissance-then-action pattern and common pitfall.
smoke-test
End-to-end smoke test skill for DeerFlow. Guides through: 1) Pulling latest code, 2) Docker OR Local installation and deployment (user preference, default to Local if Docker network issues), 3) Service availability verification, 4) Health check, 5) Final test report. Use when the user says "run smoke test", "smoke…
langbot-testing
Test LangBot WebUI and core product flows with an automated browser and backend logs. Use when validating the configured LangBot frontend, pipeline Debug Chat, model provider setup and test buttons, bot and knowledge-base UI flows, or troubleshooting failed LangBot end-to-end tests.