Borrowing it
Nothing to install: this file belongs to Mallikarjun-Roddannavar/playwright-agentic-automation. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/Mallikarjun-Roddannavar/playwright-agentic-automation/main/AGENTS.mdgit clone --depth 1 https://github.com/Mallikarjun-Roddannavar/playwright-agentic-automationWrote 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/instructions/mallikarjun-roddannavar/playwright-agentic-automation/agents-md)<a href="https://agentmods.dev/instructions/mallikarjun-roddannavar/playwright-agentic-automation/agents-md"><img src="https://agentmods.dev/badge/instructions/mallikarjun-roddannavar/playwright-agentic-automation/agents-md/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/instructions/mallikarjun-roddannavar/playwright-agentic-automation/agents-md"><img src="https://agentmods.dev/badge/instructions/mallikarjun-roddannavar/playwright-agentic-automation/agents-md.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 | $0.01660 | $0.01660 |
| Opus 5 | $0.00830 | $0.00830 |
| Sonnet 5 | $0.00332 | $0.00332 |
| Haiku 4.5 | $0.00166 | $0.00166 |
Grade A, and why
playwright-agentic-automation AGENTS.md 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.
How it starts
The opening of the file, as written. The whole thing — 136 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AGENTS.md
This file applies to the entire playwright-agentic-automation framework.
Purpose
Maintain this Playwright + TypeScript framework for UI and API automation practice. Follow Playwright best practices and Selenium-style Page Object Model guidance as adapted in this repo.
Agentic QA operating principles
- Diagnose before modifying; green output is not evidence that product behavior is correct.
- Read
qa/failure-taxonomy.jsonbefore diagnosing or repairing a failure. It is the detailed policy source of truth. - Preserve real test, trace, screenshot, API, source, and requirement evidence before classification.
- Application defects, API contract failures, environment failures, and
UNKNOWNare not healing opportunities. - Assertions express test intent. Never weaken an assertion without supported behavior and any policy-required review.
- Never skip, fixme, delete, swallow, or force a test merely to obtain green output.
- Prefer the smallest evidence-backed repair; then run
npm run qa:guardrailsand rerun the affected test. - Use official Playwright agents, CLI, or optional MCP where helpful. This repository adds QA discipline around them rather than replacing them.
Use The Local Skills
Use these local skills when their scope matches the task:
pw-ui-pomforui/pages,ui/specs, and UI navigation/page-object changespw-api-pomforapi/services,api/specs,utils/fixtures/TestFixtures.ts, and auth/API session workpw-framework-toolingforplaywright.config.ts, linting, formatting, typechecking, logging, waits, reporting, and README quality-tooling updatescodebase-second-brainfor persistent codebase discovery, OKF knowledge updates, AST graph queries, and Obsidian-ready knowledge navigationqa-safe-healingfor diagnosis-only reports and policy-governed repair after a Playwright failure
When a request asks how a feature works, how behavior is tested, what covers a
feature, or whether knowledge is stale or conflicting, use codebase-second-brain
as the primary skill. Use pw-ui-pom and pw-api-pom as supporting skills for
the specific UI or API files identified by the knowledge layer. Users should be
able to ask these questions naturally without naming knowledge files or commands.
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 Changed · +14 lines · +235 tokens per session 6d410959171b
- 9d ago First seen · 122 lines · 1,425 tokens per session scan A 3bdd67e9f9f5
playwright-agentic-automation AGENTS.md is an instructions file published in the GitHub repository Mallikarjun-Roddannavar/playwright-agentic-automation (11 stars, last pushed 2d ago), licensed MIT. It adds 1,660 tokens to every session, about $0.0083 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.
Other instructions, from other repositories
next.js AGENTS.md
AGENTS.md instructions for vercel/next.js, covering next.js development guide, codebase structure, monorepo overview, core package: packages/next and other important packages.
codex AGENTS.md
AGENTS.md instructions for openai/codex, covering rust/codex-rs, the codex-core crate, code review rules, crate api surface and model visible context.
vscode buildNext.instructions.md
Working notes and architecture documentation for the new esbuild-based build system in build/next. Use when making changes to the new build pipeline (transpile/bundle commands, NLS plugin, source-map handling, resource copying, or self-hosting watch tasks).
vscode oss-third-party-notices.instructions.md
Instructions for microsoft/vscode, covering vs code oss third-party-notices pipeline, architecture, pipeline flow in ci, applying the notice (cutover) and fallback chain (never fail the build).
langchain AGENTS.md
AGENTS.md instructions for langchain-ai/langchain, covering global development guidelines for the langchain monorepo, corridor security analysis, project architecture and context, monorepo structure and development tools & commands.
deepseek-harness AGENTS.md
AGENTS.md instructions for deepseek-ai/deepseek-harness, covering agents.md, pre-stable apis and released session data, repository layout, commands and host sandbox failures.