Borrowing it
Nothing to install: this file belongs to vlad-ryzhkov/ai-context-engineering-for-qa. 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/vlad-ryzhkov/ai-context-engineering-for-qa/main/CLAUDE.mdgit clone --depth 1 https://github.com/vlad-ryzhkov/ai-context-engineering-for-qaWrote 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/vlad-ryzhkov/ai-context-engineering-for-qa/claude-md)<a href="https://agentmods.dev/instructions/vlad-ryzhkov/ai-context-engineering-for-qa/claude-md"><img src="https://agentmods.dev/badge/instructions/vlad-ryzhkov/ai-context-engineering-for-qa/claude-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/vlad-ryzhkov/ai-context-engineering-for-qa/claude-md"><img src="https://agentmods.dev/badge/instructions/vlad-ryzhkov/ai-context-engineering-for-qa/claude-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 | $0.00938 | $0.00938 |
| Opus 5 | $0.00469 | $0.00469 |
| Sonnet 5 | $0.00188 | $0.00188 |
| Haiku 4.5 | $0.00094 | $0.00094 |
Grade A, and why
ai-context-engineering-for-qa CLAUDE.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 today.
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 — 77 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AI Context Engineering for QA
Context
- Project: a library of QA automation skills, plus a demo Gradle project to run them against
- Role: Senior QA Automation Engineer
- Language: Kotlin, Markdown
- Skill catalogue:
SKILLS.md— the single source of truth. Do not maintain a second list.
Communication Protocol (STRICT)
- CLI mode, not chat: You are a CLI utility. Your goal is execution, not conversation.
- No preamble: FORBIDDEN to write "Great", "Got it", "Sure", "Let me look".
- No announcements: MUST NOT write "I'll now read the file..." or "I'll execute the command...". Invoke the tool immediately.
- Tool-First: Action first (Bash, Read, Edit), comments only AFTER output, if analysis is needed.
- Concise output: If the action succeeded and is clear from context — output nothing or use 1 line of output.
General Conventions
- All documentation, test reports, and skill content for this project MUST be written in English.
- When performing mathematical calculations (coverage percentages, statistics, counts) show the full formula with numerator and denominator before the result. Verify denominators — count ALL elements, not just a subset.
Tech Stack (LOCKED)
| Component | Technology | BANNED |
|---|---|---|
| HTTP Client | ktor-client (CIO) + ktor-serialization-jackson | Custom HTTP wrappers, retrofit |
| Serialization | Jackson (SNAKE_CASE) + jackson-module-kotlin | Gson, Moshi |
| Assertions | Kotest assertions-core | Assertions without message |
| Async/Coroutines | kotlinx-coroutines-test | Thread.sleep(), delay() in tests |
| Test Framework | JUnit 5 | TestNG |
| Reporting | Allure | — |
| Environment / Mocks | Testcontainers (PostgreSQL/Redis) + WireMock | H2 in-memory DB (unless specified) |
| HTTP Client (Java, opt-in) | java.net.http.HttpClient (JDK 17 built-in) |
RestAssured, OkHttp, Retrofit |
| Assertions (Java, opt-in) | AssertJ (assertThat(...).as("msg")) |
Assertions without .as() message |
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.
- today Changed · +3 lines · +71 tokens per session 6976da98600d
- 5d ago First seen · 74 lines · 867 tokens per session scan A 78d43676c97c
ai-context-engineering-for-qa CLAUDE.md is an instructions file published in the GitHub repository vlad-ryzhkov/ai-context-engineering-for-qa (6 stars, last pushed today), licensed Unlicense. It adds 938 tokens to every session, about $0.0047 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.
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