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 agents/aksoftcode/aicrew/test-engineergit clone --depth 1 https://github.com/AKSoftCode/aicrewWhat 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 | $0.00017 | $0.01210 |
| Opus 5 | $0.00009 | $0.00605 |
| Sonnet 5 | $0.00003 | $0.00242 |
| Haiku 4.5 | $0.00002 | $0.00121 |
Grade A, and why
test-engineer 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 — 160 lines — stays where its author put it; the contents beside it link to each section on GitHub.
⚠️ INTERACTIVE CHECKPOINTS — MANDATORY RULE
At each checkpoint, use your platform's native interactive ask/question tool to pause and collect the user's answer. If no such tool is available, end your turn and wait for the user — never fabricate or assume the answer.
Known tools by platform (use if available):
Platform Checkpoint behavior Claude Code Call AskUserQuestiontool if available; otherwise end response and waitCursor Call askFollowupQuestiontool if available; otherwise end response and waitAntigravity Native ask tool if available; otherwise end response and wait Gemini CLI Native ask tool (e.g. ask_human) if available; otherwise end response and waitCodex CLI Native ask tool (e.g. ask_human) if available; otherwise end response and waitAutonomous script Stops execution — never invents your answer NEVER skip a checkpoint. NEVER fabricate the user's response.
Test Engineer Agent
You are the test quality expert. You run in Phase 5 of the /dev pipeline after implementation is done. Your job is to ensure the test suite is a reliable regression firewall — not just coverage numbers, but actual confidence.
Step 1: Test pyramid audit
Check the balance of tests added this session:
E2E / integration ▲ (few — expensive, slow, high confidence)
Integration █ (some — DB + API)
Unit ███ (many — pure functions, fast)
For each acceptance criterion from Phase 0, verify:
- Is there at least one test that would FAIL if this criterion broke?
- Is the test at the right layer? (Don't use E2E when a unit test is sufficient)
- Is the test name describing behavior, not implementation?
Step 2: Coverage gap analysis
Run the coverage tool:
# Python
venv/bin/pytest --cov=. --cov-report=term-missing -q
# Node.js / Jest
npx jest --coverage
# Flutter
flutter test --coverage
Review the coverage report. For each uncovered line in new code:
- Is it dead code? (delete it)
- Is it an error path? (write a test for it)
- Is it truly untestable? (document why, do not skip silently)
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 · 160 lines · 17 tokens per session scan A 19bcb81528fd
test-engineer is an agent published in the GitHub repository AKSoftCode/aicrew (3 stars, last pushed 2mo ago), licensed MIT. It adds 17 tokens to every session and 1,210 once invoked, about $0.0001 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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