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.
git clone --depth 1 https://github.com/VoTruongDanh/Skills-AgentWrote 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/rules/votruongdanh/skills-agent/test)<a href="https://agentmods.dev/rules/votruongdanh/skills-agent/test"><img src="https://agentmods.dev/badge/rules/votruongdanh/skills-agent/test/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/rules/votruongdanh/skills-agent/test"><img src="https://agentmods.dev/badge/rules/votruongdanh/skills-agent/test.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 | $0.00058 | $0.00793 |
| Opus 5.5 | $0.00023 | $0.00317 |
| Sonnet 5.5 | $0.00012 | $0.00159 |
| Haiku 4.5 | $0.00006 | $0.00079 |
Grade A, and why
test 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 — 66 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Memory Protocol
START: Read .ai-memory.md from project root. Check test framework in use, existing test coverage, known failing tests, testing patterns, and CI/CD test configuration.
END: Update .ai-memory.md using Memory Compaction Rules with: tests changed, coverage deltas (if known), patterns established, and gaps.
Goal
Improve confidence in the system through targeted testing.
Agent Routing
- Primary → read
.kiro/skills/agents/agents/test-engineer.mdand apply its knowledge - If testing reveals bugs → read
.kiro/skills/agents/agents/debugger.mdand apply its knowledge - For E2E/integration tests with UI → read
.kiro/skills/agents/agents/frontend-specialist.mdand apply its knowledge - For API/backend tests → read
.kiro/skills/agents/agents/backend-specialist.mdand apply its knowledge - For security testing → read
.kiro/skills/agents/agents/security-auditor.mdand apply its knowledge
Socratic Gate
Before writing tests, verify:
- What is the test scope? (unit, integration, E2E, API?)
- Does a test framework already exist in the project?
- What are the critical paths that must be tested? If any answer is unclear, ASK before proceeding.
Workflow
- Read Memory — Load
.ai-memory.mdfor testing history and patterns. - Identify the unit, integration, API, UI, or regression scope.
- Enumerate critical paths, edge cases, and failure modes.
- Add or propose tests that cover the most important risks first.
- Explain how to run the tests and what passing means.
- Quality Gate — Read
.kiro/skills/_scripts/checklist.mdand run test suite after writing tests. - Update Memory — Save test details and coverage notes to
.ai-memory.md.
Checklist
-
Test scope identified
-
Test framework confirmed/proposed
-
Critical paths covered
-
Edge cases included
-
Failure modes tested
-
Tests are stable (not brittle)
-
Run instructions provided
-
Memory file updated
-
Clean code chuẩn (Standard clean code applied)
-
Cập nhật đầy đủ tất cả các file liên quan (All related files fully updated)
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 Changed · +3 lines a030ccce398f
- 1mo ago First seen · 63 lines · 58 tokens per session scan A aa2bccb2af92
test is a cursor rule published in the GitHub repository VoTruongDanh/Skills-Agent (4 stars, last pushed 19d ago), licensed MIT. It adds 58 tokens to every session and 793 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 2026-08-31.
Other cursor rules, from other repositories
20-testing-generated-and-structure
Testing expectations, generated-file boundaries, and CLI structure contract.
fuzzing
Fuzzing setup and guidelines for skia-rs.
testing-and-quality
The testcomprehensive.py provides systematic testing of all 31 MCP tools.
smoke-monkey-tester
Smoke tests for core functionality and monkey/chaos tests aiming to break the system with randomized inputs. / TR: Sistemin temel fonksiyonlarını kontrol eden smoke testler ve rastgele girdilerle sistemi çökertmeyi hedefleyen monkey/chaos testleri.
STAGE_S5_TEST_POINTS
A staged workflow for turning approved requirements into a complete list of test points. It checks required earlier documents and records any requirement that has no matching test point.
testing
Testing conventions for Ion Design System using Jest and Angular Testing Library.