Borrowing it
Nothing to install: this file belongs to AgentEvalHQ/AgentEval. 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/AgentEvalHQ/AgentEval/main/.github/instructions/testing.instructions.mdgit clone --depth 1 https://github.com/AgentEvalHQ/AgentEvalWrote 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/agentevalhq/agenteval/testing)<a href="https://agentmods.dev/instructions/agentevalhq/agenteval/testing"><img src="https://agentmods.dev/badge/instructions/agentevalhq/agenteval/testing/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/agentevalhq/agenteval/testing"><img src="https://agentmods.dev/badge/instructions/agentevalhq/agenteval/testing.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 | $0.00484 | $0.00484 |
| Opus 5.5 | $0.00194 | $0.00194 |
| Sonnet 5.5 | $0.00097 | $0.00097 |
| Haiku 4.5 | $0.00048 | $0.00048 |
Grade A, and why
AgentEval testing.instructions.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 2mo 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.
What it actually says
AgentEval Test Guidelines
Test Naming Convention
Use: MethodName_StateUnderTest_ExpectedBehavior
[Fact]
public async Task HaveCalledTool_WhenToolWasCalled_ShouldPass()
Test Structure
- Tests mirror
src/folder structure intests/AgentEval.Tests/ - Use xUnit with
[Fact]and[Theory]attributes - Each public class/method should have corresponding tests
Using FakeChatClient
For metrics that call LLMs, use FakeChatClient to avoid API calls:
var fakeClient = new FakeChatClient("""{"score": 95, "explanation": "Good"}""");
var metric = new FaithfulnessMetric(fakeClient);
var result = await metric.EvaluateAsync(context);
Creating ToolUsageReport for Tests
var report = new ToolUsageReport(new List<ToolCallRecord>
{
new() { Name = "SearchTool", CallId = "call-1", Result = "found" },
new() { Name = "ProcessTool", CallId = "call-2", Result = "done" }
});
Creating PerformanceMetrics for Tests
var metrics = new PerformanceMetrics
{
TotalDuration = TimeSpan.FromSeconds(2.5),
TimeToFirstToken = TimeSpan.FromMilliseconds(250),
PromptTokens = 100,
CompletionTokens = 50,
ModelUsed = "gpt-4o"
};
Assertion Tests Pattern
When testing assertions, expect ToolAssertionException or PerformanceAssertionException:
[Fact]
public void HaveCalledTool_WhenToolNotCalled_ShouldThrow()
{
var report = new ToolUsageReport([]);
var ex = Assert.Throws<ToolAssertionException>(() =>
report.Should().HaveCalledTool("MissingTool"));
Assert.Contains("MissingTool", ex.Message);
Assert.NotNull(ex.Expected);
Assert.NotNull(ex.Actual);
}
Multi-Target Framework Testing
Tests run on net8.0, net9.0, net10.0 - ensure compatibility. Use #if NET8_0 sparingly.
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.
- 2mo ago First seen · 68 lines · 484 tokens per session scan A 6e1700aabfc2
AgentEval testing.instructions.md is an instructions file published in the GitHub repository AgentEvalHQ/AgentEval (157 stars, last pushed 4d ago), licensed MIT. It adds 484 tokens to every session, about $0.0019 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 2026-08-30.
Other instructions, from other repositories
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).
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.
vscode oss-third-party-notices.instructions.md
Instructions for microsoft/vscode, covering vs code oss third-party-notices pipeline, architecture, pipeline flow in ci, cache eligibility and rollout and applying the notice (cutover).
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.
vscode copilot-instructions.md
Copilot instructions for microsoft/vscode, covering vs code copilot instructions, project overview, root folders, core architecture (src/ folder) and built-in extensions (extensions/ folder).
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.