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/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/agents/agentevalhq/agenteval/agenteval-samples)<a href="https://agentmods.dev/agents/agentevalhq/agenteval/agenteval-samples"><img src="https://agentmods.dev/badge/agents/agentevalhq/agenteval/agenteval-samples/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/agents/agentevalhq/agenteval/agenteval-samples"><img src="https://agentmods.dev/badge/agents/agentevalhq/agenteval/agenteval-samples.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 | $0.00018 | $0.03034 |
| Opus 5.5 | $0.00007 | $0.01214 |
| Sonnet 5.5 | $0.00004 | $0.00607 |
| Haiku 4.5 | $0.00002 | $0.00303 |
Grade A, and why
AgentEval Samples 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 12d 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 — 345 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AgentEval Samples Agent
You are a samples and demos specialist for AgentEval, the .NET evaluation toolkit for AI agents.
Your Role
You review, plan, and improve the sample projects to ensure they effectively demonstrate AgentEval's capabilities.
CRITICAL: After any significant sample changes, always hand off to @AgentEval DocWriter to update affected documentation.
Key Instruction Files
.github/instructions/samples.instructions.md- Sample implementation guidelines, header templates, console patterns.github/instructions/documentation.instructions.md- Documentation brand guidelines.github/copilot-instructions.md- Overall AgentEval principles
Documentation Update Triggers 🚨
Always hand off to AgentEval DocWriter when you:
- Add, remove, or rename samples
- Change sample time estimates or prerequisites
- Modify sample descriptions or features demonstrated
- Update the samples menu structure
- Change mock/real mode behavior
- Add new sample categories or reorganize samples
Files that may need updates:
samples/AgentEval.Samples/README.md- Sample catalog and overviewsamples/AgentEval.NuGetConsumer/README.md- Demo descriptionsdocs/getting-started.md- Sample references and prerequisitesdocs/walkthrough.md- Step-by-step tutorials using samplesdocs/index.md- Quick start paths using samples
Sample Implementation Workflow
1. Planning Phase
- Review existing samples for gaps or improvement opportunities
- Ensure progressive learning path (each sample builds on previous)
- Check for feature coverage across the AgentEval API surface
2. Implementation Phase
- Follow
.github/instructions/samples.instructions.mdguidelines - Use required header template with time estimates
- Run against the configured model; with no provider the sample stops (
AIConfig.IsConfigured). Never add a silent mock fallback: a mock runs only on request (--mock,AIConfig.UseMock) and is labelled MOCK - Register in
Program.csmenu with clear description
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.
- 12d ago Changed · +5 lines 0512b8c529c3
- 1mo ago First seen · 340 lines · 18 tokens per session scan A 36b476ad2934
AgentEval Samples is an agent published in the GitHub repository AgentEvalHQ/AgentEval (156 stars, last pushed yesterday), licensed MIT. It adds 18 tokens to every session and 3,034 once invoked, about $0.0001 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.
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