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/documentation.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/documentation)<a href="https://agentmods.dev/instructions/agentevalhq/agenteval/documentation"><img src="https://agentmods.dev/badge/instructions/agentevalhq/agenteval/documentation/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/documentation"><img src="https://agentmods.dev/badge/instructions/agentevalhq/agenteval/documentation.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 | $0.01257 | $0.01257 |
| Opus 5.5 | $0.00503 | $0.00503 |
| Sonnet 5.5 | $0.00251 | $0.00251 |
| Haiku 4.5 | $0.00126 | $0.00126 |
Grade A, and why
AgentEval documentation.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.
How it starts
The opening of the file, as written. The whole thing — 202 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AgentEval Documentation Guidelines
🎯 Core Principles
1. Evaluation First, Testing Second
- Lead with evaluation capabilities (quality metrics, LLM-as-judge)
- Follow with testing infrastructure (assertions, CI/CD)
- Frame testing as "automation of evaluation results"
2. Never Reveal Future Plans
Unless explicitly asked:
- Do NOT discuss upcoming features or planned changes
- Do NOT reference strategic direction or internal plans
- Do NOT mention /strategy folder content
- Focus on what IS available, not what WILL BE
3. No Redundancy - Point to Documents
- Never repeat detailed information already in another document
- Link to specific documents: "See assertions.md for details"
- Only repeat key principles or critical safety information
4. No Specific Numbers or Versions
| ❌ Don't Use | ✅ Use Instead |
|---|---|
| "3,015+ tests" | "comprehensive test suite" |
| "21 samples" | "detailed examples" |
| "v0.2.0-beta" | "current version" |
🏷️ Brand Identity
Primary Tagline: "The .NET Evaluation Toolkit for AI Agents"
AgentEval IS:
- The .NET equivalent of RAGAS and DeepEval for Python
- Built first for Microsoft Agent Framework (MAF)
- An evaluation framework that also does testing
AgentEval is NOT:
- Just a testing framework
- A Python port or wrapper
- A simple assertion library
Terminology Standards
| ✅ Preferred | ❌ Avoid | Context |
|---|---|---|
| evaluation | testing | Core purpose description |
| evaluate | test | When describing metrics |
| evaluation run | test run | Metric execution |
| evaluation result | test result | Metric outputs |
Exception: "Testing" is acceptable when discussing xUnit/NUnit/MSTest or CI/CD.
📚 Documentation Structure
Folder Layout
docs/- Main documentation folderdocs/adr/- Architecture Decision Recordsdocs/api/- Generated API referencedocs/showcase/- Examples and case studiesREADME.md- Project overviewCONTRIBUTING.md- Contribution guidelines
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 · 202 lines · 1,257 tokens per session scan A 16a90b5c66a7
AgentEval documentation.instructions.md is an instructions file published in the GitHub repository AgentEvalHQ/AgentEval (157 stars, last pushed 4d ago), licensed MIT. It adds 1,257 tokens to every session, about $0.0050 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.