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AgentTestMethodology

Universal AI Agent Testing Methodology — with PheronAgent as Reference Case Study

Version 7 · 2026-07-14


What This Is

A framework-agnostic, architecture-independent test methodology and battery that any agent developer can apply directly to their own project — regardless of language, runtime, or toolset.

The primary document exists in two languages: METHODOLOGY.md (English) and METHODOLOGY_TR.md (Turkish, the original — this is where the methodology was actually developed; see STORY.md). Both are structured in five layers:

Layer Content
Part I Industry benchmark map — what 61 academic and industry sources measure, and how to use them
Part II Universal test battery — 58 core blocks (L1–L4 / Error Recovery / Multi-Turn / Security), each split into a tool-agnostic Universal Capability definition and a concrete Reference Implementation
Parts III–IV, VI PheronAgent case study — how the methodology applies to a real agent with 50+ native/MCP tools (read for examples; do not copy verbatim)
Part V Advanced verifiability roadmap — cryptographic execution proofs, ZKP-based model verification, anti-gaming protocol (explicitly marked as aspirational/not yet implemented)
Parts VII–IX Audit trail — open issues, reconciliation log, full bibliography with verification status for every external claim

PheronAgent is one case study. The methodology is the product.


Quick Start

To build a test battery for your own agent: → Part II, Sections 4–10. Replace "PheronAgent Reference Implementation" fields with your own agent's tool names and expected outputs. The Universal Capability definitions require no changes.

To understand which benchmarks to cite: → Part I (61 benchmarks/standards/tools, categorized) + Part IX bibliography.

To get blank, project-neutral templates:templates/golden_dataset.template.json and templates/BLANK_TEST_BLOCK.template.md

To audit this document's own claims: → Parts VII–IX — detected inconsistencies, resolution records, and verification status of every external citation.

To read how this came to exist:STORY.md — the actual multi-week process: real bugs found in a running agent, real test runs, real corrections. Not a marketing narrative.


Coverage

Benchmark Categories (Part I)

  • Function-calling / Tool Use — BFCL, API-Bank, ToolBench, NESTFUL, ToolSandbox, ComplexFuncBench, ACEBench, StableToolBench, MetaTool
  • Multi-step Reasoning — GAIA, AgentBench, τ-bench, τ²-bench (dual-control, user simulator)
  • Web / Browser — WebArena, Mind2Web, WebVoyager, BrowserGym, VisualWebArena, AssistantBench
  • OS / Desktop / Terminal — OSWorld, AndroidWorld, Windows Agent Arena, Terminal-Bench
  • Software Engineering — SWE-bench, SWE-Lancer, MLE-bench
  • Security / Adversarial — InjecAgent, AgentDojo, AgentHarm, ToolEmu, R-Judge, SafeAgentBench, PrivacyLens, ST-WebAgentBench, Cybench + OWASP Top 10 for Agentic Applications 2026 (ASI01–ASI10) full taxonomy
  • Memory / Long Context — LongMemEval, LoCoMo, BEAM (1M and 10M token scale)
  • Harness Ecosystem — OpenClaw/Hermes, WildClawBench, HAL, CLEAR

Methodology Sections (Part I, Section 9)

Section Topic
9.1 LLM-as-Judge — known biases and mitigation strategies
9.2 pass@k vs. pass^k — when each applies, practical collapse table
9.3 Exact match vs. partial credit
9.4 Trajectory vs. end-state evaluation
9.5 Cost and latency metrics (CLEAR framework, HAL leaderboard approach)
9.6 Production observability — OpenTelemetry GenAI semantic conventions, LangSmith / Arize Phoenix / Langfuse / W&B Weave
9.7 Eval harness selection guide
9.8 Automated red-teaming — garak, PyRIT, DeepTeam
9.9 Benchmark reliability and anti-gaming
9.10 Multi-agent system testing
9.11 Regulatory alignment map — NIST AI RMF, MITRE ATLAS, EU AI Act, ISO/IEC 42001

Security Coverage (Part I, Sections 6.11–6.12)

Full OWASP Top 10 for Agentic Applications 2026 (ASI01–ASI10) taxonomy table with cross-mapping to the 6 universal security test blocks in Part II. Includes OWASP MCP Top 10 and MCP supply-chain security methodology (Section 8.5), plus a coverage-control survey of 40 agent safety benchmarks published April 2023–March 2026 (arXiv:2605.16282).

Test Battery (Part II)

58 universal core blocks across 7 tiers:

Tier Blocks Focus
L1 Basic 21 Routing, tool selection, parameter accuracy
L2 Intermediate 11 Chained tool calls, context carryover
L3 Advanced 7 Nested output passing, long-horizon planning
L4 Professional 5 Live inference, production-grade tasks
Error Recovery 4 Graceful failure, retry logic
Multi-Turn 4 Policy consistency, session memory
Security 6 Injection, privilege escalation, data exfiltration

Each block specifies: prerequisite tier, test type, input prompt, expected behavior (universal), acceptance criteria, rejection criteria, and a PheronAgent reference run for comparison.


Repository Structure

AgentTestMethodology/
├── METHODOLOGY.md                     # Primary document, English (v7, ~5750 lines)
├── METHODOLOGY_TR.md                  # Primary document, Turkish original (v7, ~5700 lines)
├── STORY.md                           # How this methodology actually came to be
├── README.md                          # This file
├── LICENSE                            # MIT — templates and code
├── LICENSE-docs.md                    # CC BY 4.0 — documentation and methodology
├── CHANGELOG.md                       # Version-by-version history
├── templates/
│   ├── BLANK_TEST_BLOCK.template.md   # Empty test block — fill in for your agent
│   └── golden_dataset.template.json   # Golden dataset schema
└── results/
    └── PheronAgent/
        ├── README.md                    # What this folder contains
        ├── datasets/                    # Filled-in golden-dataset examples (seed + smoke)
        └── run_qwen3.5-9b_*.{md,jsonl}  # 32 real result files, Section 2.7 naming — see folder README

Reuse

Documentation and methodology (METHODOLOGY.md, METHODOLOGY_TR.md, README.md, all .md content): CC BY 4.0 — free to use, adapt, and distribute with attribution.

Templates and code (templates/, any scripts): MIT — no restrictions.

Attribution example: "Based on AgentTestMethodology by Turgay Soysal (github.com/trgysvc/AgentTestMethodology), CC BY 4.0"


Scope and Honest Limitations

This document makes the following claims — and only these:

  • The 58 universal test blocks in Part II are directly applicable to any agent architecture.
  • The benchmark descriptions in Part I reflect published academic and industry sources; every external claim has a citation and a verification status in Part IX.
  • PheronAgent results reflect actual test runs where stated; sections marked "EXECUTION PENDING" have not yet been run.
  • Part V (cryptographic verifiability roadmap) is explicitly aspirational — not implemented, not planned for near-term, included for community discussion only.

What this document does not claim: that it covers every possible agent evaluation scenario, that the PheronAgent results are reproducible on other hardware without adjustment, or that any benchmark score from Part I applies to your agent without running it yourself.


Contributing

Issues and pull requests are welcome for:

  • Benchmark additions or corrections (with citation)
  • Errors in the universal test blocks
  • Template improvements
  • Translations of the methodology sections

Please open an issue before submitting a PR for structural changes to Part II.


Version History

See CHANGELOG.md for the full version-by-version history (currently at Version 7). For the story behind why each version changed what it changed — including the real bugs and dead ends that drove it — see STORY.md.

About

Framework-agnostic AI agent testing methodology: 61-source benchmark map, 58-block universal test battery (L1–L4, security, memory, multi-turn), OWASP Top 10 for Agentic Applications 2026, observability, cost/latency, and automated red-teaming. PheronAgent included as a reference case study.

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