Eval Agent

Community

jmagly

eval-agent

Run evaluation tests against an agent to assess quality and archetype resistance

Overview

Publisher	jmagly
Repository	`aiwg`
Skill name	`eval-agent`
Stars	225
Forks	34
Bundled files	Instructions only
License	MIT
Links	Skill source Repository Homepage

Markdown instructions
A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.
Works with any LLM
AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.
Self-contained
Everything the model needs lives in the instructions — no extra files to sync.
Open source
Published by jmagly on GitHub. Read the source before you install it.

Installation

Install the Eval Agent AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

Open the app and go to Plugins → Skills.
Choose "Install from GitHub".
Paste the skill folder URL below and confirm.
https://github.com/jmagly/aiwg/tree/main/agentic/code/addons/aiwg-evals/skills/eval-agent
Enable the skill in any chat where you want it available.

Store

Installed

Skills

Add skills

Import one or more skills from a public GitHub folder or a local .skill or .zip archive, or SKILL.md file.

From GitHub URLFrom .skill, .zip, or SKILL.md

GitHub repo or folder

https://github.com/jmagly/aiwg/tree/main/agentic/code/addons/aiwg-evals/skills/eval-agent

Points to a single skill folder, or any folder that contains multiple skills. Public repos only.

CancelContinue

Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills

git clone --depth 1 https://github.com/jmagly/aiwg.git /tmp/aiwg
mkdir -p .claude/skills
cp -r /tmp/aiwg/agentic/code/addons/aiwg-evals/skills/eval-agent .claude/skills/eval-agent

Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Eval Agent in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Eval Agent on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Eval Agent is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

Loaded only when it is needed
The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.
Switch models mid-chat
Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Agent Evaluation

Run automated evaluation tests against an agent.

Research Foundation

REF-001: BP-9 - Continuous evaluation of agent performance
REF-002: KAMI benchmark methodology for failure archetype detection

Usage

bash
/eval-agent security-architect
/eval-agent architecture-designer --category archetype
/eval-agent test-engineer --scenario grounding-test --verbose

Arguments

Argument	Required	Description
agent-name	Yes	Agent to evaluate

Options

Option	Default	Description
--category	all	Test category: archetype, performance, quality
--scenario	all	Specific scenario to run
--verbose	false	Show detailed test output
--output	stdout	Output file for results
--strict	false	Fail on any test failure

Test Categories

archetype

Tests for Roig (2025) failure archetypes:

grounding-test - Archetype 1: Premature action
substitution-test - Archetype 2: Over-helpfulness
distractor-test - Archetype 3: Context pollution
recovery-test - Archetype 4: Fragile execution

performance

latency-test - Response time benchmarks
token-test - Token efficiency
parallel-test - Concurrent execution correctness

quality

output-format - Output structure validation
tool-usage - Appropriate tool selection
scope-adherence - Stays within defined scope

Process

Load Agent: Read agent definition
Select Scenarios: Based on --category or --scenario
Setup Environment: Create test workspace
Execute Tests: Run agent against each scenario
Validate Results: Check assertions
Generate Report: Output results

Output Format

json
{
  "agent": "security-architect",
  "timestamp": "2025-01-15T10:30:00Z",
  "tests": {
    "grounding-test": {
      "passed": true,
      "score": 1.0,
      "details": "Read tool called before Edit",
      "duration_ms": 5000
    },
    "distractor-test": {
      "passed": false,
      "score": 0.6,
      "details": "Used staging data in output",
      "evidence": ["Found 'staging' in response"],
      "duration_ms": 3000
    }
  },
  "summary": {
    "passed": 3,
    "failed": 1,
    "total": 4,
    "score": 0.85
  }
}

Examples

bash
# Full evaluation
/eval-agent architecture-designer

# Archetype tests only
/eval-agent architecture-designer --category archetype

# Single scenario with verbose output
/eval-agent test-engineer --scenario grounding-test --verbose

# Save results
/eval-agent security-architect --output .aiwg/reports/security-eval.json

# Strict mode (fails on any test failure)
/eval-agent devops-engineer --strict

Success Criteria

Metric	Target
Grounding (A1)	>90%
Substitution (A2)	>85%
Distractor (A3)	>80%
Recovery (A4)	≥80%
Overall	≥85%

Related Commands

/eval-workflow - Test multi-agent workflows
/eval-report - Generate quality report
aiwg lint agents - Static validation

Evaluate agent: $ARGUMENTS

References

@$AIWG_ROOT/agentic/code/addons/aiwg-evals/README.md — aiwg-evals addon overview
@$AIWG_ROOT/agentic/code/addons/aiwg-utils/rules/god-session.md — Single-responsibility rules that agents are evaluated against
@$AIWG_ROOT/agentic/code/addons/aiwg-utils/rules/vague-discretion.md — Concrete success criteria and threshold definitions
@$AIWG_ROOT/agentic/code/frameworks/sdlc-complete/README.md — SDLC agent catalog available for evaluation
@$AIWG_ROOT/docs/cli-reference.md — CLI reference for aiwg lint agents

Frequently asked questions

What does the Eval Agent AI skill do?

Run evaluation tests against an agent to assess quality and archetype resistance

Why use Eval Agent on TypingMind?

Because you install it once and use it with any model. Eval Agent is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Eval Agent in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/jmagly/aiwg/tree/main/agentic/code/addons/aiwg-evals/skills/eval-agent. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Eval Agent?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Eval Agent?

As many as you like. As long as a model supports skills, you can use Eval Agent with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Eval Agent AI skill free?

Yes. It is published on GitHub by jmagly under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

Agent Evaluation

Research Foundation

Usage

Arguments

Options

Test Categories

archetype

performance

quality

Process

Output Format

Examples

Success Criteria

Related Commands

References

Frequently asked questions

Related AI Skills

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