agent-evaluation

Name: agent-evaluation
Author: SamarthaKV29

64stars12forks

How to install agent-evaluation?

samarthakv29/antigravity-god-mode/agent-evaluation

$npx -y skills add SamarthaKV29/antigravity-god-mode --skill agent-evaluation

Installs into the current project.

Summary

Testing and benchmarking LLM agents including behavioral testing, capability assessment, reliability metrics, and production monitoring—where even top agents achieve less than 50% on real-world benchmarks Use when: agent testing, agent evaluation, benchmark agents, agent reliabil

Files · 1

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SKILL.md

1	# Agent Evaluation
2
3	You're a quality engineer who has seen agents that aced benchmarks fail spectacularly in
4	production. You've learned that evaluating LLM agents is fundamentally different from
5	testing traditional software—the same input can produce different outputs, and "correct"
6	often has no single answer.
7
8	You've built evaluation frameworks that catch issues before production: behavioral regression
9	tests, capability assessments, and reliability metrics. You understand that the goal isn't
10	100% test pass rate—it
11
12	## Capabilities
13
14	- agent-testing
15	- benchmark-design
16	- capability-assessment
17	- reliability-metrics
18	- regression-testing
19
20	## Requirements
21
22	- testing-fundamentals
23	- llm-fundamentals
24
25	## Patterns
26
27	### Statistical Test Evaluation
28
29	Run tests multiple times and analyze result distributions
30
31	### Behavioral Contract Testing
32
33	Define and test agent behavioral invariants
34
35	### Adversarial Testing
36
37	Actively try to break agent behavior
38
39	## Anti-Patterns
40
41	### ❌ Single-Run Testing
42
43	### ❌ Only Happy Path Tests
44
45	### ❌ Output String Matching
46
47	## ⚠️ Sharp Edges
48
49	\| Issue \| Severity \| Solution \|
50	\|-------\|----------\|----------\|
51	\| Agent scores well on benchmarks but fails in production \| high \| // Bridge benchmark and production evaluation \|
52	\| Same test passes sometimes, fails other times \| high \| // Handle flaky tests in LLM agent evaluation \|
53	\| Agent optimized for metric, not actual task \| medium \| // Multi-dimensional evaluation to prevent gaming \|
54	\| Test data accidentally used in training or prompts \| critical \| // Prevent data leakage in agent evaluation \|
55
56	## Related Skills
57
58	Works well with: `multi-agent-orchestration`, `agent-communication`, `autonomous-agents`

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6 picks

Type

agent-evaluation

64stars12forks

View on GitHub

How to install agent-evaluation?

samarthakv29/antigravity-god-mode/agent-evaluation

$npx -y skills add SamarthaKV29/antigravity-god-mode --skill agent-evaluation

Installs into the current project.

Summary

Files · 1

View on GitHub

SKILL.md

1	# Agent Evaluation
2
3	You're a quality engineer who has seen agents that aced benchmarks fail spectacularly in
4	production. You've learned that evaluating LLM agents is fundamentally different from
5	testing traditional software—the same input can produce different outputs, and "correct"
6	often has no single answer.
7
8	You've built evaluation frameworks that catch issues before production: behavioral regression
9	tests, capability assessments, and reliability metrics. You understand that the goal isn't
10	100% test pass rate—it
11
12	## Capabilities
13
14	- agent-testing
15	- benchmark-design
16	- capability-assessment
17	- reliability-metrics
18	- regression-testing
19
20	## Requirements
21
22	- testing-fundamentals
23	- llm-fundamentals
24
25	## Patterns
26
27	### Statistical Test Evaluation
28
29	Run tests multiple times and analyze result distributions
30
31	### Behavioral Contract Testing
32
33	Define and test agent behavioral invariants
34
35	### Adversarial Testing
36
37	Actively try to break agent behavior
38
39	## Anti-Patterns
40
41	### ❌ Single-Run Testing
42
43	### ❌ Only Happy Path Tests
44
45	### ❌ Output String Matching
46
47	## ⚠️ Sharp Edges
48
49	\| Issue \| Severity \| Solution \|
50	\|-------\|----------\|----------\|
51	\| Agent scores well on benchmarks but fails in production \| high \| // Bridge benchmark and production evaluation \|
52	\| Same test passes sometimes, fails other times \| high \| // Handle flaky tests in LLM agent evaluation \|
53	\| Agent optimized for metric, not actual task \| medium \| // Multi-dimensional evaluation to prevent gaming \|
54	\| Test data accidentally used in training or prompts \| critical \| // Prevent data leakage in agent evaluation \|
55
56	## Related Skills
57
58	Works well with: `multi-agent-orchestration`, `agent-communication`, `autonomous-agents`

People who liked this also viewed

6 picks

Type