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.
npx skills add athola/claude-night-market --skill subagent-testinggit clone --depth 1 https://github.com/athola/claude-night-marketWrote 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/skills/athola/claude-night-market/subagent-testing)<a href="https://agentmods.dev/skills/athola/claude-night-market/subagent-testing"><img src="https://agentmods.dev/badge/skills/athola/claude-night-market/subagent-testing/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/skills/athola/claude-night-market/subagent-testing"><img src="https://agentmods.dev/badge/skills/athola/claude-night-market/subagent-testing.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00022 | $0.00823 |
| Opus 5 | $0.00011 | $0.00411 |
| Sonnet 5 | $0.00004 | $0.00165 |
| Haiku 4.5 | $0.00002 | $0.00082 |
Grade A, and why
subagent-testing 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 6d 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 — 114 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Subagent Testing - TDD for Skills
Test skills with fresh subagent instances to prevent priming bias and validate effectiveness.
When NOT To Use
- Writing the skill under test (use
abstract:skill-authoring) - A static quality audit with no execution (use
abstract:skills-eval)
Table of Contents
- Overview
- Why Fresh Instances Matter
- Testing Methodology
- Quick Start
- Detailed Testing Guide
- Success Criteria
Overview
Fresh instances prevent priming: Each test uses a new Claude conversation to verify the skill's impact is measured, not conversation history effects.
Why Fresh Instances Matter
The Priming Problem
Running tests in the same conversation creates bias:
- Prior context influences responses
- Skill effects get mixed with conversation history
- Can't isolate skill's true impact
Fresh Instance Benefits
- Isolation: Each test starts clean
- Reproducibility: Consistent baseline state
- Measurement: Clear before/after comparison
- Validation: Proves skill effectiveness, not priming
Testing Methodology
Three-phase TDD-style approach:
Phase 1: Baseline Testing (RED)
Test without skill to establish baseline behavior.
Phase 2: With-Skill Testing (GREEN)
Test with skill loaded to measure improvements.
Phase 3: Rationalization Testing (REFACTOR)
Test skill's anti-rationalization guardrails.
Quick Start
# 1. Create baseline tests (without skill)
# Use 5 diverse scenarios
# Document full responses
# 2. Create with-skill tests (fresh instances)
# Load skill explicitly
# Use identical prompts
# Compare to baseline
# 3. Create rationalization tests
# Test anti-rationalization patterns
# Verify guardrails work
Detailed Testing Guide
For complete testing patterns, examples, and templates:
- Testing Patterns - Full TDD methodology
- Test Examples - Baseline, with-skill, rationalization tests
- Analysis Templates - Scoring and comparison frameworks
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 6d ago First seen · 114 lines · 22 tokens per session scan A f04b55c990c7
subagent-testing is a skill published in the GitHub repository athola/claude-night-market (337 stars, last pushed today), licensed MIT. It adds 22 tokens to every session and 823 once invoked, about $0.0001 per session on Opus 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 2026-09-03.
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principle-test-behavior-not-implementation
Apply when you write, change, or keep a test. Call the code the way its users do and assert the result they observe against a literal expected value. If the test would still pass when every imported function returns undefined, rewrite the assertion or delete the test.