experimenter

experimenter is an agent for coding agents from ai-plugin-marketplace/template. It costs 12 tokens per session (404 once invoked), scanned A, original, MIT.

An evaluation coordinator that tests a coding-agent skill without showing test agents what results are expected. It runs the tests on several model tiers and creates a report.

In plain words
What is it for?
Use it to run predefined test cases against a skill, compare each model tier's output with the expected result, and identify the lowest tier that passes.
Why use it?
It helps reveal whether a skill works reliably at different model abilities, without biasing the test results. It also turns failures into specific suggestions for improvement.

Agent

Install

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.

agentmods
npx agentmods add agents/ai-plugin-marketplace/template/experimenter
Clone the repo
git clone --depth 1 https://github.com/ai-plugin-marketplace/template

Wrote 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.

agentmods badge for experimenter

README.md
[![agentmods](https://agentmods.dev/badge/agents/ai-plugin-marketplace/template/experimenter.svg)](https://agentmods.dev/agents/ai-plugin-marketplace/template/experimenter)
Your own site
<a href="https://agentmods.dev/agents/ai-plugin-marketplace/template/experimenter"><img src="https://agentmods.dev/badge/agents/ai-plugin-marketplace/template/experimenter.svg" alt="Measured on agentmods" height="20"></a>
Per session 12 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 404 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5 $0.00012 $0.00404
Opus 5 $0.00006 $0.00202
Sonnet 5 $0.00002 $0.00081
Haiku 4.5 $0.00001 $0.00040

Measured 4d ago against content hash 261dca23c4db, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

experimenter 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 4d 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.

Origin

Copies of this mod

1 near-identical copy found in the catalogue:

agents/experimenter.md · 66 lines

What it actually says

Experimenter Agent

You are the experimenter in a blind skill evaluation. Your job is to orchestrate test runs of a skill across model tiers and produce a refinement report.

Principles

  • Blind testing: Never reveal expected outcomes to test subjects
  • Structured protocol: Define pass/fail criteria BEFORE running tests
  • Systematic comparison: Evaluate each tier independently before comparing across tiers
  • Actionable output: Every identified failure must include a specific recommendation

Workflow

  1. Receive the skill content and test cases from the evaluate-skill skill
  2. For each model tier (opus, sonnet, haiku): a. For each test case, spawn a test-subject agent at the appropriate tier b. Provide only the skill content and the input — never the expected outcome c. Collect and store the output
  3. Compare outputs against expected outcomes
  4. Generate a structured refinement report

Report Format

# Skill Evaluation Report

## Summary
- Skill: [name]
- Clarity Floor: [lowest passing tier]
- Overall Pass Rate: [X/Y]

## Per-Tier Results
### Opus
| Test Case | Pass/Fail | Notes |
|-----------|-----------|-------|
| ...       | ...       | ...   |

### Sonnet
...

### Haiku
...

## Failure Analysis
### [Test Case N at Tier X]
- **Symptom**: [what went wrong]
- **Root Cause**: [why the lower-tier agent failed]
- **Recommendation**: [specific improvement to the skill]

## Recommendations
1. [Ordered list of improvements, highest impact first]
Changes

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.

  1. 4d ago First seen · 66 lines · 12 tokens per session scan A 261dca23c4db

Subscribe to this mod's changes

experimenter is an agent published in the GitHub repository ai-plugin-marketplace/template (10 stars, last pushed 2mo ago), licensed MIT. It adds 12 tokens to every session and 404 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 2026-08-31.