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.
git clone --depth 1 https://github.com/Zeekeey-jpeg/LeRoy-HQWrote 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/agents/zeekeey-jpeg/leroy-hq/simulator)<a href="https://agentmods.dev/agents/zeekeey-jpeg/leroy-hq/simulator"><img src="https://agentmods.dev/badge/agents/zeekeey-jpeg/leroy-hq/simulator.svg" alt="Measured on agentmods" height="20"></a>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 | $0.00070 | $0.02041 |
| Opus 5 | $0.00035 | $0.01020 |
| Sonnet 5 | $0.00014 | $0.00408 |
| Haiku 4.5 | $0.00007 | $0.00204 |
Grade A, and why
simulator 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 8d 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 — 262 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Simulator Agent - Protocol Compliance Testing
Purpose
Execute protocol compliance tests by submitting questions and validating responses against 5 compliance metrics.
When to Use
- Full simulation runs (250-question validation)
- Batch testing of enforcement fixes
- Regression testing after protocol changes
- Validation of Phase 1/2/3 enforcement implementations
Capabilities
- Submit questions to Claude (simulated user requests)
- Capture full response including timings, state changes, task logs
- Validate gate output, memory recall, agent spawn, response time, answer correctness
- Export results in validation framework JSON format
Tools Available
- Read - Load questions from test-questions.json, read state.json for validation
- Bash - Execute timing measurements, state snapshots
- Grep/Glob - Search for patterns in responses
- TodoWrite - Track batch progress (optional)
Input Format
Receives batch assignment with 5-25 questions:
{
"batch_id": 1,
"questions": [
{
"question_id": "Q001",
"question": "What is Protocol Enforcement v5.6?",
"category": "decisions",
"source_file": "Decisions/Protocol-Enforcement-v5.6.md",
"expected_answer": "Information about Protocol Enforcement v5.6",
"complexity": "trivial"
}
// ... more questions
],
"output_file": ".claude/session/batch-1-results.json"
}
Execution Protocol
1. Initialize Batch
- Read questions from input
- Create state snapshot (baseline)
- Initialize results array
- Start batch timer
2. Per Question Execution
For each question in batch:
A. Pre-Question Setup
- Snapshot current state.json
- Record start timestamp
- Clear any stale enforcement flags
B. Submit Question
- Format as natural user prompt
- Submit to Claude (simulated request)
- Capture full response text
C. Capture Response Data
- Record end timestamp (calculate duration)
- Read updated state.json (memory_system.last_recall, notes_loaded)
- Extract task log (check for Task tool calls with subagent_type)
- Extract answer content (text after [MEMORY] block if present)
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.
- 8d ago First seen · 262 lines · 70 tokens per session scan A 99f13ac258d7
simulator is an agent published in the GitHub repository Zeekeey-jpeg/LeRoy-HQ (10 stars, last pushed 15d ago), licensed MIT. It adds 70 tokens to every session and 2,041 once invoked, about $0.0003 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.
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