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 JAICHANGPARK/workshop-harness --skill workshop-persona-loop-evaluatorgit clone --depth 1 https://github.com/JAICHANGPARK/workshop-harnessWrote 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/jaichangpark/workshop-harness/workshop-persona-loop-evaluator)<a href="https://agentmods.dev/skills/jaichangpark/workshop-harness/workshop-persona-loop-evaluator"><img src="https://agentmods.dev/badge/skills/jaichangpark/workshop-harness/workshop-persona-loop-evaluator.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 | $0.00067 | $0.01301 |
| Opus 5 | $0.00034 | $0.00651 |
| Sonnet 5 | $0.00013 | $0.00260 |
| Haiku 4.5 | $0.00007 | $0.00130 |
Grade A, and why
workshop-persona-loop-evaluator 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 — 122 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Workshop Persona Loop Evaluator Skill
Purpose
Applies Loop Engineering and multi-persona simulation to evaluate workshop materials before a live session. The agent assumes 4 distinct attendee reviewer roles to identify difficulty mismatches, missing prerequisites, vague instructions, security risks, and architecture flaws.
The 4 Attendee Reviewer Personas
1. Non-Coder / Complete Beginner Persona (Non-Coder)
- Profile: Product managers, designers, non-technical founders, marketers, or beginners with zero programming/terminal background.
- Review Lens:
- Are terminal commands 100% copy-paste ready without assumed shell knowledge?
- Are visual GUI steps (e.g., VS Code extension installation, clicking buttons) included?
- Is technical jargon (e.g.,
virtualenv,npm,CLI,API key,localhost) explained in plain language? - Would this attendee get stuck at step 1 due to missing OS prep?
- Key Metric: Zero friction to first successful run (No terminal blockers).
2. Novice / Beginner Developer Persona (Novice)
- Profile: Junior developers, students, or hobbyists with basic Python/JS syntax knowledge who struggle with environment variables, virtualenvs, pathing, and package conflicts.
- Review Lens:
- Are virtual environment (
venv/uv) creation and package installation explicit? - Is the delta between
01_starterand02_finalcode clear? - Are common runtime errors (e.g.,
ModuleNotFoundError,APIKeyError,PortInUse) covered with 10-second hotfix instructions? - Are API keys safely loaded via
.envinstead of hardcoded strings?
- Are virtual environment (
- Key Metric: Clear starter-to-final path and instant error recovery.
3. Intermediate Developer Persona (Intermediate)
- Profile: Experienced full-stack or backend developers familiar with REST APIs and basic LLM prompts, seeking non-trivial practical application.
- Review Lens:
- Does the curriculum go beyond basic "Hello World" into real-world patterns (RAG, structured output, function calling)?
- Is the code modular, readable, and idiomatic?
- Are stretch goals / bonus tasks provided for attendees who finish labs quickly?
- Are trade-offs (e.g., local Gemma vs Cloud Gemini) clearly explained?
- Key Metric: High engagement and practical architectural depth.
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 · 122 lines · 67 tokens per session scan A 5fdf8ecce4e4
workshop-persona-loop-evaluator is a skill published in the GitHub repository JAICHANGPARK/workshop-harness (5 stars, last pushed 7d ago), licensed MIT. It adds 67 tokens to every session and 1,301 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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