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 98ping/chip --skill mylab-pearsongit clone --depth 1 https://github.com/98ping/chipWrote 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/98ping/chip/mylab-pearson)<a href="https://agentmods.dev/skills/98ping/chip/mylab-pearson"><img src="https://agentmods.dev/badge/skills/98ping/chip/mylab-pearson/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/98ping/chip/mylab-pearson"><img src="https://agentmods.dev/badge/skills/98ping/chip/mylab-pearson.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00181 | $0.01133 |
| Opus 5 | $0.00090 | $0.00566 |
| Sonnet 5 | $0.00036 | $0.00227 |
| Haiku 4.5 | $0.00018 | $0.00113 |
Grade A, and why
mylab-pearson 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 today.
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 — 79 lines — stays where its author put it; the contents beside it link to each section on GitHub.
MyLab / Pearson homework
Drives a Pearson MyLab (MathXL) assignment end to end with the Claude in Chrome
tools. The full runbook — every trap, with the fix — is
tooling/MYLAB_PEARSON.md. Read it before the first interaction; what follows
is the shape of the job.
The page helper is tooling/mylab-pearson.js.
Which skill
myopenmath.com→ themyopenmathskill. Different machinery (MathQuill, hash routing, per-question submits).mylabmastering.pearson.com/mylab.pearson.com→ this skill.
Ask first
Reading and computing is ordinary help. Opening an attempt, typing into boxes, and clicking Check answer each need Max's go-ahead. One ask covers a homework set with unlimited attempts. A timed or limited-attempt quiz is different: the irreversible step is opening it, so quote the attempt count, time limit and due date and ask before you start. Never enter credentials.
Steps
-
Get the tab into the MCP group. Clicking the assignment fires a popup that lands outside the group — ask Max to drag it in. Never let the group reach zero tabs, it dissolves (§1).
-
Promote the player to top-level before clicking Get started:
location.href = document.getElementById('ctl00_ctl00_InsideForm_MasterContent_PlayerHtml5').srcYou land ontdx.acs.pearson.comwith a real DOM instead of being screenshot-only. This is the move that makes the whole run fast (§2). -
Paste
tooling/mylab-pearson.js, then__ML.hookPopups(). -
Scope it: question count, points, due date, and whether tries are limited.
-
Per part:
__ML.q()to read →__ML.openFig()+__ML.fig()for any figure → compute → click the left edge of the box and type → verify with__ML.fields()→__ML.hit(/^Check answer/). -
Confirm with
__ML.score(), then__ML.hit(/^Next/). -
Write the study note into
output/study-notes/<course>-<set>.md, same format as themyopenmathskill's step 6: atopics:line, then Formulas, Strategies, Traps, Question index. Write it right after the last question, while the work is still in context.
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.
- today First seen · 79 lines · 181 tokens per session scan A 12356a13ffd8
mylab-pearson is a skill published in the GitHub repository 98ping/chip (1 stars, last pushed today), licensed MIT. It adds 181 tokens to every session and 1,133 once invoked, about $0.0009 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 2026-09-10.
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