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 | $0.01700 |
| Opus 5.5 | $0.00072 | $0.00680 |
| Sonnet 5.5 | $0.00036 | $0.00340 |
| Haiku 4.5 | $0.00018 | $0.00170 |
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 1mo 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 — 111 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, or__ML.table()+__ML.stats()for a data table (§14) → compute → click the left edge of the box and type → verify with__ML.fields()→ wait 1s (§16) →__ML.hit(/^Check answer/). Batch the whole part (fill, wait, check, screenshot) into onebrowser_batchcall rather than one tool call per step.
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.
- 1mo ago Changed · +32 lines 781596eb772b
- 1mo ago 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 1mo ago), licensed MIT. It adds 181 tokens to every session and 1,700 once invoked, about $0.0007 per session on Opus 5.5. 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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