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 KunanonJ/ai-skills-hub --skill aside-captcha-solvergit clone --depth 1 https://github.com/KunanonJ/ai-skills-hubWrote 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/kunanonj/ai-skills-hub/aside-captcha-solver)<a href="https://agentmods.dev/skills/kunanonj/ai-skills-hub/aside-captcha-solver"><img src="https://agentmods.dev/badge/skills/kunanonj/ai-skills-hub/aside-captcha-solver/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/kunanonj/ai-skills-hub/aside-captcha-solver"><img src="https://agentmods.dev/badge/skills/kunanonj/ai-skills-hub/aside-captcha-solver.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 | $0.00034 | $0.00578 |
| Opus 5 | $0.00017 | $0.00289 |
| Sonnet 5 | $0.00007 | $0.00116 |
| Haiku 4.5 | $0.00003 | $0.00058 |
Grade A, and why
aside-captcha-solver 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 — 70 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Solving CAPTCHAs
Use the captcha global in REPL. Three methods: click, drag, readText. All return a snapshot tree so you can verify visually.
Checkbox CAPTCHAs
// 1. Find widget bounds via snapshot / evaluate
const s = await snapshot(page);
const bounds = await page.evaluate(`(() => {
const el = document.querySelector('iframe');
if (!el) return null;
const r = el.getBoundingClientRect();
return { x: r.x, y: r.y, width: r.width, height: r.height };
})()`);
// 2. Click and check result
const tree = await captcha.click(page, bounds);
// tree = post-click snapshot — check if widget shows checkmark / "verified"
Slider / Puzzle Drag CAPTCHAs
// Drag from the slider handle to the target position
const tree = await captcha.drag(page, { x: 150, y: 300 }, { x: 450, y: 300 });
// tree = post-drag snapshot — check if puzzle solved
// With more granular steps for precision
const tree = await captcha.drag(page, from, to, { steps: 40 });
Text / Number CAPTCHAs
// OCR the CAPTCHA image region
const text = await captcha.readText(page, { x: 100, y: 200, width: 200, height: 60 });
// → "xK7m2"
// Or OCR the full page (if bounds unknown)
const text = await captcha.readText(page);
// Then fill the input
await page.locator('input').fill(text);
Methods
captcha.click(page?, bounds): Promise<string>
Click within bounds (left-center), wait 3s, return snapshot tree.
captcha.drag(page?, from, to, opts?): Promise<string>
Drag between two viewport coordinates. opts.steps controls smoothness (default 20). Returns snapshot tree.
captcha.readText(page?, bounds?): Promise<string | null>
Screenshot (optionally clipped to bounds), OCR via vision model, return the text.
Tips
- CAPTCHA widgets are often inside iframes — viewport coordinates via
page.mouse.click(x, y)reach them - Use
annotatedScreenshot()if you need to visually inspect the CAPTCHA state - For image grid challenges, use
annotatedScreenshot()+ vision to identify cells, then click each one
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 · 70 lines · 34 tokens per session scan A 1f7aee73f50e
aside-captcha-solver is a skill published in the GitHub repository KunanonJ/ai-skills-hub (5 stars, last pushed yesterday), licensed MIT. It adds 34 tokens to every session and 578 once invoked, about $0.0002 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 2026-09-03.
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Trigger: SDD research, external evidence, source-backed research. Produce auditable evidence for a selected research lane.
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