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 agentmods add skills/mayank-io/mstack/blog-postnpx skills add mayank-io/mstack --skill blog-postgit clone --depth 1 https://github.com/mayank-io/mstackWhat 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 | $0.00127 | $0.02466 |
| Opus 5 | $0.00063 | $0.01233 |
| Sonnet 5 | $0.00025 | $0.00493 |
| Haiku 4.5 | $0.00013 | $0.00247 |
Grade A, and why
blog-post scanned grade A with 1 finding against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
curl -sSL -A "Mozilla/5.0" -o "<slug>/images/NN-<label>.<ext>" "<image_url>" How it starts
The opening of the file, as written. The whole thing — 227 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Download Blog Post
Save a web article as a self-contained local folder: clean markdown with YAML frontmatter, every inline image downloaded and re-referenced, and any Vedic astrology charts digitized to JSON + ASCII.
This combines two tools: Defuddle (clean text, fast, low-token) for the article
body, and the gstack browser for images — because Defuddle strips lazy-loaded <img>
tags, leaving empty ![]() placeholders. A real browser recovers the image URLs
in document order.
Browser — always gstack, never headless
Browser work goes through the gstack browser, which holds the user's logged-in sessions. A fresh Playwright instance is logged out: it silently returns login walls or truncated content that looks like a successful capture.
B="$HOME/.claude/skills/gstack/browse/dist/browse"
"$B" connect # run from the target directory — another cwd spawns a second
# daemon and kills the headed session
"$B" goto "<url>"
"$B" js '<expression>'
The daemon must be in headed mode. browse status reports either headed
(attached to the user's real Chrome, carrying their logins) or launched (gstack's
own Chromium on a fresh profile, logged into nothing). A launched daemon returns
a login wall for every gated page, and a login wall reads as a short page rather
than an error — nothing downstream will flag it. Verify the mode, and force a
restart when it is wrong:
"$B" status # must report `mode: headed`
"$B" connect --force-restart # only when it does not — a launched daemon holds a
# fresh profile with no logins, so nothing is lost
The _browse.py adapter runs this check inside connect() and refuses to continue
if it cannot reach headed. Do the same by hand when driving $B directly.
Do NOT disconnect when done. browse disconnect tears down the daemon and
the logged-in sessions with it. Leave it running — the daemon is a shared user
resource, connect is safe to call again, and only whoever started it should
close it. The
adapter's close() is deliberately a no-op, so leaving the async with browse_page() block tears down nothing.
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.
- 2d ago First seen · 227 lines · 127 tokens per session scan A cbc4c65e9f66
blog-post is a skill published in the GitHub repository mayank-io/mstack (5 stars, last pushed 8d ago), licensed MIT. It adds 127 tokens to every session and 2,466 once invoked, about $0.0006 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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