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/thanh-abaii/gstack-windows-port/gstack-benchmark-modelsnpx skills add thanh-abaii/gstack-windows-port --skill gstack-benchmark-modelsgit clone --depth 1 https://github.com/thanh-abaii/gstack-windows-portWrote 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/thanh-abaii/gstack-windows-port/gstack-benchmark-models)<a href="https://agentmods.dev/skills/thanh-abaii/gstack-windows-port/gstack-benchmark-models"><img src="https://agentmods.dev/badge/skills/thanh-abaii/gstack-windows-port/gstack-benchmark-models.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 | $0.00018 | $0.03669 |
| Opus 5 | $0.00009 | $0.01835 |
| Sonnet 5 | $0.00004 | $0.00734 |
| Haiku 4.5 | $0.00002 | $0.00367 |
Grade A, and why
gs:benchmark-models 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 5d 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 — 386 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Preamble (run first)
python "bin/gstack-boot.py" --skill benchmark-models | iex
If PROACTIVE is "false", do not proactively suggest gstack skills AND do not
auto-invoke skills based on conversation context. Only run skills the user explicitly
types (e.g., /gs:qa, /gs:ship). If you would have auto-invoked a skill, instead briefly say:
"I think /skillname might help here — want me to run it?" and wait for confirmation.
The user opted out of proactive behavior.
If SKILL_PREFIX is "true", the user has namespaced skill names. When suggesting
or invoking other gstack skills, use the /gstack- prefix (e.g., /gstack-qa instead
of /qa, /gstack-ship instead of /ship). Disk paths are unaffected — always use
$GSTACK_ROOT/[skill-name]/SKILL.md for reading skill files.
If output shows UPGRADE_AVAILABLE <old> <new>: read $GSTACK_ROOT/gstack-upgrade/SKILL.md and follow the "Inline upgrade flow" (auto-upgrade if configured, otherwise AskUserQuestion with 4 options, write snooze state if declined). If JUST_UPGRADED <from> <to>: tell user "Running gstack v{to} (just updated!)" and continue.
If WRITING_STYLE_PENDING is yes: You're on the first skill run after upgrading
to gstack v1. Ask the user once about the new default writing style. Use AskUserQuestion:
v1 prompts = simpler. Technical terms get a one-sentence gloss on first use, questions are framed in outcome terms, sentences are shorter.
Keep the new default, or prefer the older tighter prose?
Options:
- A) Keep the new default (recommended — good writing helps everyone)
- B) Restore V0 prose — set
explain_level: terse
If A: leave explain_level unset (defaults to default).
If B: run $GSTACK_BIN/gstack-config set explain_level terse.
Always run (regardless of choice):
Remove-Item -Force ~/.gstack/.writing-style-prompt-pending
New-Item -ItemType File -Force ~/.gstack/.writing-style-prompted | Out-Null
This only happens once. If WRITING_STYLE_PENDING is no, skip this entirely.
If LAKE_INTRO is no: Before continuing, introduce the Completeness Principle.
Tell the user: "gstack follows the Boil the Lake principle — always do the complete
thing when AI makes the marginal cost near-zero. Read more: https://garryslist.org/posts/boil-the-ocean"
Then offer to open the essay in their default browser:
Start-Process https://garryslist.org/posts/boil-the-ocean
New-Item -ItemType File -Force ~/.gstack/.completeness-intro-seen | Out-Null
Only run open if the user says yes. Always run touch/New-Item to mark as seen. This only happens once.
If TEL_PROMPTED is no AND LAKE_INTRO is yes: After the lake intro is handled,
ask the user about telemetry. Use AskUserQuestion:
Help gstack get better! Community mode shares usage data (which skills you use, how long they take, crash info) with a stable device ID so we can track trends and fix bugs faster. No code, file paths, or repo names are ever sent. Change anytime with
gstack-config set telemetry off.
Options:
- A) Help gstack get better! (recommended)
- B) No thanks
If A: run $GSTACK_BIN/gstack-config set telemetry community
If B: ask a follow-up AskUserQuestion:
How about anonymous mode? We just learn that someone used gstack — no unique ID, no way to connect sessions. Just a counter that helps us know if anyone's out there.
Options:
- A) Sure, anonymous is fine
- B) No thanks, fully off
If B→A: run $GSTACK_BIN/gstack-config set telemetry anonymous
If B→B: run $GSTACK_BIN/gstack-config set telemetry off
Always run:
New-Item -ItemType File -Force ~/.gstack/.telemetry-prompted | Out-Null
This only happens once. If TEL_PROMPTED is yes, skip this entirely.
If PROACTIVE_PROMPTED is no AND TEL_PROMPTED is yes: After telemetry is handled,
ask the user about proactive behavior. Use AskUserQuestion:
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 5d ago First seen · 386 lines · 18 tokens per session scan A d66e0211d666
gs:benchmark-models is a skill published in the GitHub repository thanh-abaii/gstack-windows-port (34 stars, last pushed 3mo ago), licensed MIT. It adds 18 tokens to every session and 3,669 once invoked, about $0.0001 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 2026-08-30.
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