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 hani-q/qstack --skill qstack-choose-modelgit clone --depth 1 https://github.com/hani-q/qstackWrote 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/hani-q/qstack/qstack-choose-model)<a href="https://agentmods.dev/skills/hani-q/qstack/qstack-choose-model"><img src="https://agentmods.dev/badge/skills/hani-q/qstack/qstack-choose-model/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/hani-q/qstack/qstack-choose-model"><img src="https://agentmods.dev/badge/skills/hani-q/qstack/qstack-choose-model.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 | $0.00134 | $0.02353 |
| Opus 5.5 | $0.00054 | $0.00941 |
| Sonnet 5.5 | $0.00027 | $0.00471 |
| Haiku 4.5 | $0.00013 | $0.00235 |
Grade B, and why
qstack-choose-model scanned grade B 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 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.
Reads agent configuration directoriesmediumAgent snooping
.claude/, .codex/, .gemini/ hold keys, settings and other credentials a mod has no legitimate need for.
2. The base URL the CLI already trusts: Codex's `model_providers.<current>.base_url` in `~/.codex/config.toml`, then `ANTHROPIC_BASE_URL`, then `OPENAI_BASE_URL`, each asked `GET /v1/models`. A CLIProxyAPI wired into eit How it starts
The opening of the file, as written. The whole thing — 174 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/qstack-choose-model
Which model should do this, and how hard should it think? Answer from what is reachable and what is measured, never from a name typed into a skill.
Invocation
/qstack-choose-model [task text] [--points N] [--files a,b] [--gate] [--live-target] [--orchestrator <model>]
With no task text, the task is the one settled in the conversation. Every
flag is optional metadata; when a board card is the task, its points,
files and refs are the metadata and the caller passes them.
Output, always the same shape, in the response and as JSON when a caller asked for it:
{"tier":"strong","model":"claude-opus-5","reasoning":"high",
"why":"5-point card with an integration seam; strong = top coding index among reachable non-orchestrator models (Artificial Analysis, 2026-09-20)",
"catalogue":"codex model_provider http://127.0.0.1:8317/v1","scores":"Artificial Analysis Data API, 2026-09-20"}
The script
Everything mechanical lives in scripts/qstack-models, next to this file.
Resolve it relative to this SKILL.md's real path; never hardcode a home.
| Command | Prints |
|---|---|
discover |
the reachable model ids and which source produced them |
score |
the catalogue joined with coding index and price |
tier --orchestrator M |
the strong / standard / cheap map, M excluded |
resolve NAME |
the id NAME means, or the closest three when it means nothing |
probe-brief ID |
the one-line task that proves ID can be launched |
aliases |
what Claude Code's fable/opus/sonnet/haiku resolve to here, from ANTHROPIC_DEFAULT_*_MODEL |
codex-agents --orchestrator M [--reviewer R] [--dir D] [--dry-run] |
writes the tier map as custom agent files qstack_strong, qstack_standard, qstack_cheap, qstack_reviewer under ~/.codex/agents/ |
Where the catalogue comes from
First hit wins, and the output names it:
QSTACK_MODELS_URL, an override nobody has to set.- The base URL the CLI already trusts: Codex's
model_providers.<current>.base_urlin~/.codex/config.toml, thenANTHROPIC_BASE_URL, thenOPENAI_BASE_URL, each askedGET /v1/models. A CLIProxyAPI wired into either CLI is found here with no setup. - The harness's built-in list: Claude Code's Agent tool enum, detected from
CLAUDECODEin the environment orQSTACK_HARNESS=claude-code. Codex has no fixed list of its own, so from Codex this step is empty. - Nothing usable: ask the user for the models that may work, one question, free text, then
resolveeach answer.
What ships with it
2 files 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.
- 1mo ago First seen · 174 lines · 134 tokens per session scan B 14dcc4260189
qstack-choose-model is a skill published in the GitHub repository hani-q/qstack (7 stars, last pushed 3d ago), licensed MIT. It adds 134 tokens to every session and 2,353 once invoked, about $0.0005 per session on Opus 5.5. A static security scan graded it B with 1 finding (reads agent configuration directories). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-21.
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