qstack-choose-model

qstack-choose-model is a skill for Codex from hani-q/qstack. It costs 134 tokens per session (2,353 once invoked), scanned B, original, MIT.

A tool that chooses a reachable language model and reasoning level for one coding task using the available catalogue and benchmark results. It bases the choice on what the machine can access and what has been measured.

In plain words
What is it for?
Use it to select a model for a task, taking account of task difficulty, file count, point estimates, approval gates, or a live target when those details are supplied.
Why use it?
It avoids choosing a model only from a name supplied in the request, especially when that model may not be available or comparable.

Skill for Codex

Written for Codex: agents/openai.yaml present. Also seen: mentions subagents; mentions Claude Code; reads ~/.codex paths.

Good fit Use it to select a model for a task, taking account of task difficulty, file count, point estimates, approval gates, or a live target when those details are supplied.

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Install with agentmods
npx agentmods add skills/hani-q/qstack/qstack-choose-model
Install

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.

Any agent
npx skills add hani-q/qstack --skill qstack-choose-model
Clone the repo
git clone --depth 1 https://github.com/hani-q/qstack

Made for: Codex.

Wrote 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.

agentmods badge for qstack-choose-model

README.md
[![agentmods](https://agentmods.dev/badge/skills/hani-q/qstack/qstack-choose-model/github.svg)](https://agentmods.dev/skills/hani-q/qstack/qstack-choose-model)
Your own site
<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.

agentmods 80×15 button for qstack-choose-model

Your own site · 80×15
<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>
Per session 134 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,353 The whole file, excluding the scripts and references it only reads on demand.
Security scan B 1 finding. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce 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

Measured 1mo ago against content hash 14dcc4260189, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

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
skills/qstack-choose-model/SKILL.md · 174 lines

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:

  1. QSTACK_MODELS_URL, an override nobody has to set.
  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 either CLI is found here with no setup.
  3. The harness's built-in list: Claude Code's Agent tool enum, detected from CLAUDECODE in the environment or QSTACK_HARNESS=claude-code. Codex has no fixed list of its own, so from Codex this step is empty.
  4. Nothing usable: ask the user for the models that may work, one question, free text, then resolve each answer.

Read the full file on GitHub · 174 lines

Files

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.

Changes

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.

  1. 1mo ago First seen · 174 lines · 134 tokens per session scan B 14dcc4260189

Subscribe to this mod's changes

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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