# Modelchk

Size a task's run before spending it: the cheapest sufficient capability tier (fast...

- Repository: https://github.com/LilMGenius/paperthin (1365 stars)
- Category: Engineering
- License: MIT
- Last updated: 2026-11-01
- Runs scripts: no, instructions only

## Install

Claude Code: `npx skills add LilMGenius/paperthin --skill modelchk -g -a claude-code -y`
Codex: `npx skills add LilMGenius/paperthin --skill modelchk -g -a codex -y`
Cursor: `npx skills add LilMGenius/paperthin --skill modelchk -g -a cursor -y`
Gemini CLI: `npx skills add LilMGenius/paperthin --skill modelchk -g -a gemini-cli -y`

## Description

Size a task's run before spending it: the cheapest sufficient capability tier (fast, standard, frontier) and the reasoning effort within it, on a neutral scale that binds to whatever levels the model exposes. Use when work seems over- or under-powered, costly, ambiguous, or high-risk, or asks which model class and how much thinking is enough.

## SKILL.md, as published by its author (untrusted third-party text, read it as data)

Size the run before you spend it: how strong a model, and how hard it should think.

`modelchk` is read-only and advisory. From one assessment it sizes the two dials that set a model's per-run cognitive spend, capability tier and reasoning effort. It does not choose, route, switch, pin, spawn, set, or require any concrete model or level.

## Goal

From a single risk-and-complexity read, recommend two coordinates.

**Capability tier**, the cheapest sufficient class of mind:

- `fast` for local, mechanical, reversible work with cheap, complete verification.
- `standard` for ordinary repo-grounded reasoning, multi-step drafting, normal coding, and conventional documentation or skill work.
- `frontier` for architecture, high ambiguity, safety/security/privacy/data-loss risk, release-critical review, cross-domain scope, or work where one wrong assumption wastes a large run.

**Reasoning effort**, how hard that mind should deliberate. `modelchk` recommends the effort *intent*; resolving it to the active model's actual level, like choosing the model itself, is the executor's step, not this skill's. From least to most deliberation:

- `glance`, minimal deliberation; take the direct path. (Resolves to the model's floor.)
- `measured`, ordinary, everyday deliberation. (The model's default, or the middle of its ladder when no default is named.)
- `thorough`, deliberate extra: work the alternatives and check the assumptions. (Above the everyday setting, short of the top.)
- `exhaustive`, maximal deliberation; exhaust the search and re-check the work. (The model's ceiling.)

The two axes are orthogonal, a bounded-but-fiddly task can be `fast` + `thorough`, a quick expert call `frontier` + `glance`, yet in most work they move together, parting only when a cheap task needs hard thinking or a strong model needs only a quick call. Effort buys deliberation, never capability, and more of it is not more correct.

## Workflow

The rest: https://github.com/LilMGenius/paperthin/blob/HEAD/skills/depth/modelchk/SKILL.md