Borrowing it
Nothing to install: this file belongs to in-the-loop-labs/pair-review. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/in-the-loop-labs/pair-review/main/.claude/skills/update-provider-models/SKILL.mdgit clone --depth 1 https://github.com/in-the-loop-labs/pair-reviewWrote 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/in-the-loop-labs/pair-review/update-provider-models)<a href="https://agentmods.dev/skills/in-the-loop-labs/pair-review/update-provider-models"><img src="https://agentmods.dev/badge/skills/in-the-loop-labs/pair-review/update-provider-models/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/in-the-loop-labs/pair-review/update-provider-models"><img src="https://agentmods.dev/badge/skills/in-the-loop-labs/pair-review/update-provider-models.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00000 | $0.03179 |
| Opus 5 | $0.00000 | $0.01589 |
| Sonnet 5 | $0.00000 | $0.00636 |
| Haiku 4.5 | $0.00000 | $0.00318 |
Grade A, and why
update-provider-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 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.
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 — 218 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Update Provider Models
Update the built-in model configurations for pair-review's AI providers. This skill guides you through checking each provider's CLI for available models, gathering recommendations, and updating the source code.
When to Use
Run this skill periodically (e.g., monthly) or when new model releases are announced for any of the supported AI providers. Skip providers that were recently updated.
Providers to Update
The providers are defined in src/ai/ with these files:
antigravity-provider.js- Antigravity CLI (agy) modelscodex-provider.js- OpenAI Codex CLI modelscopilot-provider.js- GitHub Copilot CLI modelscursor-agent-provider.js- Cursor Agent CLI modelsopencode-provider.js- OpenCode CLI (no built-in models, config-only)claude-provider.js- Anthropic Claude CLI modelspi-provider.js- Pi coding agent modelsomp-provider.js- OMP / Oh My Pi CLI (omp, a Pi fork; only adefaultmode built in, real models are config-only)muse-provider.js- Meta Muse Code CLI (muse) models
Each provider file has a *_MODELS array at the top defining models with:
id: The CLI model identifier (passed to--modelflag)name: Display name in the UItier: One offast,balanced,thorough(orfree,premium)tagline,description,badge,badgeClass: UI metadatadefault: true: Marks the default model for the provideraliases: Optional extra ids that resolve to this entry (used to keep saved councils/configs working when an id is renamed)
Ground Rules for Probing
- Never trust a CLI's own model listing over a live probe. Installed binaries lag
the backend: on 2026-09-06
agy models(agy 1.0.16) did not list Gemini 3.8 Flash, and Muse's cached catalog did not list Spark 1.3, yet both ids ran fine. Conversely, ids a provider file still carries may be dead (gpt-5.4, gemini-3.5-flash). Probe every id you keep AND every id you add. - macOS has no
timeout. Wrap probes with perl instead:perl -e 'alarm 120; exec @ARGV' <cli> <args...> - Run probes from the scratchpad directory (some CLIs treat cwd as a workspace) and
run slow batches with
run_in_background. - Do not print
~/.pair-review/config.jsonwholesale — it holds tokens. Grep only thecommandlines you need.
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 Changed · +72 lines 2c7478b19fc6
- 10d ago First seen · 146 lines · 0 tokens per session scan A c1b18f57b1a1
update-provider-models is a skill published in the GitHub repository in-the-loop-labs/pair-review (58 stars, last pushed yesterday), licensed Apache-2.0. It costs nothing until one of its globs matches a file; then it loads 3,179 tokens. 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.
Other skills, from other repositories
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
local-ai-agents
Build local-first AI agents that run entirely on a developer workstation with Microsoft Foundry Local and Qwen function-calling models. Covers Small Language Models (SLMs), the OpenAI-compatible local endpoint, sandboxed local tools, local RAG with Chroma, local MCP servers, hybrid cloud/local routing, and the…
next-cache-components-adoption
Turn on Cache Components in a Next.js app and resolve the blocking routes it surfaces. Use when the user wants to enable, adopt, or migrate to Cache Components, flip the cacheComponents flag, work through a flood of blocking-prerender / instant validation errors, run the cache-components-instant-false codemod, or…
insight-error-page
Write or audit an insight-kind error page for the Next.js dev overlay. Use when creating a new errors/ .mdx page, auditing an existing one, or checking that a page matches the framework fix cards. Covers page structure, title alignment, FixCard cards with Copy prompt button, code snippets, terminology verification…
next-cache-components-optimizer
Drive a Next.js route to instant navigation by setting up an agentic loop, under Cache Components / PPR, on initial load (hard navigation) and client-side navigation (soft navigation). Encode the goal as a failing @next/playwright instant() e2e and work it to green, one verified route at a time; the shipped test then…
next-partial-prefetching-adoption
Turn on Partial Prefetching in a Next.js app and work through the insights it surfaces. Use when the user wants to enable or adopt Partial Prefetching, flip the partialPrefetching flag, opt routes in with export const prefetch = 'partial', audit Link prefetch={true} behavior, preserve existing prefetched UI with…