What is or-recommend-model?

An interactive guide for choosing an OpenRouter AI model for a particular task. OpenRouter is a service that provides access to models from different providers.

Use it when comparing models for coding, chat, document processing, agent tool use, or other workloads and you want a ranked shortlist.

It helps narrow a large model catalog by asking about workload, cost, context size, speed, input types, and tool or structured-output needs.

or-recommend-model — Skill for Claude Code by danielrosehill

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 danielrosehill/Claude-Open-Router-Model-Research-Plugin --skill or-recommend-model

Clone the repo

git clone --depth 1 https://github.com/danielrosehill/Claude-Open-Router-Model-Research-Plugin

Made for: Claude Code.

Or install open-router-model-research, the plugin that ships this one along with the rest of its 8 skills.

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.

README.md

[![agentmods](https://agentmods.dev/badge/skills/danielrosehill/claude-open-router-model-research-plugin/or-recommend-model/github.svg)](https://agentmods.dev/skills/danielrosehill/claude-open-router-model-research-plugin/or-recommend-model)

Your own site

<a href="https://agentmods.dev/skills/danielrosehill/claude-open-router-model-research-plugin/or-recommend-model"><img src="https://agentmods.dev/badge/skills/danielrosehill/claude-open-router-model-research-plugin/or-recommend-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.

Your own site · 80×15

<a href="https://agentmods.dev/skills/danielrosehill/claude-open-router-model-research-plugin/or-recommend-model"><img src="https://agentmods.dev/badge/skills/danielrosehill/claude-open-router-model-research-plugin/or-recommend-model.svg" alt="Reviewed on agentmods" width="80" height="20"></a>

Per session 93 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.

When invoked 868 The whole file, excluding the scripts and references it only reads on demand.

Security scan A 0 findings. 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.

Model	Per session	Once invoked
Fable 5.1	$0.00093	$0.00868
Opus 5.5	$0.00037	$0.00347
Sonnet 5.5	$0.00019	$0.00174
Haiku 4.5	$0.00009	$0.00087

Measured 2mo ago against content hash f5a6c9fe4d42, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

or-recommend-model 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 2mo 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.

skills/or-recommend-model/SKILL.md · 65 lines

How it starts

The opening of the file, as written. The whole thing — 65 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Interactive recommendation flow: clarify the user's requirements, query the catalog, propose 2–3 ranked picks with rationale.

When to use

The user wants guidance on choosing a model and has not given enough detail to filter directly. The task is open-ended ("help me pick" / "which model should I use for X").

Workflow

Step 1: Gather requirements

Ask the user a short set of clarifying questions — only the ones not already answered. Keep the round-trip tight:

Use case — what's the workload? (chat, agentic tool use, document parsing, code generation, summarization, vision, audio, structured extraction, etc.)
Modalities — text only? Need image input? Audio input? Image generation?
Budget — soft ceiling on $/1M tokens (prompt and completion), or "cheapest possible", or "quality matters more than cost"?
Context window — minimum context required? (typical buckets: 8K, 32K, 128K, 200K+, 1M+)
Throughput / latency — does response speed matter? Any provider preference?
Tool use / structured output — needs function calling? JSON mode? Strict structured outputs?
Open-source preference — does the user want only open-weights models (DeepSeek, Llama, Qwen, Mistral) or are proprietary models (OpenAI, Anthropic, Google) fine?

Don't ask all seven if the user has already answered some. If you have enough to make a reasonable shortlist after 2–3 questions, proceed.

Step 2: Filter the catalog

Fetch https://openrouter.ai/api/v1/models and apply filters:

Modality requirements → architecture.input_modalities
Tool/structured output → supported_parameters includes tools / structured_outputs
Context → context_length >= user_minimum
Budget → pricing.prompt and pricing.completion within ceiling
Open-weights only → filter out openai/, anthropic/, google/ (proprietary), keep meta-llama/, deepseek/, qwen/, mistralai/, etc.

Step 3: Rank and present

Score each candidate against the user's stated priorities (cost vs. capability vs. context). Present 2–3 recommendations, not a long list:

Read the full file on GitHub · 65 lines

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.

2mo ago First seen · 65 lines · 93 tokens per session scan A f5a6c9fe4d42

Subscribe to this mod's changes

or-recommend-model is a skill published in the GitHub repository danielrosehill/Claude-Open-Router-Model-Research-Plugin (2 stars, last pushed 6mo ago), licensed MIT. It adds 93 tokens to every session and 868 once invoked, about $0.0004 per session on Opus 5.5. 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 2026-08-31.

Data and AI Prompting

or-recommend-model next to 6 skills from other repositories
Mod	Type	Stars	Last push	Licence	Scan	Tokens	Works with
or-recommend-modeldanielrosehill/Claude-Open-Router-Model-Research-Plugin	Skill	2	6mo ago	MIT	A	93	Claude Code
llm-app-patternsdavila7/claude-code-templates	Skill	33k	yesterday	MIT	A	54	Claude Code, Codex
prompt-engineerJeffallan/claude-skills	Skill	12k	7d ago	MIT	A	93	Claude Code
prompt-optimizationlangwatch/langwatch	Skill	5.0k	yesterday	Apache-2.0	A	105	Claude Code, Codex
omh-model-optimizationrlaope/oh-my-hermes	Skill	5.2k	yesterday	MIT	A	84	Claude Code, Codex
ideogram4digitalsamba/claude-code-video-toolkit	Skill	2.5k	yesterday	MIT	A	99	Claude Code
prompt-library-for-startupsaws/agent-toolkit-for-aws	Skill	3.4k	yesterday	Apache-2.0	A	228	Claude Code