What is or-evaluate-model?

A research guide for evaluating one OpenRouter AI model in depth. It combines the model’s OpenRouter listing with information from its model card, research paper, benchmarks, licence and known limits.

Use it to investigate a shortlisted model, check its training and intended use, review benchmark results and limitations, and make a reasoned go-or-no-go decision.

It helps you decide whether a model fits your work before relying on it in a real workflow or production system. You get information that may not appear in the OpenRouter catalogue alone.

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

Your own site

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

Per session 96 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.

When invoked 943 The whole file, excluding the scripts and references it only reads on demand.

Security scan A 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.

Model	Per session	Once invoked
Fable 5.1	$0.00096	$0.00943
Opus 5.5	$0.00038	$0.00377
Sonnet 5.5	$0.00019	$0.00189
Haiku 4.5	$0.00010	$0.00094

Measured 2mo ago against content hash b47178336df5, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

or-evaluate-model scanned grade A 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 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.

Makes network callslowCapability

Not a fault in itself. Listed so you know the mod talks to something, and to what.

curl -s https://openrouter.ai/api/v1/models -H "Accept: application/json"

skills/or-evaluate-model/SKILL.md · 95 lines

How it starts

The opening of the file, as written. The whole thing — 95 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Evaluate an OpenRouter Model in Depth

Conduct a thorough evaluation of a single model the user is considering. Combine OpenRouter catalog data with external research — Hugging Face model card, original paper, license, benchmark coverage, community feedback — to give the user a confident go/no-go answer.

When to use

The user has shortlisted a model (often from or-recommend-model or or-compare-models) and wants to understand it deeply before committing — for a real workflow, a production deployment, or a comparison against incumbents.

Workflow

Step 1: Catalog snapshot

Fetch the OpenRouter catalog and extract the target model's full record:

curl -s https://openrouter.ai/api/v1/models -H "Accept: application/json"

Capture: id, context_length, modalities, pricing, supported_parameters, top_provider info, description, created date.

Step 2: External research

Go beyond the OR catalog. Use the available research tools (WebFetch, web search, Hugging Face MCP if available) to gather:

Hugging Face model card — for open-weights models, fetch from huggingface.co/<org>/<repo>. Look for: training data, training compute, licence, intended use, limitations, evaluation results.
Original paper — if the model has an arXiv paper, summarize key claims (architecture, training scale, headline benchmarks).
Provider's own announcement / docs — for proprietary models (OpenAI, Anthropic, Google), pull from official pages.
License — clearly state the licence and any commercial-use restrictions. This is especially important for Llama, Qwen, DeepSeek, Mistral families.
Benchmark coverage — what public benchmarks has it been tested on? Headline scores on MMLU, HumanEval, GSM8K, SWE-bench, etc. — but only cite scores you can actually find, never from memory.
Known limitations / failure modes — what is the model bad at? Reasoning depth, multilingual gaps, hallucination rates, refusal behavior?
Community reception — recent discussion, reviews, or notable usage reports if findable.

Read the full file on GitHub · 95 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 · 95 lines · 96 tokens per session scan A b47178336df5

Subscribe to this mod's changes

or-evaluate-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 96 tokens to every session and 943 once invoked, about $0.0004 per session on Opus 5.5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.

Data and AI Research

or-evaluate-model next to 6 skills from other repositories
Mod	Type	Stars	Last push	Licence	Scan	Tokens	Works with
or-evaluate-modeldanielrosehill/Claude-Open-Router-Model-Research-Plugin	Skill	2	6mo ago	MIT	A	96	Claude Code
agent-platform-model-registrygoogle/skills	Skill	22k	yesterday	Apache-2.0	A	60	Claude Code, Codex
foundry-config-setupmicrosoft/agent-framework	Skill	15k	yesterday	MIT	A	65	Claude Code, Codex
google-cloud-solution-agentic-analytics-spark-knowledge-cataloggoogle/skills	Skill	22k	yesterday	Apache-2.0	A	132	Claude Code, Codex
training-checkwanshuiyin/Auto-claude-code-research-in-sleep	Skill	19k	3d ago	MIT	A	35	Claude Code
nemo-automodel-launcher-configNVIDIA/skills	Skill	3.9k	yesterday	Apache-2.0	A	30	Claude Code
finetuningmicrosoft/skills	Skill	3.2k	yesterday	MIT	A	132	Claude Code

or-evaluate-model