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.
npx skills add nirholas/three.ws --skill openrouter-ai-models-guidegit clone --depth 1 https://github.com/nirholas/three.wsWrote 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/nirholas/three.ws/openrouter-ai-models-guide)<a href="https://agentmods.dev/skills/nirholas/three.ws/openrouter-ai-models-guide"><img src="https://agentmods.dev/badge/skills/nirholas/three.ws/openrouter-ai-models-guide/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/nirholas/three.ws/openrouter-ai-models-guide"><img src="https://agentmods.dev/badge/skills/nirholas/three.ws/openrouter-ai-models-guide.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 2 findings, up to high
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- high Privilege Escalation · line 117 Code accesses credential files (SSH keys, AWS credentials, etc.). This could indicate credential theft attempts.Fix: Remove references to credential paths. Use environment variables or secrets managers. For docs, use placeholder paths (e.g., /path/to/config). Never load .env or token files in production code paths.
- medium Data Exfiltration · line 34 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
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 | $0.00064 | $0.01353 |
| Opus 5.5 | $0.00026 | $0.00541 |
| Sonnet 5.5 | $0.00013 | $0.00271 |
| Haiku 4.5 | $0.00006 | $0.00135 |
Grade A, and why
openrouter-ai-models-guide 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 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
curl https://openrouter.ai/api/v1/chat/completions \ How it starts
The opening of the file, as written. The whole thing — 161 lines — stays where its author put it; the contents beside it link to each section on GitHub.
OpenRouter AI Models Guide
OpenRouter provides a unified API for 200+ AI models. This guide covers model selection, pricing, routing, and integration with SperaxOS.
What Is OpenRouter?
A single API endpoint that routes requests to 200+ models:
Your App → OpenRouter API → Model Provider
├── OpenAI (GPT-4, o1, o3)
├── Anthropic (Claude 4, Sonnet, Haiku)
├── Google (Gemini 2.5, Pro, Flash)
├── Meta (Llama 4, Maverick)
├── Mistral (Large, Medium)
├── DeepSeek (V3, R1)
└── 50+ more providers
Quick Start
curl https://openrouter.ai/api/v1/chat/completions \
-H "Authorization: Bearer $OPENROUTER_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "anthropic/claude-sonnet-4-20250514",
"messages": [{"role": "user", "content": "Hello!"}]
}'
Model Selection Guide
By Task
| Task | Recommended Model | Why |
|---|---|---|
| Complex reasoning | claude-sonnet-4, o3 | Best logical reasoning |
| Coding | claude-sonnet-4, deepseek-v3 | Best code generation |
| Creative writing | claude-sonnet-4, gpt-4o | Most creative output |
| Fast responses | gemini-flash, claude-haiku | Lowest latency |
| Long context | gemini-pro-2.5 (1M), claude-sonnet-4 (200K) | Largest context windows |
| DeFi analysis | claude-sonnet-4, gpt-4o | Best structured data handling |
| Vision/images | gpt-4o, gemini-pro | Best image understanding |
| JSON output | claude-sonnet-4, gpt-4o | Most reliable structured output |
| Budget | deepseek-v3, llama-4 | Cheapest per token |
By Price (per 1M tokens)
| Tier | Input | Output | Models |
|---|---|---|---|
| Free | $0 | $0 | Selected models with limits |
| Budget | $0.10-0.50 | $0.30-1.50 | DeepSeek, Llama, Gemma |
| Standard | $1-5 | $3-15 | GPT-4o, Claude Sonnet, Gemini Pro |
| Premium | $10-15 | $30-60 | o3, Claude Opus |
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.
- 1mo ago First seen · 161 lines · 64 tokens per session scan A c5a9c3605c74
openrouter-ai-models-guide is a skill published in the GitHub repository nirholas/three.ws (244 stars, last pushed today), licensed Apache-2.0. It adds 64 tokens to every session and 1,353 once invoked, about $0.0003 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 2026-09-03.
Other skills, from other repositories
LLM
Implement large language model (LLM) chat completions using the z-ai-web-dev-sdk. Use this skill when the user needs to build conversational AI applications, chatbots, AI assistants, or any text generation features. Supports multi-turn conversations, system prompts, and context management.
outlines
Outlines: structured JSON/regex/Pydantic LLM generation.
guidance
Constrain LLM output with grammars; guarantee valid JSON.
data-leakage-detection
Detect sensitive information disclosure via escalating dialogue probes. Covers system prompt extraction, credential/API key leakage, PII, and internal configuration exposure.
ax-playbook
This skill helps an LLM generate correct playbook code using @ax-llm/ax. Use when the user asks about playbook(), AxPlaybook, context playbooks, evolving context, ACE / Agentic Context Engineering, agent.playbook(), or growing/applying task knowledge offline and online with evolve() and update().
ax-refine
Use this skill when writing or reviewing Ax bestOfN/refine code, reward functions, thresholds, native sample selection, serial attempts, generated advice, and attempt diagnostics.