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 fabioc-aloha/Alex_Skill_Mall --skill llm-model-selectiongit clone --depth 1 https://github.com/fabioc-aloha/Alex_Skill_MallWrote 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/fabioc-aloha/alex_skill_mall/llm-model-selection)<a href="https://agentmods.dev/skills/fabioc-aloha/alex_skill_mall/llm-model-selection"><img src="https://agentmods.dev/badge/skills/fabioc-aloha/alex_skill_mall/llm-model-selection/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/fabioc-aloha/alex_skill_mall/llm-model-selection"><img src="https://agentmods.dev/badge/skills/fabioc-aloha/alex_skill_mall/llm-model-selection.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00021 | $0.02199 |
| Opus 5 | $0.00010 | $0.01099 |
| Sonnet 5 | $0.00004 | $0.00440 |
| Haiku 4.5 | $0.00002 | $0.00220 |
Grade A, and why
llm-model-selection 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 8d 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.
LLM Model Selection Skill
Choosing the right model for the task — power vs. cost vs. speed.
⚠️ Staleness Warning
This skill depends on rapidly evolving technology. Model capabilities, pricing, and availability change frequently.
Refresh triggers:
- New model announcements (Claude, GPT, Gemini, etc.)
- Significant pricing changes
- Context window expansions
- New capability tiers
Last validated: March 2026 (Claude 4.6 generation)
Check current state: Anthropic Models, OpenAI Models
The Core Question
Is Claude Opus 4.6 overkill?
Sometimes yes, sometimes no. Match the model to the task.
Claude 4 Model Family (Current)
| Model | API ID | Best For | Input/Output (MTok) | Context | Max Output |
|---|---|---|---|---|---|
| Opus 4.6 | claude-opus-4-6 |
Building agents, most intelligent | $5 / $25 | 200K (1M beta) | 128K |
| Sonnet 4.6 | claude-sonnet-4-6 |
Best speed + intelligence balance | $3 / $15 | 200K (1M beta) | 64K |
| Haiku 4.5 | claude-haiku-4-5-20251001 |
Near-frontier intelligence, fastest | $1 / $5 | 200K | 64K |
All Claude 4 models support:
- Extended thinking
- Vision (images)
- Tool use
- Priority Tier access
Opus 4.6 and Sonnet 4.6 additionally support:
- Adaptive thinking (dynamic reasoning depth)
- 1M token context window (beta, via
context-1m-2025-08-07header — long context pricing applies beyond 200K)
AWS Bedrock IDs: anthropic.claude-opus-4-6-v1, anthropic.claude-sonnet-4-6
GCP Vertex AI IDs: claude-opus-4-6, claude-sonnet-4-6
Model Tiers
| Tier | Models | Best For | Relative Cost |
|---|---|---|---|
| Frontier | Claude Opus 4.6, GPT-5.2/5.3/Codex, o3, o1-pro | Complex reasoning, architecture, novel problems | $$$$$ |
| Capable | Claude Sonnet 4.6, GPT-5.1/Codex, GPT-4.1, GPT-4o, Gemini 2.5/3 Pro, o4-mini | Most coding tasks, refactoring, debugging | $$$ |
| Efficient | Claude Haiku 4.5, GPT-5 mini, GPT-4.1 mini/nano, GPT-4o mini, Gemini 2.5 Flash, Gemini 3 Flash | Simple edits, formatting, boilerplate | $ |
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.
- 8d ago First seen · 218 lines · 21 tokens per session scan A bbe8fbebd9cd
llm-model-selection is a skill published in the GitHub repository fabioc-aloha/Alex_Skill_Mall (4 stars, last pushed today), licensed MIT. It adds 21 tokens to every session and 2,199 once invoked, about $0.0001 per session on Opus 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 2026-09-03.
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