| name | output-dev-model-selection |
| description | Pick the right LLM model for an Output SDK prompt file. Use when writing a new .prompt file, reviewing a model choice, or upgrading a stale model. Walks through priority (reasoning/balance/speed/cost), provider selection, and a live lookup against the Vercel AI Gateway model index. |
| allowed-tools | ["Bash(curl *)","Bash(jq *)","Read","Glob"] |
Picking a Model for an Output SDK Prompt
This skill is the single source of truth for model selection across Output SDK skills and agents. Other skills link here instead of pinning specific model IDs, because model rosters drift faster than docs.
Live model snapshot
We run this at skill-load time to fetch the 10 most recently released models per provider from the Vercel AI Gateway:
output=$(curl -fsS https://ai-gateway.vercel.sh/v1/models 2>/dev/null | jq '
.data as $models
| {
anthropic: ([ $models[] | select(.id | startswith("anthropic/")) ] | sort_by(.released) | reverse | .[0:10]),
openai: ([ $models[] | select(.id | startswith("openai/")) ] | sort_by(.released) | reverse | .[0:10]),
google: ([ $models[] | select(.id | startswith("google/")) ] | sort_by(.released) | reverse | .[0:10])
}
' 2>/dev/null)
if [ -n "$output" ]; then printf '%s\n' "$output"; else echo "(snapshot unavailable)"; fi
Snapshot Data
output=$(curl -fsS https://ai-gateway.vercel.sh/v1/models 2>/dev/null | jq '
.data as $models
| {
anthropic: ([ $models[] | select(.id | startswith("anthropic/")) ] | sort_by(.released) | reverse | .[0:10]),
openai: ([ $models[] | select(.id | startswith("openai/")) ] | sort_by(.released) | reverse | .[0:10]),
google: ([ $models[] | select(.id | startswith("google/")) ] | sort_by(.released) | reverse | .[0:10])
}
' 2>/dev/null)
if [ -n "$output" ]; then printf '%s\n' "$output"; else echo "(snapshot unavailable)"; fi
Snapshot Fallback
If the block above is empty, the script didn't execute automatically — likely because part of it (jq, curl, or network access) is missing. Query and filter the snapshot yourself before continuing.
Snapshot shape
{
"anthropic": [ <model>, ..., <up to 10> ],
"openai": [ <model>, ..., <up to 10> ],
"google": [ <model>, ..., <up to 10> ]
}
Each <model> is the unmodified gateway payload. Useful fields per model:
| Field | What to use it for |
|---|
id | The provider-prefixed ID (eg anthropic/claude-sonnet-4.6) — translate to prompt-file form (Step 5) |
released | Unix timestamp of release. Snapshot is already sorted newest-first per provider. |
name | Human-readable name |
description | One-paragraph capability summary — read this when comparing similarly-named tiers |
context_window | Max input tokens. Matters when prompts include large context (codebases, long docs) |
max_tokens | Max single-response output tokens |
tags | Capability flags. reasoning, tool-use, vision, file-input, web-search, image-generation, explicit-caching, implicit-caching |
pricing.input / pricing.output | Per-token cost (USD). Multiply by 1,000,000 for "per 1M tokens" |
pricing.input_cache_read | Cached-input price — usually 10× cheaper than input |
type | language for chat models; image models surface as image-generation and aren't valid for .prompt files |
Decision flow
Step 1 — Determine task priority
Pick the first row that fits. If unclear, default to reasoning.
| Priority | Use when |
|---|
| reasoning (default) | Complex multi-step logic, structured output extraction, judges with edge cases, anything where wrong > slow |
| balance | Most generative work — summarization, classification, content drafting, conversation |
| speed | Short interactive responses, low-latency UI loops, simple transforms |
| cost | Bulk batch processing where token spend dominates and quality floor is forgiving |
Step 2 — Determine provider
Scan existing *.prompt files in the workflow (and its siblings under src/workflows/) and tally what provider: they declare.
- If the workflow (or sibling workflows) already use one provider, match it. Mixing providers means the runtime needs API keys for each — operational footgun.
- If no existing prompts, default to
anthropic.
- Only switch provider when the user explicitly asks, or when a feature you need (eg Gemini's
useSearchGrounding, OpenAI's maxToolCalls) is provider-specific.
Step 3 — Map provider name to snapshot key
Output SDK provider: values don't always line up with the snapshot keys, since Vercel groups Gemini under google/:
| Output SDK provider | Snapshot key |
|---|
anthropic | anthropic |
openai | openai |
vertex (Gemini models) | google |
vertex (Claude models) | anthropic (then re-add the @vertex suffix manually) |
bedrock | anthropic (then translate to bedrock namespace manually) |
Step 4 — Pick a model from the provider's list
The list is already sorted newest-first. Walk it top-down and pick the first model whose id matches the tier for your priority.
Skip these by default:
type != "language" (eg gpt-image-2, gemini-embedding-2) — not valid for .prompt files.- IDs containing
preview, alpha, or beta. Use stable / GA models only, even if a newer preview/alpha/beta exists. Only pick a non-stable model when the user explicitly asks for it ("use the preview", "I want the new beta", etc.).
| Priority | Anthropic — match id containing | OpenAI — match id | Google — match id |
|---|
| reasoning | claude-opus- (and tags includes reasoning) | ends with -pro | contains -pro |
| balance | claude-sonnet- | base gpt-N.M (no -mini/-nano/-pro suffix) | contains -pro |
| speed | claude-haiku- | ends with -mini | ends with -flash (not -flash-lite) |
| cost | claude-haiku- | ends with -nano | contains -flash-lite |
Tie-breakers when multiple stable models match:
- Prefer the unversioned alias (
claude-sonnet-4.6) over a dated snapshot (claude-sonnet-4-20250514) unless reproducibility is required (eg eval judges).
- If two truly equivalent rows exist, take the one with the larger
context_window, then lower pricing.input.
If every match in the snapshot is a preview/alpha/beta — meaning the entire tier is in pre-release — surface that to the user and ask before picking one. Don't silently use a preview because it was the only thing available.
Step 5 — Translate the gateway ID into a prompt-file model string
Gateway IDs carry a provider prefix and use dots; prompt-file IDs strip the prefix and use hyphens. Apply two transformations: drop everything up to and including the first /, then replace . with -.
Gateway id | Prompt-file model: |
|---|
anthropic/claude-sonnet-4.6 | claude-sonnet-4-6 |
openai/gpt-5.5 | gpt-5-5 |
google/gemini-3-flash | gemini-3-flash |
Drop the translated string into your .prompt frontmatter:
---
provider: anthropic
model: claude-sonnet-4-6
temperature: 0.7
maxTokens: 4096
---
See also
