output-dev-model-selection

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

• output-dev-prompt-file — overall .prompt file structure
• output-dev-upgrade-prompt-models — bulk-upgrade existing prompts to the latest version of their current family
• output-eval-judge-prompt — judge-specific selection guidance (start small, escalate on TPR/TNR failures)