Fill Model Descriptions
Goal
Replace empty description: "" strings in packages/llm-info/data/models.yml with concise, accurate one-sentence summaries sourced from OpenRouter first, then provider documentation as a fallback.
Scope and Contract
- Only modify entries where
descriptionis the empty string. Existing non-empty descriptions are human-curated; never overwrite them. - The file is a top-level YAML map keyed by provider id (
anthropic:,openai:, …). Each provider's value is an array of model entries. - Do not modify any other field, reorder entries, or change formatting (flow-style arrays like
roles: [chat, edit], blank lines between entries, blank line between provider sections). - This skill requires network access.
Workflow
Read
packages/llm-info/data/models.yml. Parse it with theyamllibrary'sparseDocument(NOTparse) so formatting and comments are preserved on write-back.Collect every entry where
descriptionis the empty string. Track them as{ provider, model }pairs.Source descriptions in this priority order:
a. OpenRouter —
GET https://openrouter.ai/api/v1/models(no auth required). Build a lookup keyed by lowercasedid. For each{ provider, model }, try candidates in this order:${vendor}/${model}wherevendorcomes from the Vendor Map below.${vendor}/${model.replaceAll('-', '.')}(some OR ids use.separators, e.g.claude-3.5-sonnet).- For Bedrock entries with region/alias prefixes (
us.,eu.,jp.,global.,anthropic.,minimax.,mistral.,zai.,nvidia.), strip the prefix and retry with the appropriate vendor. - For Google entries with
@defaultsuffix (e.g.claude-opus-4-7@default), strip the suffix and tryanthropic/${rest}.
b. Provider docs — if no OpenRouter hit, search the canonical provider's docs page (anthropic.com/news, platform.openai.com/docs/models, ai.google.dev/gemini-api/docs/models, mistral.ai/news, x.ai/blog, etc.) for the model's one-line summary. Use the
WebSearchorWebFetchtool.c. Skip — if neither source has a confident answer, leave
description: ""and record the{ provider, model }for the final summary. Empty is better than wrong.Truncate each sourced description per the rules in the "Truncation" section.
Write the YAML back using targeted
Pairmutations on the parsedDocument, not text replacement. Reference implementation:packages/llm-info/src/sync-models.tsshows how to load a Document, mutate sequence/map nodes, and stringify with{ lineWidth: 0, flowCollectionPadding: false }to preserve formatting.Validate by running:
pnpm --filter @marimo-team/llm-info testThe
schema.test.tstest will catch any structural drift.Report to the user:
- How many entries got descriptions.
- How many were skipped (with the provider/model list).
Vendor Map
OpenRouter id vendor prefixes for each marimo provider:
| Marimo provider | OpenRouter vendor prefix | Notes |
|---|---|---|
anthropic |
anthropic |
Direct match in most cases |
openai |
openai |
Direct match |
google |
google |
Strip @default suffix if present |
mistral |
mistralai |
Note the ai suffix |
xai |
x-ai |
Hyphenated |
azure |
openai |
Azure mostly re-exposes OpenAI models |
bedrock |
varies | Strip region prefix (us./eu./jp./global.) and use the embedded vendor (anthropic.foo → anthropic/foo) |
github |
varies | Ids like openai/gpt-4.1 carry the vendor; strip the github layer |
openrouter |
embedded in id | Ids like anthropic/claude-opus-4.7-fast already carry the vendor |
wandb |
embedded in id | Ids like deepseek-ai/DeepSeek-V3.1; the prefix is the vendor |
opencode-go |
rarely on OR | Source from provider docs |
ollama |
not on OR | Source from the Ollama model card |
Truncation
- One sentence. Split on
.and take the first. Strip trailing whitespace and any markdown formatting (**,_, backticks). - Hard cap at 200 characters. If the first sentence is longer, cut at the last word boundary before 200 and append
…. - Strip leading articles for consistency: prefer "Frontier reasoning model optimized for…" over "This is a frontier reasoning model optimized for…".
- Prefer capability statements over marketing. If OpenRouter gives "the best model from X" but the provider docs give "optimized for tool use and long-context reasoning", prefer the latter.
Examples
Good (matches the tone of existing hand-curated entries):
Latest Opus model, strongest for coding and long-running professional tasksMost capable Sonnet-class model, with frontier performance across coding, agents, and professional workLightweight Gemma model trained by Google, designed to run on a single GPUMultimodal Mixture-of-Experts model optimized for complex tool use and reasoning
Bad (do not produce these):
Claude 3.5 Sonnet delivers better-than-Opus capabilities, faster-than-Sonnet speeds, at the same Sonnet prices. Sonnet is particularly good at coding, vision…— too long, contains marketingThe best model from Anthropic— vague, no information contentAn AI model— useless**Claude 3.5 Sonnet** is a _frontier_ model…— markdown not stripped
Quick Reference
- Data file:
packages/llm-info/data/models.yml - Schema:
packages/llm-info/src/index.ts(AiModelinterface) - YAML write reference:
packages/llm-info/src/sync-models.ts(buildEntryNode,addProviderSection) - OpenRouter API:
https://openrouter.ai/api/v1/models(public, no auth) - Validation:
pnpm --filter @marimo-team/llm-info test
Source: marimo-team/marimo — distributed by TomeVault.