agenthub-models
Call model APIs through @prismshadow/agenthub — streaming text generation, image generation, speech synthesis, embeddings and the supported-model registry with one client.
git clone --depth 1 https://github.com/Prism-Shadow/penguin-harness /tmp/agenthub-models && cp -r /tmp/agenthub-models/packages/skills/skills/agenthub-models ~/.claude/skills/agenthub-modelsSKILL.md
# AgentHub Model APIs
`@prismshadow/agenthub` is a unified TypeScript client for model APIs: streaming text, image generation, speech synthesis and embeddings behind one entry point.
```bash
npm install @prismshadow/agenthub
```
The main entry point is `AutoLLMClient`:
```ts
import { AutoLLMClient } from "@prismshadow/agenthub";
const client = new AutoLLMClient({ model: "<model_id>", apiKey: "<key>", baseUrl: "<url>", clientType: "<type>" });
```
`apiKey`, `baseUrl` and `clientType` are optional (see routing below). The package also exports `listSupportedModels` (the model registry) and the error classes `AgentHubError`, `UnsupportedParameterError`, `EmptyResponseError` and `ToolCallArgumentParseError`.
## Before you start
If the user's message only invokes this skill (e.g. "use agenthub-models skill") without a concrete task, ask the user what they want to build. Do not write code until the requirement is clear.
**Important prerequisite — set the key up first, then develop.** When the script is an AI app you are building for the user, have them add the model API key in **this agent's key vault** (gear icon on its card, Agents page → settings → key vault tab) *before* you start, so the credential is in your shell environment. If the app stores its own model config, keep its Penguin data root **inside the CWD workspace** (`--root ./penguin_data`), never `~/.penguin`. Model ids can come from the penguin CLI catalog and the id table below.
Check for a usable API key before writing code — the client needs one for whichever provider you target:
```bash
env | grep -oE "(DEEPSEEK|OPENAI|ANTHROPIC|GEMINI|ZAI|MOONSHOT|MINIMAX)_API_KEY" || echo none
```
Vault keys also appear in your Vault Keys section. **Only two sources count as a usable key**: a vault-injected environment variable (the check above), or — when the app stores its own model config — a key already configured in the app's own data root (`penguin config model list --root <data_dir>`). Keys living in the global `~/.penguin` or any other `.penguin` directory do **not** count — a bare `penguin config model list` (no `--root`) reads the global store, because the CLI defaults to the global root unless `--root` is given, so a key showing up there proves nothing for your script and must never be used or copied.
If neither counted source yields a usable key, **stop immediately and ask the user to configure one — do not write code, and do not keep calling tools to retry**: ask them to add one in the agent's **key vault** (gear icon on the agent's card, Agents page → settings → key vault tab); vault values reach your shell environment on the next task. Re-checking the environment or the vault in a loop just wastes turns — one clear check, then hand back to the user.
Keep model API keys **project-local**: for an app that stores its own model config, write the key into the project under the working directory with the penguin CLI, **always passing `--root <data_dir>` for a directory inside the current working directory** (`penguin config model add --root ./penguin_data --provider <group> --model-id <id> --api-key <key>`) — without `--root` it writes to the global `~/.penguin/data` instead. `--provider` is required alongside `--model-id`: a model entry is the `(provider, model_id)` pair and the group is never inferred (use `custom` for an endpoint outside the built-in groups). Otherwise rely on vault-injected environment variables. Never read, copy or fall back to model keys stored in the user's global `~/.penguin` directory — that config belongs to the person running Penguin, not to your script.
## Model IDs
Use exact model ids. If an id is not in the table below and the user has not given one, ask the user to confirm the exact id before writing code.
| Family | Official IDs | Gateway variants |
| ---------------- | --------------------------------------------------------------------- | ----------------------------------------------------------------------------------------------------------------------------------------------- |
| Gemini 3.7 | `gemini-3.7-flash` | OpenRouter `google/gemini-3.7-flash` |
| Gemini 3.6 | `gemini-3.6-flash`, `gemini-3.5-flash-lite` | — |
| Gemini 3 | `gemini-3.1-pro-preview`, `gemini-3.5-flash`, `gemini-3.1-flash-lite` | — |
| Gemini 3 image | `gemini-3.1-flash-image`, `gemini-3-pro-image-preview` | — |
| Gemini 3 TTS | `gemini-3.1-flash-tts-preview` | — |
| Gemini embedding | `gemini-embedding-2` | — |
| Claude 5 | `claude-fable-5`, `claude-opus-5`, `claude-sonnet-5` | OpenRouter `anthropic/claude-fable-5`, `anthropic/claude-opus-5`, `anthropic/claude-sonnet-5` |
| Claude 4 | `claude-sonnet-4-6`, `claude-opus-4-7`, `claude-Use when developing PenguinHarness itself — changing packages/{core,server,web,cli,desktop,landing,docs,skills}, the built-in model catalog, the installers or the release workflow; writing or auditing changelog entries; writing a blog post or capturing release screenshots; deciding what to do about data already on disk; or auditing prose that reads like a leaked authoring session. Covers the two-repo symlink layout, the CI-parity verification chain, the record-and-ship contract, where blog media is hosted, and the seams that are intentional.
Use when changing the PenguinHarness Web App (`packages/web`) — adding or restyling any UI, picking a status colour, adding an icon, laying out a row or a form field, writing user-facing copy, or building a popup. Covers the semantic tone tokens, the icon size/stroke/gap scale, the semantic-versus-formatting rule for explanatory text, the two-dictionary i18n contract, and the portal-panel pattern with its Esc and scroll caveats.
Run one specified Test Agent on one specified Benchmark Case exactly once, privately score that execution, and return one protocol result.
Initialize an Agent's settings from a user requirement by writing AGENTS.md, setting identity metadata, and installing only needed Skills.