# Tokenlab Model Picker

> Pick TokenLab models for chat, coding, image, video, audio, embeddings, reranking, and translation by reading public model catalog signals before recommending concrete model IDs.

- **Type:** Skill
- **Install:** `agentstack add skill-hedging8563-tokenlab-skills-tokenlab-model-picker`
- **Verified:** Yes — security-reviewed for prompt injection and unsafe behavior
- **Seller:** [hedging8563](https://agentstack.voostack.com/s/hedging8563)
- **Installs:** 0
- **Category:** [AI & ML](https://agentstack.voostack.com/c/ai-and-ml)
- **Latest version:** 0.1.0
- **License:** MIT
- **Upstream author:** [hedging8563](https://github.com/hedging8563)
- **Source:** https://github.com/hedging8563/tokenlab-skills/tree/main/skills/tokenlab-model-picker
- **Website:** https://tokenlab.sh

## Install

```sh
agentstack add skill-hedging8563-tokenlab-skills-tokenlab-model-picker
```

Requires the [AgentStack CLI](https://agentstack.voostack.com/docs/cli). Works with Claude Code, Cursor, and any MCP-compatible agent.

## About

# TokenLab Model Picker

Use this skill when a user asks which TokenLab model to use, how to compare model options, or how to route a workload across model families.

## What this skill should deliver

- A short model shortlist with exact TokenLab model IDs.
- The workload assumptions used to pick the models.
- A public catalog lookup path that the user or agent can rerun.
- A fallback model when the first choice is unavailable or too expensive.
- A caveat when a recommendation depends on volatile pricing, availability, or benchmark data.

## Preferred approach

1. Identify the workload: chat, coding, agent loop, image, video, audio, embedding, rerank, translation, or multimodal.
2. Use the public model catalog before recommending hardcoded IDs:
   - General catalog: `GET https://api.tokenlab.sh/v1/models`
   - Task shortlist: `GET https://api.tokenlab.sh/v1/models?recommended_for=`
   - Model contract: `GET https://api.tokenlab.sh/v1/models/:model`
   - Pricing detail: `GET https://api.tokenlab.sh/v1/models/:model/pricing`
3. Prefer exact public model IDs over family names.
4. Separate recommendation dimensions:
   - quality or frontier capability
   - cost sensitivity
   - latency or fast iteration
   - native endpoint needs
   - multimodal input or output
5. Return a compact table, then one runnable API example if useful.

## Default shortlist patterns

- Coding and agent work: choose a strong reasoning/coding model, a cheaper fallback, and a fast iteration model.
- General chat: choose one balanced model and one lower-cost fallback.
- Image or video: use `recommended_for=image` or `recommended_for=video` instead of guessing request shapes.
- Embeddings, rerank, translation, TTS, STT, music, or 3D: use the task-specific shortlist and inspect the model contract before showing parameters.

## Output format

- One sentence naming the workload assumptions.
- A table with `Use`, `Model ID`, `Why`, and `Fallback`.
- One catalog command the user can rerun.
- One warning line if availability, pricing, or provider-native behavior must be verified.

## Avoid

- Do not claim a single universal best model.
- Do not recommend provider-prefixed or physical route names as public model IDs.
- Do not invent prices or model counts.
- Do not silently translate a native-only need into a generic chat completion.
- Do not recommend a model that is absent from the current public catalog.

## Edge Cases

- If the user asks for the cheapest option, still include capability limits.
- If the user asks for a benchmark winner, require a cited benchmark and observed date.
- If the catalog is unavailable, say so and fall back to the last known examples only as examples, not truth.

## Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

- **Author:** [hedging8563](https://github.com/hedging8563)
- **Source:** [hedging8563/tokenlab-skills](https://github.com/hedging8563/tokenlab-skills)
- **License:** MIT
- **Homepage:** https://tokenlab.sh

Install and usage instructions live in the source repository linked above.

## Pricing

- **Free** — Free

## Security capabilities

Automated source analysis of v0.1.0 — what this tool can access:

- **Network access:** no
- **Filesystem access:** no
- **Shell / process execution:** no
- **Environment & secrets:** no
- **Dynamic code execution:** no

*"Yes" means the capability is present in the source — more access means more to trust, not that it is unsafe.*


## Versions

- **0.1.0** — security scan: passed — Imported from the upstream source.

## Links

- Listing page: https://agentstack.voostack.com/l/skill-hedging8563-tokenlab-skills-tokenlab-model-picker
- Seller: https://agentstack.voostack.com/s/hedging8563
- Browse the marketplace: https://agentstack.voostack.com/browse

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Listed on AgentStack — the marketplace for AI agent skills and MCP servers. Every listing is security-reviewed. Creators keep 70%.