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LLM Profiles

Per-model tuning profiles that make AI agents call tools reliably across very different models. Tool-call reliability and the right sampling parameters vary a lot by model (first-attempt tool-call success ranges roughly Qwen ~94% > GLM ~91% > DeepSeek ~87%, and each family ships different recommended temperatures), so one global setting can never fit them all. A profile matches a provider/model and supplies the right knobs.

Built for Skales, usable as a plain data format anywhere.

What a profile tunes

  • maxTools - cap the number of tools offered (helps models that choke on a big tool set).
  • compactionLevel - prompt compaction floor (0 full, 1 compact, 2 minimal).
  • promptHint - an instruction prepended to the system prompt: per-model guidance (decisiveness, grounding) plus the library's shared voice rules (act in the same turn you announce a tool, answer like a colleague, no filler or fake knowledge-cutoff disclaimers, check context before asking).
  • params - sampling: temperature, top_p, top_k.
  • toolCallStyle - advisory: native | json | xml.
  • toolHints - per-tool notes that teach a model your exact tool names (keyed by the real tool name), for models that reach for another framework's names like create_file or bash. Look the names up in TOOLS.md.

Frontier models (Claude, GPT, Gemini) intentionally have no profile here and run unchanged. Profiles target the models that benefit: weaker, local, or quirky.

Profiles in this library

Profile Matches Why
DeepSeek deepseek V3-era / R1 / local distills: low temp + explicit tool-name hints for reliable multi-tool calling.
DeepSeek V4 deepseek-v4 Agent-grade (V4 / Flash / Pro); vendor params (temp 1.0, top_p 1.0), no tool cap (it drives the full catalogue).
Qwen qwen Qwen2.5 / Qwen3: strong native tool-caller; vendor non-thinking params.
Qwen 3.5 qwen3.5 Vendor params moved to temp 1.0, top_p 0.95, top_k 20.
MiniMax minimax Agentic tool-caller (M2.7 / M3); vendor params (temp 1.0, top_p 0.95, top_k 40), no tool cap (it drives the full catalogue).
GLM glm Solid tool-caller (4.x / 5); GLM-5 agentic-eval params (temp 0.7, top_p 0.95).
Kimi kimi Over-deliberates; instant-mode params (temp 0.6, top_p 0.95) + hint to act decisively.
Mistral mistral Low vendor temp; good for structured output.
Devstral devstral Mistral's 24B coding/agent model (matched no profile before); low deterministic temp + a coding-agent hint (edit precisely, verify with tests).
Gemma gemma Lower temp + compact prompt for reliable tool use.
Llama llama Vendor params.
Phi phi Verbose tool-caller; low temp + compact prompt.
GPT-OSS gpt-oss Strong native tool-caller for its class; decisive turns.
Nemotron nemotron NVIDIA Nemotron-3 (ultra / nano); middle-ground sampling so it gets the same per-model tuning as every other family.
Small model *b (<= ~9B ids) Compact prompt for tiny models (tool set is trimmed by the host's local-model setting, not the profile).

How Skales uses them

In Skales: Settings → LLM Profiles (its own card, next to AI Providers) or the dedicated /profiles page (opt-in). The most specific match wins (longest literal pattern, provider pinned); an imported profile outranks a built-in at equal specificity, so you can override one. Import a profile by file, by pasting JSON, or by URL - point it at a raw file in this repo (from Skales v11.3.2 a normal GitHub file link works too; it is rewritten to the raw file automatically). index.json is a manifest so a client can list and fetch the current set and stay up to date as profiles are added.

Schema

See SCHEMA.md. A profile is a small JSON file; the format is kept deliberately simple so a profile is easy to write, review, and share.

Safety

A profile is data, not code, but promptHint and toolHints are injected into the model's system prompt, so an untrusted profile is a prompt-injection vector. Import only from sources you trust; Skales shows exactly what a profile injects before you rely on it, clamps params to sane ranges, and bounds the importer. See the Safety section in SCHEMA.md.

Contributing

Profiles are community-extensible. Add or improve one via PR, see CONTRIBUTING.md. Keep entries vendor-grounded (cite the source for params) and conservative (do not over-tune a capable model).

License

The profile data here is provided for use with Skales and compatible tools. Skales is BSL-1.1. These profiles are configuration data, not Skales source.

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LLM Profiles. Per-model tuning profiles that make AI agents call tools reliably across very different models.

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