brainstorming
brainstorming
You MUST use this before any creative work - creating features, building components, adding functionality, modifying behavior, or planning anything new, in software or out of it (a talk, a business, a renovation).
task-execution-providers-toolsConfigure Kiln task execution through LiteLLM providers, structured outputs, prompts, built-in tools, skills, Kiln task tools, RAG tool references, and MCP tool sessions.
Independent GitHub snapshot · Automated classification · Original documentation governs
Use this sub-skill when the task is about choosing a Kiln model/provider, building a task run configuration, invoking adapter_for_task, adding tool IDs to a run, diagnosing adapter errors, or explaining how Kiln maps prompts, structured outputs, thinking levels, skills, and MCP tools into model calls.
KilnAgentRunConfigProperties, McpRunConfigProperties, ToolsRunConfig, adapter_for_task, provider/model registry questions, custom OpenAI-compatible models, structured output modes, thinking levels, prompt builder IDs, built-in tool IDs, KilnToolInterface, MCP tool IDs/sessions, skill tool routing, and Kiln task tools..kiln save/load, packaging, and schema persistence to the project-datamodel sub-skill.RagTool is exposed to task execution.KilnToolInterface, built-in tools, skills, Kiln task tools, RAG tool routing, MCP IDs, and MCP session behavior, read references/tools-skills-and-mcp.md.Use scripts/inspect_kiln_models.py to inspect installed Kiln model/provider registries without calling external providers:
python scripts/inspect_kiln_models.py
python scripts/inspect_kiln_models.py --provider openai --limit 20
python scripts/inspect_kiln_models.py --provider openai --json
The script imports registries and prints counts/provider coverage only. It does not call model APIs, Ollama, Docker Model Runner, MCP servers, or paid services.
This sub-skill is distilled from repo-relative evidence in libs/core/kiln_ai/datamodel/run_config.py, libs/core/kiln_ai/datamodel/tool_id.py, libs/core/kiln_ai/adapters/adapter_registry.py, libs/core/kiln_ai/adapters/provider_tools.py, libs/core/kiln_ai/adapters/ml_model_list.py, libs/core/kiln_ai/adapters/ml_embedding_model_list.py, libs/core/kiln_ai/adapters/reranker_list.py, libs/core/kiln_ai/adapters/prompt_builders.py, libs/core/kiln_ai/adapters/model_adapters/, libs/core/kiln_ai/tools/, and libs/core/kiln_ai/utils/config.py, plus adapter/tool tests. Verified package evidence covered kiln-ai, kiln-server, and kiln-studio-desktop 1.0.4.