Generate an answer grounded in selected documents by calling the frozen Executor Model through the runtime context. Use as the final generator in Agentic RAG workflows.
Scanned 9/1/2026
Install to Claude Code
npx -y skills add DocAILab/Agentic-RAG-Skill --skill component-grounded-generator --agent claude-codeInstalls into .claude/skills of the current project.
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---
name: component-grounded-generator
description: Generate an answer grounded in selected documents by calling the frozen Executor Model through the runtime context. Use as the final generator in Agentic RAG workflows.
---
# Grounded Generator Component
Provide the `generator` capability for an Agentic RAG slot.
## Interface
Input `GenerationRequest`:
- `query`: non-empty original question
- `documents`: selected evidence documents. Each document must contain non-empty
`id` and `text`; an empty sequence is allowed and is rendered as
`[No evidence supplied]`.
- optional `max_tokens`: forwarded to the frozen Executor Model
Output `GenerationResult`:
- `answer`: non-empty generated grounded answer. Leading and trailing whitespace
from the model response is stripped.
## Execution
Run `scripts/component.py:run(inputs, context)`. The runtime must provide the
frozen `context.call_model(...)`. The component formats the supplied evidence,
calls the model with `temperature=0.0`, and rejects malformed inputs or empty
model responses. Do not retrieve documents, rerank documents, or modify model
parameters.
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