ruvllm_generate_config
Create a generation config (maxTokens, temperature, topP, etc.) as JSON. Use when sending every prompt to the Anthropic API is wrong because you need local inference — air-gapped environments, MicroLoRA-fine-tuned per-task adapters, or sub-cent per-call cost. For general Claude work native Task i...
This record as markdown: /tools/ruflo/ruvllm-generate-config.md
What ruvllm_generate_config does on Ruflo
AI agents use ruvllm_generate_config to create or update resources in Ruflo, usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your Ruflo environment.
Why ruvllm_generate_config is rated Medium
This tool creates configuration objects that control LLM inference behavior. While it doesn't directly access sensitive data (Read), execute arbitrary code (Execute), delete anything (Destructive), or move money (Financial), it does modify inference parameters that could be misused to alter model behavior in unexpected ways—e.g., setting extreme temperature values to cause incoherent outputs, or crafting configs…
From the tool's definition Tool creates and generates configuration objects (maxTokens, temperature, topP, etc.) as JSON. Description explicitly states 'Create a generation config' and mentions use for 'local inference' scenarios.
Risk signalsBulk/mass operation — affects multiple targets
Attacks that exploit this kind of access
The rule that runs ruvllm_generate_config safely
PolicyLayer is an MCP gateway: it sits between your AI agents and Ruflo, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For ruvllm_generate_config, this is the rule to start with:
ruvllm_generate_config stays usable, but capped: an agent stuck in a loop can't make hundreds of changes a minute. Everything else on the server is denied unless you say otherwise.
The button opens the PolicyLayer dashboard: create your workspace, connect Ruflo, apply this rule, and every ruvllm_generate_config call is checked against it from then on.
Questions about ruvllm_generate_config
Create a generation config (maxTokens, temperature, topP, etc.) as JSON. Use when sending every prompt to the Anthropic API is wrong because you need local inference — air-gapped environments, MicroLoRA-fine-tuned per-task adapters, or sub-cent per-call cost. For general Claude work native Task is the right call. It is categorised as a Write tool in the Ruflo MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.
Register the Ruflo MCP server in PolicyLayer and add a rule for ruvllm_generate_config: allow, deny, rate-limit, or require approval. Point your MCP client at the PolicyLayer proxy URL and the rule is enforced on every call, before it reaches Ruflo. Nothing to install.
ruvllm_generate_config is a Write tool with medium risk. Write tools should be rate-limited to prevent accidental bulk modifications.
Yes. Add a rate_limit block to the ruvllm_generate_config rule in your PolicyLayer policy. For example, setting max: 10 and window: 60 limits the tool to 10 calls per minute. Rate limits are tracked per agent session and reset automatically.
Set action: deny in the PolicyLayer policy for ruvllm_generate_config. The AI agent will receive a policy violation error and cannot call the tool. You can also include a reason field to explain why the tool is blocked.
ruvllm_generate_config is provided by the Ruflo MCP server (ruvnet/ruflo). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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