daa_agent_adapt
Trigger agent adaptation based on feedback Use when native Task is wrong because you need agents that adapt their cognitive pattern (convergent / divergent / lateral / systems / critical) per-task and share knowledge across the swarm. For static one-shot agents, native Task is fine.
This record as markdown: /tools/ruflo/daa-agent-adapt.md
What daa_agent_adapt does on Ruflo
AI agents invoke daa_agent_adapt to trigger actions in Ruflo. What it does depends on the arguments the agent supplies, and its effects often reach beyond the immediate call: builds kicked off, notifications sent, workflows started.
Why daa_agent_adapt is rated High
This is Execute rather than Write because it triggers an autonomous process (agent adaptation) whose effects propagate through a multi-agent swarm system. While reversible, the tool invokes external operations whose outcomes depend on feedback and task context.
From the tool's definition Tool triggers 'agent adaptation based on feedback' and modifies 'cognitive pattern' of agents in a swarm system. The description indicates this causes agents to change behavior and 'share knowledge across the swarm' — altering runtime agent state and behavior.
Attacks that exploit this kind of access
The rule that runs daa_agent_adapt 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 daa_agent_adapt, this is the rule to start with:
daa_agent_adapt stays usable, but rate-capped: a runaway agent can't fire it dozens of times 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 daa_agent_adapt call is checked against it from then on.
Questions about daa_agent_adapt
Trigger agent adaptation based on feedback Use when native Task is wrong because you need agents that adapt their cognitive pattern (convergent / divergent / lateral / systems / critical) per-task and share knowledge across the swarm. For static one-shot agents, native Task is fine. It is categorised as a Execute tool in the Ruflo MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Register the Ruflo MCP server in PolicyLayer and add a rule for daa_agent_adapt: 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.
daa_agent_adapt is a Execute tool with high risk. Execute tools should be rate-limited and have argument validation enabled.
Yes. Add a rate_limit block to the daa_agent_adapt 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 daa_agent_adapt. 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.
daa_agent_adapt 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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