daa_knowledge_share
Share knowledge between agents 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/io-github-ruvnet-claude-flow/daa-knowledge-share.md
What daa_knowledge_share does on Claude Flow
AI agents use daa_knowledge_share to create or update resources in Claude Flow, usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your Claude Flow environment.
Why daa_knowledge_share is rated Medium
The tool writes/propagates knowledge state across multiple agents in the swarm. It modifies the cognitive/knowledge state of agents, which is a reversible write operation. It does not execute code, delete data, or involve financial transactions. Misuse could corrupt shared knowledge across the swarm, giving it a medium severity.
From the tool's definition 'Share knowledge between agents' and 'share knowledge across the swarm' — the tool creates/transmits data between agents in the swarm.
Attacks that exploit this kind of access
The rule that runs daa_knowledge_share safely
PolicyLayer is an MCP gateway: it sits between your AI agents and Claude Flow, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For daa_knowledge_share, this is the rule to start with:
daa_knowledge_share 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 Claude Flow, apply this rule, and every daa_knowledge_share call is checked against it from then on.
Questions about daa_knowledge_share
Share knowledge between agents 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 Write tool in the Claude Flow MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.
Register the Claude Flow MCP server in PolicyLayer and add a rule for daa_knowledge_share: 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 Claude Flow. Nothing to install.
daa_knowledge_share 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 daa_knowledge_share 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_knowledge_share. 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_knowledge_share is provided by the Claude Flow MCP server (claude-flow). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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