explain_delx_rewards
Start here. Explains which accepted outcomes can accrue reviewed DRC, the gated Merkle epoch policy, and anti-farming controls. Free - your first call in the rewards flow. Free Delx Protocol tool.
This record as markdown: /tools/io-github-davidmosiah-delx-mcp-a2a/explain-delx-rewards.md
What explain_delx_rewards does on Delx Mcp A2a
AI agents invoke explain_delx_rewards to trigger actions in Delx Mcp A2a. 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.
| Parameter | Type | Required | Description |
|---|---|---|---|
agent_id | string | — | Optional agent id to tailor next actions |
agent_token | string | — | Optional token; when valid, includes private reward status for this agent |
Parameters from the server's own tool schema.
Why explain_delx_rewards is rated High
explain_delx_rewards triggers real processes with real consequences. An agent gone sideways doesn't fire it once. It starts dozens of builds, sends mass notifications, or burns through compute before anyone looks up.
Attacks that exploit this kind of access
The rule that runs explain_delx_rewards safely
PolicyLayer is an MCP gateway: it sits between your AI agents and Delx Mcp A2a, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For explain_delx_rewards, this is the rule to start with:
explain_delx_rewards 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 Delx Mcp A2a, apply this rule, and every explain_delx_rewards call is checked against it from then on.
Questions about explain_delx_rewards
Start here. Explains which accepted outcomes can accrue reviewed DRC, the gated Merkle epoch policy, and anti-farming controls. Free - your first call in the rewards flow. Free Delx Protocol tool. It is categorised as a Execute tool in the Delx Mcp A2a MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
explain_delx_rewards accepts 2 parameters: agent_id, agent_token. The full parameter table on this page comes from the server's own tool schema.
Register the Delx Mcp A2a MCP server in PolicyLayer and add a rule for explain_delx_rewards: 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 Delx Mcp A2a. Nothing to install.
explain_delx_rewards 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 explain_delx_rewards 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 explain_delx_rewards. 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.
explain_delx_rewards is provided by the Delx Mcp A2a MCP server (https://api.delx.ai/v1/mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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