pillar_dca_leaderboard
View the DCA streak leaderboard. Shows top partnerships by streak length, and highlights your entry if you have one.
This record as markdown: /tools/io-github-aibtcdev-mcp-server/pillar-dca-leaderboard.md
What pillar_dca_leaderboard does on Aibtc
AI agents call pillar_dca_leaderboard to retrieve information from Aibtc without modifying anything. It is typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
Why pillar_dca_leaderboard is rated Low
This tool retrieves and displays leaderboard information (top partnerships, streak lengths, and user entry) without creating, modifying, deleting, or executing operations. It is purely informational and has no capability to alter state or trigger external operations. Blast radius from misuse is minimal—an AI agent can only display information that already exists.
From the tool's definition Tool name 'pillar_dca_leaderboard' and description 'View the DCA streak leaderboard. Shows top partnerships by streak length, and highlights your entry if you have one.' indicate a read-only query operation that retrieves and displays leaderboard data without…
Attacks that exploit this kind of access
The rule that runs pillar_dca_leaderboard safely
PolicyLayer is an MCP gateway: it sits between your AI agents and Aibtc, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For pillar_dca_leaderboard, this is the rule to start with:
pillar_dca_leaderboard is read-only, so it stays allowed. Everything else on the server is denied unless you say otherwise.
The button opens the PolicyLayer dashboard: create your workspace, connect Aibtc, apply this rule, and every pillar_dca_leaderboard call is checked against it from then on.
Questions about pillar_dca_leaderboard
View the DCA streak leaderboard. Shows top partnerships by streak length, and highlights your entry if you have one. It is categorised as a Read tool in the Aibtc MCP Server, which means it retrieves data without modifying state.
Register the Aibtc MCP server in PolicyLayer and add a rule for pillar_dca_leaderboard: 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 Aibtc. Nothing to install.
pillar_dca_leaderboard is a Read tool with low risk. Read-only tools are generally safe to allow by default.
Yes. Add a rate_limit block to the pillar_dca_leaderboard 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 pillar_dca_leaderboard. 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.
pillar_dca_leaderboard is provided by the Aibtc MCP server (aibtcdev/aibtc-mcp-server). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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