score_compounding
Compute the full 8-dimension trajectory score for an entity. Returns trust-adjusted compounding, drift, adaptation velocity, and all sub-scores with explanations. Output includes TrajectoryScoreBreakdown and TrajectorySummaryData.
This record as markdown: /tools/io-github-homenshum-nodebench/score-compounding.md
What score_compounding does on Nodebench
AI agents call score_compounding to retrieve information from Nodebench without modifying anything. It is typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
Why score_compounding is rated Low
This is a pure computation and analysis tool that calculates metrics for an entity and returns structured score breakdowns. It retrieves or derives analytical results without modifying state, triggering external operations, or causing irreversible changes. No evidence of write, delete, execute, or financial operations.
From the tool's definition Tool 'score_compounding' computes and returns scoring data ('Compute the full 8-dimension trajectory score', 'Returns trust-adjusted compounding, drift, adaptation velocity, and all sub-scores').
Attacks that exploit this kind of access
The rule that runs score_compounding safely
PolicyLayer is an MCP gateway: it sits between your AI agents and Nodebench, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For score_compounding, this is the rule to start with:
score_compounding 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 Nodebench, apply this rule, and every score_compounding call is checked against it from then on.
Questions about score_compounding
Compute the full 8-dimension trajectory score for an entity. Returns trust-adjusted compounding, drift, adaptation velocity, and all sub-scores with explanations. Output includes TrajectoryScoreBreakdown and TrajectorySummaryData. It is categorised as a Read tool in the Nodebench MCP Server, which means it retrieves data without modifying state.
Register the Nodebench MCP server in PolicyLayer and add a rule for score_compounding: 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 Nodebench. Nothing to install.
score_compounding 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 score_compounding 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 score_compounding. 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.
score_compounding is provided by the Nodebench MCP server (nodebench-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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