college_value_score
One-call 'is this degree worth the cost' read for a US college (and optionally a named program). Joins the College Scorecard / IPEDS education domain (average net price, six-year completion rate, median earnings ten years after entry, and - when a program is named - program-level median debt and ...
This record as markdown: /tools/io-github-blackboxfoundry-livedatalink/college-value-score.md
What college_value_score does on Livedatalink
AI agents call college_value_score to retrieve information from Livedatalink without modifying anything. It is typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
| Parameter | Type | Required | Description |
|---|---|---|---|
state | string | — | Optional 2-letter state to disambiguate the school name (e.g. 'OH'). |
college | string | Yes | US college/university name (e.g. 'University of Michigan', 'Ohio State University'). |
program | string | — | Optional program name or CIP prefix (e.g. 'Nursing', 'Computer Science') to add program-level debt-vs-earnings evidence. |
Parameters from the server's own tool schema.
Why college_value_score is rated Low
Even though college_value_score only reads data, uncontrolled read access leaks sensitive information and racks up API costs: an agent caught in a retry loop can make thousands of calls a minute without anyone noticing.
Attacks that exploit this kind of access
The rule that runs college_value_score safely
PolicyLayer is an MCP gateway: it sits between your AI agents and Livedatalink, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For college_value_score, this is the rule to start with:
college_value_score 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 Livedatalink, apply this rule, and every college_value_score call is checked against it from then on.
Questions about college_value_score
One-call 'is this degree worth the cost' read for a US college (and optionally a named program). Joins the College Scorecard / IPEDS education domain (average net price, six-year completion rate, median earnings ten years after entry, and - when a program is named - program-level median debt and 1-year earnings) with a keyless BLS wage context (CES average hourly earnings, annualized) to place those earnings against the broad US private-sector wage. Returns a plain read - STRONG VALUE / FAIR / WEAK VALUE / INSUFFICIENT DATA - with the cost-vs-earnings evidence itemized and each sub-signal scored. A source that fails is noted, not fatal. Premium cross-source synthesis; Scorecard earnings cover federally-aided students only and lag by years. Informational only, not admissions, financial, or career advice. It is categorised as a Read tool in the Livedatalink MCP Server, which means it retrieves data without modifying state.
college_value_score accepts 3 parameters: state, college, program. Required: college. The full parameter table on this page comes from the server's own tool schema.
Register the Livedatalink MCP server in PolicyLayer and add a rule for college_value_score: 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 Livedatalink. Nothing to install.
college_value_score 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 college_value_score 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 college_value_score. 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.
college_value_score is provided by the Livedatalink MCP server (https://livedatalink.ai/mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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