college_outcomes_by_program
Program-level outcomes (4-digit CIP code) for one school: median earnings one year after completion, median debt at completion, and award counts.
This record as markdown: /tools/io-github-blackboxfoundry-livedatalink/college-outcomes-by-program.md
What college_outcomes_by_program does on Livedatalink
AI agents call college_outcomes_by_program 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 |
|---|---|---|---|
unit_id | string | Yes | IPEDS UNITID. |
Parameters from the server's own tool schema.
Why college_outcomes_by_program is rated Low
This tool performs a straightforward data query operation with no side effects. It fetches pre-computed educational outcome statistics from a database and returns them to the caller. There is no capability to modify data, execute code, delete records, or conduct financial transactions.
From the tool's definition Tool retrieves program-level outcomes data (median earnings, median debt, award counts) for a specified school using a 4-digit CIP code. The description uses retrieval language: 'Program-level outcomes...for one school' with specific data points returned.
Attacks that exploit this kind of access
The rule that runs college_outcomes_by_program 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_outcomes_by_program, this is the rule to start with:
college_outcomes_by_program 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_outcomes_by_program call is checked against it from then on.
Questions about college_outcomes_by_program
Program-level outcomes (4-digit CIP code) for one school: median earnings one year after completion, median debt at completion, and award counts. It is categorised as a Read tool in the Livedatalink MCP Server, which means it retrieves data without modifying state.
college_outcomes_by_program accepts 1 parameter: unit_id. Required: unit_id. 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_outcomes_by_program: 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_outcomes_by_program 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_outcomes_by_program 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_outcomes_by_program. 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_outcomes_by_program 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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