random_job
Generate random job title(s) using Faker.
This record as markdown: /tools/io-tinyfn-tinyfn/random-job.md
What random_job does on TinyFn
AI agents call random_job to retrieve information from TinyFn 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 |
|---|---|---|---|
count | integer | — | Number of job titles to generate |
locale | object | — | Locale (e.g., en_US, fr_FR, de_DE) |
Parameters from the server's own tool schema.
Why random_job is rated Low
This tool retrieves/generates data (random job titles) with no side effects, state changes, or external dependencies. It is purely generative and deterministic in nature, consistent with the server's advertised purpose of providing '500+ deterministic tools' for utility functions. No data is modified, deleted, executed, or committed financially.
From the tool's definition Tool description states 'Generate random job title(s) using Faker' — it generates synthetic data without modifying any persistent state or triggering external operations.
Attacks that exploit this kind of access
The rule that runs random_job safely
PolicyLayer is an MCP gateway: it sits between your AI agents and TinyFn, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For random_job, this is the rule to start with:
random_job 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 TinyFn, apply this rule, and every random_job call is checked against it from then on.
Questions about random_job
Generate random job title(s) using Faker. It is categorised as a Read tool in the TinyFn MCP Server, which means it retrieves data without modifying state.
random_job accepts 2 parameters: count, locale. The full parameter table on this page comes from the server's own tool schema.
Register the TinyFn MCP server in PolicyLayer and add a rule for random_job: 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 TinyFn. Nothing to install.
random_job 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 random_job 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 random_job. 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.
random_job is provided by the TinyFn MCP server (https://api.tinyfn.io/mcp/all/). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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