hypothesis_test
Perform statistical hypothesis tests: z-test, t-test, or chi-squared test. Returns test statistic, p-value, and rejection decision.
This record as markdown: /tools/io-github-malamutemayhem-unclick-mcp-server/hypothesis-test.md
What hypothesis_test does on UnClick
AI agents invoke hypothesis_test to trigger actions in UnClick. What it does depends on the arguments the agent supplies, and its effects often reach beyond the immediate call: builds kicked off, notifications sent, workflows started.
| Parameter | Type | Required | Description |
|---|---|---|---|
tail | string | — | Tail type (default two) |
test | string | Yes | Type of test |
alpha | number | — | Significance level (default 0.05) |
expected | array | — | Expected frequencies (for chi2) |
observed | array | — | Observed frequencies (for chi2) |
sample_std | number | — | Sample standard deviation (for t-test) |
sample_mean | number | — | Sample mean (for z/t tests) |
sample_size | integer | — | Sample size (for z/t tests) |
population_std | number | — | Population standard deviation (for z-test) |
population_mean | number | — | Population mean / null hypothesis value |
Parameters from the server's own tool schema.
Why hypothesis_test is rated High
This tool executes statistical computations on provided data. It does not read from external sources, write data, delete anything, or involve finances — it runs a calculation/algorithm and returns results. Execute is the most appropriate category as it performs an operation (running a statistical test) whose output depends on the arguments supplied.
From the tool's definition 'Perform statistical hypothesis tests: z-test, t-test, or chi-squared test. Returns test statistic, p-value, and rejection decision.'
Risk signalsHigh parameter count (10 properties)
Attacks that exploit this kind of access
The rule that runs hypothesis_test safely
PolicyLayer is an MCP gateway: it sits between your AI agents and UnClick, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For hypothesis_test, this is the rule to start with:
hypothesis_test stays usable, but rate-capped: a runaway agent can't fire it dozens of times a minute. Everything else on the server is denied unless you say otherwise.
The button opens the PolicyLayer dashboard: create your workspace, connect UnClick, apply this rule, and every hypothesis_test call is checked against it from then on.
Questions about hypothesis_test
Perform statistical hypothesis tests: z-test, t-test, or chi-squared test. Returns test statistic, p-value, and rejection decision. It is categorised as a Execute tool in the UnClick MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
hypothesis_test accepts 10 parameters: tail, test, alpha, expected, observed, sample_std, sample_mean, sample_size, population_std, population_mean. Required: test. The full parameter table on this page comes from the server's own tool schema.
Register the UnClick MCP server in PolicyLayer and add a rule for hypothesis_test: 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 UnClick. Nothing to install.
hypothesis_test is a Execute tool with high risk. Execute tools should be rate-limited and have argument validation enabled.
Yes. Add a rate_limit block to the hypothesis_test 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 hypothesis_test. 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.
hypothesis_test is provided by the UnClick MCP server (@unclick/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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