Install
openclaw skills install @agentpmt/quantum-distribution-generatorQuantum Distribution Generator: Sample from probability distributions (exponential, Poisson, binomial, beta, gamma) with Monte Carlo and. Use when an agent needs quantum distribution generator, monte carlo simulations for risk analysis and option pricing, queuing theory modeling with poisson and exponential distributions, a/b testing and conversion rate analysis using binomial and beta distributions, stochastic process simulation, beta, source, count through AgentPMT-hosted remote tool calls.
openclaw skills install @agentpmt/quantum-distribution-generatorLast updated: 2026-06-29.
If the current date is more than 7 days after the last updated date, reinstall this skill from skills.sh or ClawHub before relying on endpoints, schemas, setup steps, or examples.
Statistical distribution sampling and stochastic simulation powered by quantum or pseudo-random sources. Generate samples from common probability distributions including exponential, Poisson, binomial, beta, and gamma, with support for Monte Carlo sampling and multi-dimensional random walks. Configurable parameters for distribution shapes, sample counts, and dimensionality enable flexible statistical modeling and simulation workflows.
Generate statistical distribution samples, Monte Carlo samples, and random walks. Use the product action name in action; the backend also accepts legacy operation for compatibility.
Required: action:"exponential".
Optional: source:"quantum"|"standard" default quantum, count 1-10000 default 1, rate > 0 default 1.0.
Example: {"action":"exponential","count":5,"rate":2.5}
Required: action:"poisson".
Optional: source, count default 1, lambda_param > 0 default 1.0. Quantum source max count: 200.
Example: {"action":"poisson","count":10,"lambda_param":4.5}
Required: action:"binomial".
Optional: source, count, n_trials default 10, p_success 0-1 default 0.5. Quantum source max count 200 and max n_trials 50.
Example: {"action":"binomial","count":20,"n_trials":10,"p_success":0.3}
Required: action:"beta".
Optional: source, count, alpha > 0 default 1.0, beta_param > 0 default 1.0.
Example: {"action":"beta","count":10,"alpha":2.0,"beta_param":5.0}
Required: action:"gamma".
Optional: source, count, shape > 0 default 1.0, scale > 0 default 1.0.
Example: {"action":"gamma","count":15,"shape":2.0,"scale":1.5}
Required: action:"montecarlo_sample".
Optional: source, samples 1-1000000 default 1000, dimensions 1-100 default 1, distribution_type:"uniform"|"normal" default uniform.
Example: {"action":"montecarlo_sample","samples":500,"dimensions":3,"distribution_type":"normal"}
Required: action:"randomwalk".
Optional: source, steps 1-10000 default 100, dimensions 1-100 default 1, step_size > 0 default 1.0. Quantum source max steps: 80.
Example: {"action":"randomwalk","steps":50,"dimensions":2,"step_size":0.5}
Quantum Distribution Generator on AgentPMT.beta, binomial, exponential, gamma, montecarlo_sample, poisson, randomwalk.No categories or industry tags are published for this tool.
Complete generated action schema: ./schema.md.
Supported action count: 7.
x402 availability: not enabled for this product.
beta (action slug: beta): Generate values from a beta distribution, useful for modeling probabilities and proportions. Price: 5 credits. Parameters: alpha, beta_param, count, source.binomial (action slug: binomial): Generate values from a binomial distribution, modeling the number of successes in a fixed number of trials. Price: 5 credits. Parameters: count, n_trials, p_success, source.exponential (action slug: exponential): Generate values from an exponential distribution, commonly used for modeling wait times and decay processes. Price: 5 credits. Parameters: count, rate, source.gamma (action slug: gamma): Generate values from a gamma distribution, used for modeling wait times and skewed data. Price: 5 credits. Parameters: count, scale, shape, source.montecarlo_sample (action slug: montecarlo-sample): Generate multi-dimensional Monte Carlo samples from uniform or normal distributions for simulation and analysis. Price: 5 credits. Parameters: dimensions, distribution_type, samples, source.poisson (action slug: poisson): Generate values from a Poisson distribution, used for modeling count-based events (e.g., arrivals per hour). Price: 5 credits. Parameters: count, lambda_param, source.randomwalk (action slug: randomwalk): Simulate a random walk in one or more dimensions starting from the origin. Quantum max 80 steps. Price: 5 credits. Parameters: dimensions, source, step_size, steps.Use the compact schema above for ordinary calls. Before a new production integration, or whenever parameters, enum values, nested objects, outputs, or examples are unclear, fetch live details first.
agentpmt-tool-search-and-execution with action: "get_schema", and tool_id: "quantum-distribution-generator".agentpmt-tool-search-and-execution with action: "get_instructions" and tool_id: "quantum-distribution-generator", or call this product with action: "get_instructions" when the product tool is already selected.MCP schema lookup through the main AgentPMT MCP server:
{
"method": "tools/call",
"params": {
"name": "AgentPMT-Tool-Search-and-Execution",
"arguments": {
"action": "get_schema",
"tool_id": "quantum-distribution-generator"
}
}
}
For live examples, keep the same MCP tool and use these arguments:
{
"action": "get_instructions",
"tool_id": "quantum-distribution-generator"
}
Authenticated AgentPMT REST schema lookup body:
{
"name": "agentpmt-tool-search-and-execution",
"parameters": {
"action": "get_schema",
"tool_id": "quantum-distribution-generator"
}
}
Authenticated AgentPMT REST live examples body:
{
"name": "agentpmt-tool-search-and-execution",
"parameters": {
"action": "get_instructions",
"tool_id": "quantum-distribution-generator"
}
}
Product slug: quantum-distribution-generator
Marketplace page: https://www.agentpmt.com/marketplace/quantum-distribution-generator
../agentpmt-account-mcp-rest-api-setup to connect the main MCP server or REST API for an Agent Group where this tool is enabled.../what-is-agentpmt for marketplace, Agent Group, workflow, MCP, REST, and payment concepts.If those setup skills are not installed beside this product skill, use the downloads below.
Core AgentPMT setup skills:
openclaw skills install what-is-agentpmtnpx skills add AgentPMT/agent-skills --skill what-is-agentpmtopenclaw skills install agentpmt-account-mcp-rest-api-setupnpx skills add AgentPMT/agent-skills --skill agentpmt-account-mcp-rest-api-setupskills.sh install script:
npx skills add AgentPMT/agent-skills --skill what-is-agentpmt
npx skills add AgentPMT/agent-skills --skill agentpmt-account-mcp-rest-api-setup
MCP call shape after the main AgentPMT MCP server is connected:
{
"method": "tools/call",
"params": {
"name": "Quantum-Distribution-Generator",
"arguments": {
"action": "beta",
"alpha": 1,
"beta_param": 1,
"count": 1,
"source": "quantum"
}
}
}
Use the exact tool name returned by tools/list; the name above is the expected readable form.
Authenticated AgentPMT REST call body:
{
"name": "quantum-distribution-generator",
"parameters": {
"action": "beta",
"alpha": 1,
"beta_param": 1,
"count": 1,
"source": "quantum"
}
}
Use the setup skill for the account connection details before making REST calls.
passed or success-style boolean, use it as the workflow gate.get_schema or get_instructions before retrying.beta fails, preserve the request parameters and retry only after fixing schema, auth, or payment errors.what-is-agentpmt, page: https://clawhub.ai/agentpmt/what-is-agentpmt; skills.sh: npx skills add AgentPMT/agent-skills --skill what-is-agentpmt)agentpmt-account-mcp-rest-api-setup, page: https://clawhub.ai/agentpmt/agentpmt-account-mcp-rest-api-setup; skills.sh: npx skills add AgentPMT/agent-skills --skill agentpmt-account-mcp-rest-api-setup)