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simulate_gacha

Read-only

Simulate gacha draws to analyze probability distributions and expected pulls. Supports tiered pools without pity and gacha with soft/hard pity systems.

Instructions

概率模拟(确定性引擎):mode=tiers 模拟无保底分层概率池(rogue 技能三选一、宝箱品质掉落)N 次抽取的各层次数分布与分位;mode=pity 模拟带保底的抽卡(基础概率+软/硬保底)抽数分布与期望。

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
modeYestiers=分层池抽取;pity=保底抽卡
drawsNomode=tiers:单轮抽取次数(如一局 15 次三选一 = 15 抽)
tiersNomode=tiers 必填:各层名称与单次命中率(概率和须为 1)
baseRateNomode=pity:基础概率(如 0.006)
hardPityNomode=pity:硬保底抽数
iterationsNo模拟轮数(默认 1000)
softPityStartNomode=pity:软保底起始抽数
softPityIncrementNomode=pity:软保底每抽概率增量

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.1/5.0
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations declare readOnlyHint=true, so the description is not burdened with stating read-only behavior. The description adds the 'deterministic engine' trait, but does not elaborate on output format, performance, or error handling. Given the annotation coverage, a 3 is appropriate – the description adds some context but misses richer behavioral details.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is two sentences, dense with information, and front-loads the mode concept before detailing each variant. No wasted words; every clause adds meaning. Structure is exemplary for a multi-mode tool.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Without an output schema, the description must explain return values. It mentions 'distribution and quantiles' and 'distribution and expectation' but does not specify the exact structure (e.g., array of counts, percentiles). For a tool with 8 parameters and two complex modes, this is a noticeable gap, though the description covers the essential functional scope.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so baseline is 3. The description adds value by explaining mode-dependent parameter requirements (mode=tiers needs tiers; mode=pity needs baseRate, hardPity, etc.), clarifying conditional semantics not obvious from the schema alone. This elevates it to 4.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states a specific verb (simulate) and resource (gacha/probability draws), and explicitly distinguishes two modes (tiers for layered pools without pity, pity for gacha with guarantee). Concrete examples (rogue skill three-choice, chest quality drops) anchor its purpose and differentiate it from sibling tools like battle_simulate.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explicitly specifies when to use each mode (mode=tiers for layered pools, mode=pity for guaranteed draws), which effectively routes the agent to the correct parameter set. However, it does not mention when not to use this tool or alternative tools for similar probabilistic tasks, so it falls short of explicit exclusion guidance.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.