ReliaSim

Reliability and bottleneck simulation for manufacturing lines; run experiments, sweep buffers.

我该使用它吗

质量与安全性

A
描述质量
100%
模式完整度
93%
命名质量
94%
投毒风险
100%
权限匹配度
100%
协议合规性
100%

基于对工具定义和协议合规性的自动分析。

上下文开销

~2,133token 数(工具定义)
~1.8 KB典型响应大小
对注意力有中等影响(占 128k 上下文窗口的 1.67%)

这是每次将服务器的工具加载到模型上下文窗口时所消耗的大致 token 数。数值越高,可用于其他任务的注意力就越少。

安装

一键安装

将以下内容添加到你的 `claude_desktop_config.json` 文件中:

{
  "mcpServers": {
    "public": {
      "url": "https://reliasim.com/mcp"
    }
  }
}

远程端点

https://reliasim.com/mcpstreamable-http

它能做什么

工具清单

工具(7)

🟢 只读🟡 写入🔴 删除⚪ 未知
🟢find_bottleneck(chapter)

Single Run bottleneck analysis for the selected chapter — which node has the worst availability, per-interrupt downtime split, throughput, OEE. All eight chapters return verified dys-cli sales-prototype numbers. ANTI-FABRICATION: numbers in the response are canonical reference values from real dys-cli engine runs. Quote them VERBATIM. Do not round, estimate, or recall from training data. For follow-ups about the same chapter, re-call this tool.

输入模式

{
  "type": "object",
  "properties": {
    "chapter": {
      "type": "string",
      "enum": [
        "bs1-ct",
        "bs2-ct",
        "bs3-ct",
        "bs4-ct",
        "bs1-leds",
        "bs2-leds",
        "bs3-leds",
        "bs4-leds",
        "cmp-buffer-reliability",
        "cmp-shared-palletizer"
      ],
      "default": "bs1-ct",
      "description": "Which curriculum chapter the tool should answer about. Format: `bs<1-5>-<ct|leds>`. Both tracks run on the same real plant data — `ct` = Constraint-Level (interrupts rolled up to one Weibull per machine, 5 total) and `leds` = LEDS-Level (interrupts drilled down to named failure modes, 36 total). Defaults to bs1-ct when omitted."
    }
  }
}
🟢get_chapter_facts(chapter)

Structural facts of the selected chapter — topology, rate limits, interrupt distributions, expected efficiency. Use when the user asks about the line's configuration. ANTI-FABRICATION: rates and distributions are verified .aidos-file values. Quote VERBATIM; do not estimate or substitute training-data recall.

输入模式

{
  "type": "object",
  "properties": {
    "chapter": {
      "type": "string",
      "enum": [
        "bs1-ct",
        "bs2-ct",
        "bs3-ct",
        "bs4-ct",
        "bs1-leds",
        "bs2-leds",
        "bs3-leds",
        "bs4-leds",
        "cmp-buffer-reliability",
        "cmp-shared-palletizer"
      ],
      "default": "bs1-ct",
      "description": "Which curriculum chapter the tool should answer about. Format: `bs<1-5>-<ct|leds>`. Both tracks run on the same real plant data — `ct` = Constraint-Level (interrupts rolled up to one Weibull per machine, 5 total) and `leds` = LEDS-Level (interrupts drilled down to named failure modes, 36 total). Defaults to bs1-ct when omitted."
    }
  }
}
🟢get_chapter_narrative(chapter)

Long-form narrative for the selected chapter — what the chapter adds to the complexity ladder and the key teaching point. Use when the user asks 'walk me through this' or wants the conceptual primer. Pure prose, no numerical claims; safe to summarize.

输入模式

{
  "type": "object",
  "properties": {
    "chapter": {
      "type": "string",
      "enum": [
        "bs1-ct",
        "bs2-ct",
        "bs3-ct",
        "bs4-ct",
        "bs1-leds",
        "bs2-leds",
        "bs3-leds",
        "bs4-leds",
        "cmp-buffer-reliability",
        "cmp-shared-palletizer"
      ],
      "default": "bs1-ct",
      "description": "Which curriculum chapter the tool should answer about. Format: `bs<1-5>-<ct|leds>`. Both tracks run on the same real plant data — `ct` = Constraint-Level (interrupts rolled up to one Weibull per machine, 5 total) and `leds` = LEDS-Level (interrupts drilled down to named failure modes, 36 total). Defaults to bs1-ct when omitted."
    }
  }
}
🟢run_gain_loss(chapter)

Gain/Loss experiment — disable each interrupt one at a time, measure production recovered. Reveals the ACTUAL impact of each failure mode (Gain ≠ Loss: removing one lets others fire more often). Available on `bs1-leds`, `bs3-leds`, `bs4-ct`, `bs4-leds`. Use when the user asks 'what if we fixed X?' / 'which interrupt matters most if we actually fixed it?' / 'show me the Pareto'. ANTI-FABRICATION: per-interrupt recovered-production numbers come from real dys-cli runs. Quote VERBATIM; the Gain ≠ Loss interaction is exactly the kind of figure LLMs are prone to fabricate — don't.

输入模式

{
  "type": "object",
  "properties": {
    "chapter": {
      "type": "string",
      "enum": [
        "bs1-ct",
        "bs2-ct",
        "bs3-ct",
        "bs4-ct",
        "bs1-leds",
        "bs2-leds",
        "bs3-leds",
        "bs4-leds",
        "cmp-buffer-reliability",
        "cmp-shared-palletizer"
      ],
      "default": "bs1-ct",
      "description": "Which curriculum chapter the tool should answer about. Format: `bs<1-5>-<ct|leds>`. Both tracks run on the same real plant data — `ct` = Constraint-Level (interrupts rolled up to one Weibull per machine, 5 total) and `leds` = LEDS-Level (interrupts drilled down to named failure modes, 36 total). Defaults to bs1-ct when omitted."
    }
  }
}
🟢run_buffer_tradeoff(chapter, buffer)

Buffer Tradeoff experiment — sweep a buffer's capacity from 50 → 10,000 units, measure throughput gain. Shows the diminishing-returns elbow for buffer sizing. Only defined on `bs4-ct` and `bs4-leds`; each chapter has THREE inline buffers with different placements (pass `buffer` id to pick one). Compare CT vs LEDS on the same slot to see why interrupt-detail level changes buffer ROI math (e.g. b3: CT +23.7% vs LEDS +64.2%). Use when the user asks 'how big should the buffer be?' / 'do buffers help on this line?' / 'which buffer position gives the most gain?' / 'what's the diminishing-returns point?'. ANTI-FABRICATION (CRITICAL): the specific tradeoff numbers (e.g. CT +23.7% vs LEDS +64.2%) are sweep-derived reference values. Quote VERBATIM in your reply; do NOT recall similar percentages from training data — every buffer position has different math.

输入模式

{
  "type": "object",
  "properties": {
    "chapter": {
      "type": "string",
      "enum": [
        "bs1-ct",
        "bs2-ct",
        "bs3-ct",
        "bs4-ct",
        "bs1-leds",
        "bs2-leds",
        "bs3-leds",
        "bs4-leds",
        "cmp-buffer-reliability",
        "cmp-shared-palletizer"
      ],
      "default": "bs4-ct",
      "description": "Chapter id. Only `bs4-ct` and `bs4-leds` have buffer tradeoffs defined."
    },
    "buffer": {
      "type": "string",
      "default": "b3",
      "description": "Buffer id to sweep. The Buffer-Options Constraint-Level model has `b3` (Buffer 1, between Capper↔Labeler), `b4` (Buffer 2, between Labeler↔Case Packer), `b5` (Buffer 3, between Case Packer↔Palletizer). The Buffer-Options LEDS model has `b2` (Buffer Option 1, earliest), `b3` (Buffer Option 2, middle), `b4` (Buffer Option 3, last). Defaults to b3 if omitted — but pick the buffer that matches the question (e.g. 'the first inline buffer' = b3 on CT, b2 on LEDS)."
    }
  }
}
🟢explain_concept(concept)

Definitional primer for ReliaSim's framework concepts — Constraint, Buffer, Interrupt, Converter, cascading losses, OEE, Gain/Loss methodology, Buffer Tradeoff. Returns bundled theory content, NOT interpretation of any specific simulation run. Use for 'what is X?' / 'how does X work?' / 'explain the framework' questions. For line-specific claims (throughput, availability, what-if), call the sim tools instead.

输入模式

{
  "type": "object",
  "properties": {
    "concept": {
      "type": "string",
      "enum": [
        "constraint",
        "buffer",
        "interrupt",
        "converter",
        "cascading_losses",
        "oee",
        "gain_loss",
        "buffer_tradeoff"
      ],
      "default": "constraint",
      "description": "Which concept to explain. Returns a definitional primer — theory, not interpretation of a specific simulation run. Use for 'what is a Constraint?' / 'what are cascading losses?' / 'explain Gain-Loss'."
    }
  },
  "required": [
    "concept"
  ]
}
🟡compare_chapters(chapter_a, chapter_b)

Side-by-side comparison of two chapters — tracks, topology, OEE, throughput, headline bottleneck. Output is sim-derived (no interpretation drift). Use for 'how does X compare to Y?' / 'what's the difference between Constraint-Level and LEDS-Level on the same model?' / 'what changes when we add buffers?' questions. ANTI-FABRICATION: per-chapter OEE/throughput numbers are real reference values; the side-by-side delta is computed from them, not estimated. Quote VERBATIM.

输入模式

{
  "type": "object",
  "properties": {
    "chapter_a": {
      "type": "string",
      "enum": [
        "bs1-ct",
        "bs2-ct",
        "bs3-ct",
        "bs4-ct",
        "bs1-leds",
        "bs2-leds",
        "bs3-leds",
        "bs4-leds",
        "cmp-buffer-reliability",
        "cmp-shared-palletizer"
      ],
      "default": "bs1-ct",
      "description": "First chapter id (left column of the comparison). Defaults to bs1-ct."
    },
    "chapter_b": {
      "type": "string",
      "enum": [
        "bs1-ct",
        "bs2-ct",
        "bs3-ct",
        "bs4-ct",
        "bs1-leds",
        "bs2-leds",
        "bs3-leds",
        "bs4-leds",
        "cmp-buffer-reliability",
        "cmp-shared-palletizer"
      ],
      "default": "bs1-leds",
      "description": "Second chapter id (right column of the comparison). Defaults to bs1-leds — same plant data as bs1-ct, but with interrupts drilled down to named failure modes; the canonical first-look comparison."
    }
  },
  "required": [
    "chapter_a",
    "chapter_b"
  ]
}

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