이 MCP로 할 수 있는 일
Runs manufacturing-line reliability and bottleneck simulations, including buffer-sizing and gain/loss experiments.
기능
도구
7
도구
compare_chapters
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.
입력 스키마
{'type': 'object', 'required': ['chapter_a', 'chapter_b'], 'properties': {'chapter_a': {'enum': ['bs1-ct', 'bs2-ct', 'bs3-ct', 'bs4-ct', 'bs1-leds', 'bs2-leds', 'bs3-leds', 'bs4-leds', 'cmp-buffer-reliability', 'cmp-shared-palletizer'], 'type': 'string', 'default': 'bs1-ct', 'description': 'First chapter id (left column of the comparison). Defaults to bs1-ct.'}, 'chapter_b': {'enum': ['bs1-ct', 'bs2-ct', 'bs3-ct', 'bs4-ct', 'bs1-leds', 'bs2-leds', 'bs3-leds', 'bs4-leds', 'cmp-buffer-reliability', 'cmp-shared-palletizer'], 'type': 'string', '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.'}}}
explain_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.
입력 스키마
{'type': 'object', 'required': ['concept'], 'properties': {'concept': {'enum': ['constraint', 'buffer', 'interrupt', 'converter', 'cascading_losses', 'oee', 'gain_loss', 'buffer_tradeoff'], 'type': 'string', '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'."}}}
find_bottleneck
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.
입력 스키마
{'type': 'object', 'properties': {'chapter': {'enum': ['bs1-ct', 'bs2-ct', 'bs3-ct', 'bs4-ct', 'bs1-leds', 'bs2-leds', 'bs3-leds', 'bs4-leds', 'cmp-buffer-reliability', 'cmp-shared-palletizer'], 'type': 'string', '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
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.
입력 스키마
{'type': 'object', 'properties': {'chapter': {'enum': ['bs1-ct', 'bs2-ct', 'bs3-ct', 'bs4-ct', 'bs1-leds', 'bs2-leds', 'bs3-leds', 'bs4-leds', 'cmp-buffer-reliability', 'cmp-shared-palletizer'], 'type': 'string', '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
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.
입력 스키마
{'type': 'object', 'properties': {'chapter': {'enum': ['bs1-ct', 'bs2-ct', 'bs3-ct', 'bs4-ct', 'bs1-leds', 'bs2-leds', 'bs3-leds', 'bs4-leds', 'cmp-buffer-reliability', 'cmp-shared-palletizer'], 'type': 'string', '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
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.
입력 스키마
{'type': 'object', 'properties': {'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)."}, 'chapter': {'enum': ['bs1-ct', 'bs2-ct', 'bs3-ct', 'bs4-ct', 'bs1-leds', 'bs2-leds', 'bs3-leds', 'bs4-leds', 'cmp-buffer-reliability', 'cmp-shared-palletizer'], 'type': 'string', 'default': 'bs4-ct', 'description': 'Chapter id. Only `bs4-ct` and `bs4-leds` have buffer tradeoffs defined.'}}}
run_gain_loss
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.
입력 스키마
{'type': 'object', 'properties': {'chapter': {'enum': ['bs1-ct', 'bs2-ct', 'bs3-ct', 'bs4-ct', 'bs1-leds', 'bs2-leds', 'bs3-leds', 'bs4-leds', 'cmp-buffer-reliability', 'cmp-shared-palletizer'], 'type': 'string', '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.'}}}
기록
최근 도구 변경
삭제됨
run_showcase
2026년 9월 23일 2:54 AM
변경됨
run_showcase
2026년 9월 21일 3:00 AM
변경됨
compare_chapters
2026년 9월 21일 3:00 AM
변경됨
run_buffer_tradeoff
2026년 9월 21일 3:00 AM
변경됨
run_gain_loss
2026년 9월 21일 3:00 AM
변경됨
get_chapter_narrative
2026년 9월 21일 3:00 AM
변경됨
get_chapter_facts
2026년 9월 21일 3:00 AM
변경됨
find_bottleneck
2026년 9월 21일 3:00 AM
추가됨
run_showcase
2026년 9월 17일 12:37 PM
추가됨
compare_chapters
2026년 9월 17일 12:37 PM
추가됨
explain_concept
2026년 9월 17일 12:37 PM
추가됨
run_buffer_tradeoff
2026년 9월 17일 12:37 PM
추가됨
run_gain_loss
2026년 9월 17일 12:37 PM
추가됨
get_chapter_narrative
2026년 9월 17일 12:37 PM
추가됨
get_chapter_facts
2026년 9월 17일 12:37 PM
추가됨
find_bottleneck
2026년 9월 17일 12:37 PM
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