Server definition
- Hash
- sha256:72e246086fc9907fd3e69234add1bd71c3ef2265cb9e8fa083097419cdf2f21b
- What it is
- What a remote MCP server returned when asked what it offers: 11 tools
The blob, as servednamed by its sha256
{
"instructions": "ReliaStats is a free MCP server from ChiAha for reliability statistics theory + interpretation. Eleven tools across three families. Theory (4, doc-backed): explain_reliability_basics, explain_distributions_for_reliability, explain_advanced_reliability_patterns, explain_pi_vs_ci_for_validation. Pure-math interpretive (5, stateless deterministic): interpret_weibull_shape, weibull_summary, compute_availability, system_reliability, recommend_distribution. Cross-MCP bridge (2, soft-reference catalog only): list_paired_models, describe_bottling_line — these route LLM clients between ReliaStats and ReliaSim sandboxes around the bottling-line paired model. The MCP layer does NOT fit distributions or validate datasets; the ReliaStats Designer at https://reliasim.com/reliastats/designer is the compute surface. ANTI-FABRICATION (IMPORTANT FOR ASSISTANT BEHAVIOR): every numeric result is closed-form reliability math (deterministic); every text result is a quoted section from ChiAha-authored docs. Quote returned content VERBATIM in your reply; do not paraphrase reliability theory or recompute closed-form values from training-data recall. For custom modeling beyond what these tools expose, contact ChiAha.",
"tools": [
{
"description": "Given MTBF and MTTR (same time unit), return steady-state availability A = MTBF / (MTBF + MTTR). One-line closed-form, but worth a dedicated tool so LLMs don't fumble the identity (the most common mistake is conflating MTBF with MTTF and silently inflating availability by the MTTR). Use whenever a user supplies an MTBF/MTTR pair and asks for availability. ANTI-FABRICATION: exact closed-form. Quote verbatim.",
"inputSchema": {
"properties": {
"mtbf": {
"default": 1000,
"description": "Mean Time Between Failures (repairable system). Same time unit as MTTR.",
"minimum": 0,
"type": "number"
},
"mttr": {
"default": 10,
"description": "Mean Time To Repair. Same time unit as MTBF.",
"minimum": 0,
"type": "number"
}
},
"required": [
"mtbf",
"mttr"
],
"type": "object"
},
"name": "compute_availability",
"outputSchema": null
},
{
"description": "Return the full worked-example doc for the bottling-line paired model — topology (5 machines: Filler/Capper/Labeler/Case Packer/Palletizer, 100 bottles/min, Weibull(30,1) TTF + Weibull(5,1) downtime at the Constraint-Level rollup), the two tracks (CT rollup vs LEDS-Level drill-down to 36 named failure modes), the 4 build sequences (BS1 → BS4), the file-shape mapping between ReliaSim outputs and ReliaStats modes, and a worked cross-MCP tool chain. Optional 'section' parameter narrows to one H2 section. ANTI-FABRICATION: content is sourced from docs/paired-model-bottling-line.md; every claim references the .aidos files or ChapterRegistry.fs in reliasim-site.",
"inputSchema": {
"properties": {
"section": {
"default": "",
"description": "Optional H2 section name from docs/paired-model-bottling-line.md to narrow the response. Examples: 'Topology — the line itself', 'The two tracks — Constraint-Level vs LEDS-Level', 'The four build sequences (BS1 → BS4)', 'File-shape mapping — which ReliaStats mode consumes what', 'The cross-MCP workflow — worked example'. Omit to return the full doc.",
"type": "string"
}
},
"required": [],
"type": "object"
},
"name": "describe_bottling_line",
"outputSchema": null
},
{
"description": "Return a textbook-tier explainer of advanced reliability patterns: censored data (right/left/interval — the rule not the exception), Maximum Likelihood Estimation, Goodness-of-Fit tests (Anderson-Darling favored over KS for tail-sensitive reliability work), the Confidence-Interval vs Prediction-Interval distinction that backs the Interrupt Validation scatter, accelerated life testing (Arrhenius / inverse power law / Coffin-Manson), and Bayesian reliability. No inputs. ANTI-FABRICATION: text is sourced from docs/reliability-theory.md.",
"inputSchema": {
"properties": {},
"required": [],
"type": "object"
},
"name": "explain_advanced_reliability_patterns",
"outputSchema": null
},
{
"description": "Return a textbook-tier distribution zoology for reliability work: why Weibull is the default, the shape-parameter β table mapping β-ranges to physical failure modes (β<1 infant mortality, β=1 random, β>1 wearout), when to reach for Exponential / Lognormal / Normal / Gamma, and practitioner heuristics for picking a distribution. No inputs. Use when a user asks 'which distribution should I fit' / 'what does Weibull β mean' / 'when to use Lognormal'. ANTI-FABRICATION: text is sourced from docs/reliability-theory.md. The β-as-failure-mode interpretation is ChiAha's practitioner framing — quote verbatim; do not paraphrase.",
"inputSchema": {
"properties": {},
"required": [],
"type": "object"
},
"name": "explain_distributions_for_reliability",
"outputSchema": null
},
{
"description": "Return the specific explainer for the ReliaStats Interrupt Validation scatter chart's red y=x / blue 95% Prediction Interval / teal 99% Confidence Interval reference lines. Use when a user asks 'what do the bands mean' / 'why is my point outside the blue line' / 'how do I read the validation scatter'. The bands are FIXED plotting conventions — they are NOT recomputed from the loaded data; this is anti-fab by design. Text sourced from docs/reliability-theory.md (the 'Confidence intervals vs prediction intervals' sub-section of Advanced Reliability Patterns).",
"inputSchema": {
"properties": {},
"required": [],
"type": "object"
},
"name": "explain_pi_vs_ci_for_validation",
"outputSchema": null
},
{
"description": "Return a textbook-tier explainer of reliability fundamentals: the four reliability functions R(t)/F(t)/f(t)/h(t), MTBF vs MTTF vs MTTR, the availability identity A = MTBF/(MTBF+MTTR), the bathtub curve, and series/parallel system reliability. No inputs. Use when a user asks 'what is reliability theory' / 'explain MTBF' / 'how does availability work' / 'what's a hazard rate'. ANTI-FABRICATION: text is sourced from docs/reliability-theory.md (the canonical ChiAha reliability primer). Quote sections verbatim; do not paraphrase reliability theory from training-data recall.",
"inputSchema": {
"properties": {},
"required": [],
"type": "object"
},
"name": "explain_reliability_basics",
"outputSchema": null
},
{
"description": "Given a Weibull shape parameter β (and optionally the characteristic-life parameter η), return a plain-language interpretation: which bathtub-curve regime β implies (infant mortality / random / wearout), what action that suggests (process-of-care / steady-state monitoring / maintenance scheduling), and — if η provided — closed-form MTTF and B-life numbers from the Weibull formulas. Pure-math + lookup, no engine call, fully deterministic. Use when a user reports a fitted β and wants to know what to DO with it. ANTI-FABRICATION: MTTF and B-life are exact closed-form values from the two-parameter Weibull (η · Γ(1+1/β) and η · (-ln(1-p))^(1/β)). Quote them verbatim.",
"inputSchema": {
"properties": {
"beta": {
"default": 2,
"description": "Weibull shape parameter β (dimensionless). Typical reliability range 0.3 – 8.0.",
"maximum": 20,
"minimum": 0.01,
"type": "number"
},
"eta": {
"default": 1000,
"description": "Optional Weibull characteristic-life parameter η, in the same time units you care about (e.g. hours). When provided, the response includes MTTF + B-life numbers.",
"minimum": 0,
"type": "number"
}
},
"required": [
"beta"
],
"type": "object"
},
"name": "interpret_weibull_shape",
"outputSchema": null
},
{
"description": "Return the catalog of paired models — concrete real-world systems that live in two ChiAha sandboxes simultaneously, one for dynamics (DES via ReliaSim) and one for statistics (distribution fitting + validation via ReliaStats). Today: a single paired model — the bottling line. Returns canonical model IDs + cross-MCP routing metadata (which ReliaSim chapter, which ReliaSim MCP tools, which ReliaStats mode consumes which file shape). Use when a user asks about cross-MCP workflows, paired sandboxes, or the bottling-line example. ANTI-FABRICATION: this is a soft-reference catalog — to actually run a simulation, the LLM client calls ReliaSim's MCP tools directly.",
"inputSchema": {
"properties": {},
"required": [],
"type": "object"
},
"name": "list_paired_models",
"outputSchema": null
},
{
"description": "Given a free-text symptom description (e.g. 'manufacturing burn-in', 'bearing wearout under variable load', 'cosmic-ray bit flips'), return an ordered shortlist of distribution candidates with a one-line rationale per recommendation. Keyword-matched against a curated dictionary; ALWAYS treat output as a starting point for fitting work, not a fit. The actual fitting happens in the ReliaStats sandbox (protected/app.html). ANTI-FABRICATION: rationales are written ChiAha content; the algorithm is a deterministic substring match. Quote verbatim.",
"inputSchema": {
"properties": {
"symptoms": {
"default": "bearing wearout",
"description": "Free-text description of the failure data or context — e.g. 'manufacturing burn-in', 'bearing wearout', 'cosmic-ray bit flips', 'multi-stage degradation'. Substring-matched against a keyword dictionary; returns an ordered shortlist with rationale.",
"type": "string"
}
},
"required": [
"symptoms"
],
"type": "object"
},
"name": "recommend_distribution",
"outputSchema": null
},
{
"description": "Given per-component reliabilities and a structure ('series' or 'parallel'), return the system reliability. Series = product (all must work). Parallel = 1 − product(1−Rᵢ) (at least one works). Useful for back-of-envelope RBD calcs before reaching for full RBD tooling. For mixed-structure systems (series with parallel sub-blocks), call this tool repeatedly on the sub-blocks. ANTI-FABRICATION: exact closed-form. Quote verbatim.",
"inputSchema": {
"properties": {
"components": {
"default": [
0.95,
0.95,
0.95
],
"description": "Per-component reliabilities in [0, 1]. Order doesn't matter.",
"items": {
"maximum": 1,
"minimum": 0,
"type": "number"
},
"type": "array"
},
"structure": {
"default": "series",
"description": "RBD structure: 'series' (all must work) or 'parallel' (at least one works).",
"enum": [
"series",
"parallel"
],
"type": "string"
}
},
"required": [
"components",
"structure"
],
"type": "object"
},
"name": "system_reliability",
"outputSchema": null
},
{
"description": "Given Weibull two-parameter (β, η), return all the closed-form summary statistics: MTTF (η·Γ(1+1/β)), B10 / B50 / B90 life, characteristic life (just η, surfaced explicitly), and — if evaluateAtT supplied — R(t), F(t), and hazard h(t) at that time. Pure-math, fully deterministic. Use when the user has a fit and wants the numbers downstream tools normally compute (don't recompute these from training-data recall — call this tool). ANTI-FABRICATION: every number is an exact closed-form value. Quote verbatim.",
"inputSchema": {
"properties": {
"beta": {
"default": 2,
"description": "Weibull shape parameter β (dimensionless).",
"maximum": 20,
"minimum": 0.01,
"type": "number"
},
"eta": {
"default": 1000,
"description": "Weibull characteristic life η, in your chosen time unit.",
"minimum": 0,
"type": "number"
},
"evaluateAtT": {
"default": 500,
"description": "Optional time t (same unit as η) at which to also return reliability R(t), failure F(t), and hazard h(t).",
"minimum": 0,
"type": "number"
}
},
"required": [
"beta",
"eta"
],
"type": "object"
},
"name": "weibull_summary",
"outputSchema": null
}
]
}Verify it yourself
curl -s https://api.teppi.xyz/v1/evidence/sha256:72e246086fc9907fd3e69234add1bd71c3ef2265cb9e8fa083097419cdf2f21b | sha256sum