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Whatsonyourmind

oraclaw-mcp-server

by Whatsonyourmind
OverviewSchemaRelated ServersScoreDiscussions
TypeScript
Remote

score_convergence

Read-onlyIdempotent

Aggregates probability estimates from multiple independent sources into a convergence score and consensus probability, highlighting outlier sources by pairwise disagreement.

Instructions

Score how much multiple independent sources agree on a probability estimate, weighting by recency, volume, and confidence. Use to fuse signals from polling, prediction markets, model ensembles, or any source emitting a 0..1 probability. Returns an aggregate convergence score, the consensus probability, and per-pair disagreement so you can see which sources are outliers. Free tier. For comparing pre-binned distributions, prefer this over simulate_montecarlo.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
sourcesYesIndependent estimators each emitting a probability for the same event.
configNoOptional weighting overrides.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
convergenceScoreYesOverall agreement (1=consensus, 0=divergent).
consensusProbabilityNoWeighted aggregate probability.
sourcesNoNumber of sources used.
componentsNoPer-component scores feeding the aggregate.

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Changed5 schema fields changed
    • addedInput schema / properties / config
      Added value: +{
+  "description": "Optional weighting overrides.",
+  "properties": {
+    "freshnessHalfLifeMs": {
+      "minimum": 1,
+      "type": "number"
+    },
+    "outlierThreshold": {
+      "maximum": 1,
+      "minimum": 0,
+      "type": "number"
+    },
+    "scale": {
+      "type": "number"
+    },
+    "shift": {
+      "type": "number"
+    },
+    "wA": {
+      "description": "Weight on agreement component.",
+      "type": "number"
+    },
+    "wD": {
+      "description": "Weight on dispersion penalty.",
+      "type": "number"
+    },
+    "wF": {
+      "description": "Weight on freshness.",
+      "type": "number"
+    },
+    "wU": {
+      "description": "Weight on uncertainty penalty.",
+      "type": "number"
+    }
+  },
+  "type": "object"
+}
    • removedInput schema / properties / distributions
      Removed value: -{
-  "description": "[{sourceId, values: number[]}]",
-  "items": {
-    "type": "object"
-  },
-  "type": "array"
-}
    • addedInput schema / properties / sources
      Added value: +{
+  "description": "Independent estimators each emitting a probability for the same event.",
+  "items": {
+    "properties": {
+      "confidence": {
+        "description": "Optional. Source-reported certainty.",
+        "maximum": 1,
+        "minimum": 0,
+        "type": "number"
+      },
+      "id": {
+        "description": "Stable source identifier.",
+        "type": "string"
+      },
+      "lastUpdated": {
+        "description": "Optional. Unix epoch ms; older sources are downweighted.",
+        "type": "integer"
+      },
+      "name": {
+        "description": "Display label.",
+        "type": "string"
+      },
+      "probability": {
+        "description": "This source's probability estimate.",
+        "maximum": 1,
+        "minimum": 0,
+        "type": "number"
+      },
+      "volume": {
+        "description": "Optional. Sample size / liquidity behind the estimate.",
+        "minimum": 0,
+        "type": "number"
+      }
+    },
+    "required": [
+      "id",
+      "name",
+      "probability"
+    ],
+    "type": "object"
+  },
+  "minItems": 1,
+  "type": "array"
+}
    • changedInput schema / required
      Previous value: -[
-  "distributions"
-]New value: +[
+  "sources"
+]
    • changedOutput schema / (root)
      Previous value: -nullNew value: +{
+  "properties": {
+    "components": {
+      "description": "Per-component scores feeding the aggregate.",
+      "type": "object"
+    },
+    "consensusProbability": {
+      "description": "Weighted aggregate probability.",
+      "maximum": 1,
+      "minimum": 0,
+      "type": "number"
+    },
+    "convergenceScore": {
+      "description": "Overall agreement (1=consensus, 0=divergent).",
+      "maximum": 1,
+      "minimum": 0,
+      "type": "number"
+    },
+    "sources": {
+      "description": "Number of sources used.",
+      "type": "integer"
+    }
+  },
+  "required": [
+    "convergenceScore"
+  ],
+  "type": "object"
+}
  2. First observedv1.0.1

TDQS

A4.7/5.0
Behavior5/5

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

The description adds behavioral context beyond annotations: it discloses the output ('returns an aggregate convergence score, the consensus probability, and per-pair disagreement'), mentions 'free tier', and implies reading behavior consistent with annotation readOnlyHint=true. No contradictions.

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 concise (two sentences plus a brief note), front-loaded with the core purpose and usage, and every sentence adds value without redundancy.

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

Completeness5/5

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

Given the tool's complexity (nested objects, many optional fields, output schema present), the description is complete: it explains purpose, usage, output, and alternative. With an output schema, return values need not be described in detail.

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

Parameters3/5

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

Schema description coverage is 100%, so the baseline is 3. The description does not add new parameter-level details beyond what the schema already provides, but it also does not need to since the schema is comprehensive.

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 the tool's action ('score how much multiple independent sources agree'), identifies the resource ('probability estimate'), and distinguishes it from siblings by mentioning 'for comparing pre-binned distributions, prefer this over simulate_montecarlo'.

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

Usage Guidelines5/5

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

The description explicitly recommends use cases ('fuse signals from polling, prediction markets, model ensembles, or any source emitting a 0..1 probability') and provides an alternative ('for comparing pre-binned distributions, prefer this over simulate_montecarlo'), giving clear when-to-use and when-not-to-use guidance.

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

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