ImmunoGraph MCP

normalize_scores

Read-onlyIdempotent

Transforms raw observations into comparable unit-interval values with a named versioned registry, recording the applied transformation for consensus or ranking workflows.

Instructions

Transform supplied raw observations into comparable unit-interval values using a named versioned normalization registry. Use after evidence collection and before consensus or ranking; this does not fetch predictors or improve source quality. Returns normalized observations and records the applied transformation.

Input Schema

Name	Required	Description
`runId`	Yes	Caller-chosen identifier linking this call to one research run.
`observations`	Yes	Caller-supplied evidence observations; this tool does not fetch them.
`registryVersion`	Yes	Version of the score normalization profile registry.

Output Schema

Name	Required	Description
`ok`	Yes	Whether execution completed successfully.
`data`	No	Tool-specific result fields on success.
`meta`	Yes	Run identifiers, timings, and input/output hashes.
`error`	No	Structured failure on unsuccessful execution.

Schema Changelog

Changes observed during successful MCP inspections.

Changed4 schema fields changedv0.2.1Oct 31, 2026

addedInput schema / properties / observations / description

Added value: +"Caller-supplied evidence observations; this tool does not fetch them."

addedInput schema / properties / registryVersion / description

Added value: +"Version of the score normalization profile registry."

addedInput schema / properties / runId / description

Added value: +"Caller-chosen identifier linking this call to one research run."

changedOutput schema / (root)

Previous value: -nullNew value: +{
+  "$schema": "https://json-schema.org/draft/2020-12/schema",
+  "additionalProperties": {},
+  "properties": {
+    "data": {
+      "additionalProperties": {},
+      "description": "Tool-specific result fields on success.",
+      "properties": {},
+      "type": "object"
+    },
+    "error": {
+      "additionalProperties": false,
+      "description": "Structured failure on unsuccessful execution.",
+      "properties": {
+        "category": {
+          "type": "string"
+        },
+        "code": {
+          "type": "string"
+        },
+        "details": {
+          "additionalProperties": {},
+          "properties": {},
+          "type": "object"
+        },
+        "message": {
+          "type": "string"
+        },
+        "retryable": {
+          "type": "boolean"
+        }
+      },
+      "required": [
+        "code",
+        "category",
+        "message",
+        "retryable"
+      ],
+      "type": "object"
+    },
+    "meta": {
+      "additionalProperties": {},
+      "description": "Run identifiers, timings, and input/output hashes.",
+      "properties": {
+        "completedAt": {
+          "type": "string"
+        },
+        "durationMs": {
+          "type": "number"
+        },
+        "inputHash": {
+          "type": "string"
+        },
+        "outputHash": {
+          "type": "string"
+        },
+        "requestId": {
+          "type": "string"
+        },
+        "runId": {
+          "type": "string"
+        },
+        "startedAt": {
+          "type": "string"
+        },
+        "toolName": {
+          "type": "string"
+        },
+        "toolVersion": {
+          "type": "string"
+        }
+      },
+      "required": [
+        "requestId",
+        "runId",
+        "toolName",
+        "toolVersion",
+        "startedAt",
+        "inputHash"
+      ],
+      "type": "object"
+    },
+    "ok": {
+      "description": "Whether execution completed successfully.",
+      "type": "boolean"
+    }
+  },
+  "required": [
+    "ok",
+    "meta"
+  ],
+  "type": "object"
+}

First observedv0.2.0Oct 31, 2026

TDQS

A4.4/5.0

Behavior4/5

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

Annotations already declare readOnlyHint and idempotentHint, so the safety profile is covered; the description adds that the applied transformation is recorded and that normalized observations are returned. It does not say how unknown registry versions or malformed profiles are handled, which would matter for a versioned transform.

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?

Three tight sentences: purpose first, then workflow position, then an exclusion and return note. No repetition of the schema and nothing that fails to earn its place.

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

Completeness4/5

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

With a full input schema, an output schema, and annotations in place, the description covers what an agent needs to place and call the tool. The remaining gap is guidance on which normalization profile or registry version to pick, which the schema alone does not resolve.

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 all three parameters are already documented, and the description only reinforces that observations are caller-supplied and the registry is versioned. It adds no detail on the profile kinds (IDENTITY, INVERSE_PERCENTILE, FIXED_MIN_MAX, LOGISTIC) or on choosing a registryVersion, so baseline 3 is right.

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?

Specific verb (transform) plus resource (raw observations into unit-interval values) with the mechanism named (versioned normalization registry). It is clearly distinct from the neighboring compute_consensus, rank_candidates, and predict_* tools, which the description explicitly separates itself from.

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?

States explicit workflow placement — 'use after evidence collection and before consensus or ranking' — which routes the agent relative to real siblings. It also names what the tool does not do ('does not fetch predictors or improve source quality'), heading off the most likely misuse.

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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