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ATTRACTOR Verification & State

by io.github.NovanBaillif
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map_fields

Read-onlyIdempotent

Use this tool when your workflow needs map json fields api. Input: value, mapping, omit_missing. Returns a structured deterministic result with explicit errors, avoiding another model parsing/normalization retry. Project explicitly mapped dotted source paths to dotted object target paths. Unmapped fields are omitted by design. Reject target overlaps and reserved path segments. Missing sources error unless omit_missing=true; omissions are reported. Output arrays are not constructed. Limits: request 24 KB, JSON depth 24, 4,000 nodes. Reserved prototype keys and unsafe integers rejected. Inputs processed transiently; private HMAC trace metadata retained.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
valueYes
mappingYes
omit_missingNo
attractor_trace_idNoOptional public correlation handle from a prior result; not authentication or proof of identity.
attractor_knowledge_idNoOptional prior result handle. Reuse is counted only when the supplied value matches that result fingerprint.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed3 schema fields changed
    • addedInput schema / properties / attractor_knowledge_id
      Added value: +{
+  "description": "Optional prior result handle. Reuse is counted only when the supplied value matches that result fingerprint.",
+  "pattern": "^ATR-K-[a-f0-9]{64}$",
+  "type": "string"
+}
    • addedInput schema / properties / attractor_trace_id
      Added value: +{
+  "description": "Optional public correlation handle from a prior result; not authentication or proof of identity.",
+  "pattern": "^ATR-T-[a-f0-9]{32}$",
+  "type": "string"
+}
    • changedOutput schema / (root)
      Previous value: -nullNew value: +{
+  "anyOf": [
+    {
+      "properties": {
+        "attractor_trace_id": {
+          "type": "string"
+        },
+        "commons": {
+          "type": "object"
+        },
+        "knowledge_id": {
+          "type": "string"
+        },
+        "ok": {
+          "const": true
+        },
+        "request_id": {
+          "type": "string"
+        },
+        "result": {
+          "properties": {
+            "omitted": {
+              "type": "array"
+            },
+            "projection": {
+              "type": "boolean"
+            },
+            "value": {
+              "type": "object"
+            }
+          },
+          "required": [
+            "value",
+            "omitted",
+            "projection"
+          ],
+          "type": "object"
+        },
+        "tool": {
+          "type": "string"
+        }
+      },
+      "required": [
+        "ok",
+        "tool",
+        "result",
+        "knowledge_id",
+        "attractor_trace_id",
+        "request_id",
+        "commons"
+      ],
+      "type": "object"
+    },
+    {
+      "properties": {
+        "error": {
+          "type": "string"
+        },
+        "request_id": {
+          "type": "string"
+        }
+      },
+      "required": [
+        "error"
+      ],
+      "type": "object"
+    }
+  ],
+  "type": "object"
+}
  2. Added

TDQS

A3.6/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false. The description adds substantial behavioral detail: deterministic output, explicit error handling, rejection of target overlaps and reserved paths, missing-source behavior, output arrays not constructed, limits (24KB, depth 24, 4,000 nodes), security rejections, and transient input handling. This enriches the agent's understanding beyond the annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is dense but structured, front-loading the usage condition and then covering behavior and limits. It is not overly long, but the phrasing 'map json fields api' is clunky and the sentence order could be tightened. It earns a middle score for efficiency without being truly concise.

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?

Given the tool's complexity (mapping, error conditions, limits, security), the description covers nearly everything an agent needs: it states error behavior, size/depth limits, reserved key handling, and that outputs are not arrays. An output schema exists, so return format specifics are already structured. The only minor gap is the precise input type of 'value', but the mapping context implies an object.

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 coverage is only 40% (attractor_trace_id and attractor_knowledge_id have descriptions). The description compensates for the core parameters: it explains mapping as a source-to-target path projection and omit_missing as a toggle for missing-source errors. However, it does not specify the expected type or structure of 'value' beyond its name, leaving some ambiguity.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool maps JSON fields by projecting dotted source paths to dotted target paths, and that unmapped fields are omitted. It differentiates from siblings like flatten_json and canonicalize_json by its specific mapping function, though it doesn't name alternatives. The phrase 'map json fields api' is awkward but the core purpose is evident.

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

Usage Guidelines3/5

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

The opening line 'Use this tool when your workflow needs map json fields api' provides a usage condition but lacks explicit exclusions or named alternatives. It doesn't tell the agent when NOT to use it or what other tools handle different JSON transformations, leaving the routing partially implicit.

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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