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world-model-mcp

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link_to_goal

Associate entities or regions with state-memory task nodes to define goals, unlink them, or extract a goal-relevant spatial slice via get_context. Mutates associations or returns read-only context.

Instructions

Link or unlink entities and regions to state-memory task nodes, or extract a goal-relevant spatial slice. Actions: link, unlink, get_context. link/unlink mutate association rows only. get_context is read-only. Returns {ok, action, links[]|context}. Use link_to_goal instead of record_outcome when associating entities with state-memory task nodes rather than recording physical movement deltas.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
notesNoContext notes
actionNoAction to perform: "link" (default), "unlink", or "get_context" to retrieve goal-relevant spatial slice
radiusNoProximity radius around agent for get_context action (default: 30)
projectNoOptional project identifier
task_idNoState memory task node ID
entity_idNoTarget entity ID to link/unlink
region_idNoTarget region ID to link
max_entitiesNoMaximum entities to return for get_context action (default: 20)
relationshipNoRole of entity relative to goal (default: target)
min_clearanceNoMinimum clearance distance required to satisfy the goal
success_regionNoSpatial bounding volume region defining goal arrival
target_entity_idNoDirect target entity ID for navigation and clearance tracking
current_agent_positionNoCurrent agent position for get_context action

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed3 schema fields changedv0.6.0
    • addedInput schema / properties / min_clearance
      Added value: +{
+  "description": "Minimum clearance distance required to satisfy the goal",
+  "type": "number"
+}
    • addedInput schema / properties / success_region
      Added value: +{
+  "description": "Spatial bounding volume region defining goal arrival",
+  "properties": {
+    "max": {
+      "properties": {
+        "x": {
+          "type": "number"
+        },
+        "y": {
+          "type": "number"
+        },
+        "z": {
+          "type": "number"
+        }
+      },
+      "type": "object"
+    },
+    "min": {
+      "properties": {
+        "x": {
+          "type": "number"
+        },
+        "y": {
+          "type": "number"
+        },
+        "z": {
+          "type": "number"
+        }
+      },
+      "type": "object"
+    }
+  },
+  "type": "object"
+}
    • addedInput schema / properties / target_entity_id
      Added value: +{
+  "description": "Direct target entity ID for navigation and clearance tracking",
+  "type": "string"
+}
  2. Changed1 schema field changedv0.5.1
    • addedInput schema / properties / action / enum
      Added value: +[
+  "link",
+  "unlink",
+  "get_context"
+]
  3. Changed4 schema fields changedv0.4.1
    • removedInput schema / $schema
      Removed value: -"http://json-schema.org/draft-07/schema#"
    • removedInput schema / additionalProperties
      Removed value: -false
    • removedInput schema / properties / action / enum
      Removed value: -[
-  "link",
-  "unlink",
-  "get_context"
-]
    • removedInput schema / properties / current_agent_position / additionalProperties
      Removed value: -true
  4. First observedv0.3.1

TDQS

A4.4/5.0
Behavior5/5

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

With annotations already covering readOnlyHint=false, destructiveHint=false, and idempotentHint=false, the description adds useful behavioral detail: link/unlink mutate association rows only, get_context is read-only, and it specifies the return shape. This clarifies the mixed read/write nature of the tool 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.

Conciseness5/5

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

The description is front-loaded with the core purpose and action variants, then adds mutation scope, return shape, and the sibling alternative. Every sentence contributes useful selection or invocation information without unnecessary padding.

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?

For a complex 13-parameter tool with nested objects and no output schema, the description supplies the key missing context: action behavior, read-only vs mutating distinctions, return shape, and the sibling alternative. It does not explain every parameter interaction, but the exhaustive schema descriptions carry that load.

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 input schema already documents all 13 parameters, including enums and nested objects. The description repeats the action values and return shape but does not add parameter-level meaning beyond the schema, making the baseline 3 appropriate.

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 states specific verbs and resources: linking/unlinking entities and regions to state-memory task nodes, plus extracting a goal-relevant spatial slice. It names the action variants and explicitly distinguishes itself from record_outcome, so an agent can route to it without opening the schema.

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

Usage Guidelines4/5

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

It gives a clear alternative: use link_to_goal instead of record_outcome when associating entities with state-memory task nodes rather than recording physical movement deltas. However, it does not address when to prefer get_context over neighbouring read tools such as query_entities or get_spatial_map.

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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