Skip to main content
Glama

Synapse Layer — Trust Infrastructure for AI Agents

by io.github.SynapseLayer
OverviewDiscussionsAdmin

initialize_context

Read-only

Initialize a persistent memory context for a conversation or agent session. Returns REDACTED metadata by default (detail="summary"). Use detail="full" with a reason (10–200 chars) to retrieve plaintext content under MEMORY_EXPORT_GOVERNANCE_V1.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
detailNoDetail level. "summary" (default) = redacted metadata only, no plaintext. "full" = plaintext content; REQUIRES the reason parameter and is audit-logged.
reasonNoREQUIRED only when detail="full" (10–200 chars). Audit policy: MEMORY_EXPORT_GOVERNANCE_V1. Human-readable justification for retrieving PLAINTEXT context. Without it, detail="full" WILL fail with code -32602.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
scopeYes
agent_idNo
memoriesNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • changedOutput schema / (root)
      Previous value: -nullNew value: +{
+  "properties": {
+    "agent_id": {
+      "type": "string"
+    },
+    "memories": {
+      "items": {
+        "type": "object"
+      },
+      "type": "array"
+    },
+    "scope": {
+      "enum": [
+        "agent",
+        "tenant"
+      ],
+      "type": "string"
+    }
+  },
+  "required": [
+    "scope"
+  ],
+  "type": "object"
+}
  2. Changed2 schema fields changed
    • addedInput schema / properties / detail
      Added value: +{
+  "description": "Detail level. \"summary\" (default) = redacted metadata only, no plaintext. \"full\" = plaintext content; REQUIRES the reason parameter and is audit-logged.",
+  "enum": [
+    "summary",
+    "full"
+  ],
+  "type": "string"
+}
    • addedInput schema / properties / reason
      Added value: +{
+  "description": "REQUIRED only when detail=\"full\" (10–200 chars). Audit policy: MEMORY_EXPORT_GOVERNANCE_V1. Human-readable justification for retrieving PLAINTEXT context. Without it, detail=\"full\" WILL fail with code -32602.",
+  "type": "string"
+}
  3. Changed2 schema fields changed
    • removedInput schema / properties / detail
      Removed value: -{
-  "description": "Detail level. \"summary\" (default) = redacted metadata only, no plaintext. \"full\" = plaintext content; REQUIRES the reason parameter and is audit-logged.",
-  "enum": [
-    "summary",
-    "full"
-  ],
-  "type": "string"
-}
    • removedInput schema / properties / reason
      Removed value: -{
-  "description": "REQUIRED only when detail=\"full\" (10–200 chars). Audit policy: MEMORY_EXPORT_GOVERNANCE_V1. Human-readable justification for retrieving PLAINTEXT context. Without it, detail=\"full\" WILL fail with code -32602.",
-  "type": "string"
-}
  4. Changed3 schema fields changed
    • addedInput schema / properties / detail
      Added value: +{
+  "description": "Detail level. \"summary\" (default) = redacted metadata only, no plaintext. \"full\" = plaintext content; REQUIRES the reason parameter and is audit-logged.",
+  "enum": [
+    "summary",
+    "full"
+  ],
+  "type": "string"
+}
    • addedInput schema / properties / reason
      Added value: +{
+  "description": "REQUIRED only when detail=\"full\" (10–200 chars). Audit policy: MEMORY_EXPORT_GOVERNANCE_V1. Human-readable justification for retrieving PLAINTEXT context. Without it, detail=\"full\" WILL fail with code -32602.",
+  "type": "string"
+}
    • changedOutput schema / (root)
      Previous value: -{
-  "additionalProperties": true,
-  "properties": {
-    "agent_id": {
-      "type": "string"
-    },
-    "count": {
-      "type": "number"
-    },
-    "error": {
-      "description": "Present only on fail-closed path.",
-      "type": "string"
-    },
-    "initialized": {
-      "type": "boolean"
-    },
-    "memories": {
-      "items": {
-        "additionalProperties": true,
-        "type": "object"
-      },
-      "type": "array"
-    },
-    "query": {
-      "type": "string"
-    },
-    "scope": {
-      "type": "string"
-    }
-  },
-  "required": [
-    "initialized",
-    "count",
-    "memories"
-  ],
-  "type": "object"
-}New value: +null
  5. Changed1 schema field changed
    • changedOutput schema / (root)
      Previous value: -nullNew value: +{
+  "additionalProperties": true,
+  "properties": {
+    "agent_id": {
+      "type": "string"
+    },
+    "count": {
+      "type": "number"
+    },
+    "error": {
+      "description": "Present only on fail-closed path.",
+      "type": "string"
+    },
+    "initialized": {
+      "type": "boolean"
+    },
+    "memories": {
+      "items": {
+        "additionalProperties": true,
+        "type": "object"
+      },
+      "type": "array"
+    },
+    "query": {
+      "type": "string"
+    },
+    "scope": {
+      "type": "string"
+    }
+  },
+  "required": [
+    "initialized",
+    "count",
+    "memories"
+  ],
+  "type": "object"
+}
  6. Added
  7. Removed
  8. Added

TDQS

A4.4/5.0
Behavior4/5

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

Beyond the annotations (readOnlyHint=true, openWorldHint=false), the description adds significant context about the audit-logging behavior of 'full' mode, the requirement for a human-readable justification, and the failure code without it. This provides essential behavioral detail that the annotations alone do not convey, especially regarding governance compliance.

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, with two sentences that efficiently convey purpose, behavior, and parameter nuances. It is well-structured with a clear front-loading of purpose followed by critical usage details for different detail levels, and every sentence is informative without waste.

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 tool with an output schema (implied by 'returns REDACTED metadata') and comprehensive parameter documentation, the description is largely complete. It explains the two modes, the dependency between parameters, and governance context. However, it could be slightly improved by briefly noting what happens if context is already initialized (e.g., whether it resets or updates) or if there are any side effects, given the 'initialize' verb suggests a starting state.

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

Parameters4/5

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

Schema coverage is 100%, and the description reinforces parameter usage by explaining that 'summary' returns redacted metadata while 'full' requires a reason and returns plaintext. It adds value beyond the schema by clarifying that 'reason' is strictly required for 'full' detail and mentioning the audit policy and error code, which aids selection.

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 initializes a persistent memory context for conversations or agent sessions, using specific verbs and resources. It distinguishes itself from sibling tools like 'list_memories' and 'recall' by focusing on initialization rather than retrieval, and it provides a clear distinction between the 'summary' and 'full' detail levels.

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?

The description explicitly guides when to use each detail level, specifying that 'summary' is the default and 'full' requires a reason parameter under audit policy. However, it doesn't explicitly clarify when NOT to use this tool versus initializing memory via other means or when initialization is unnecessary, such as if context already exists.

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

All Synapse Layer — Trust Infrastructure for AI Agents toolsInspect
Try in Browser
One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

Glama MCP Gateway

Add one secure layer between your agents and this server.

Resources