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Glama

noticed

by so.noticed.mcp

update_list

DestructiveIdempotent

Rename a list, change the specific goal noticed matches suggestions against, or enable/disable AI suggestions. Identify it by list_id or an unambiguous list_name.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameNoNew list name.
list_idNoThe list id. Pass this OR list_name.
list_nameNoThe list name, matched case-insensitively. Pass this OR list_id.
ai_enabledNoWhether noticed should suggest additions and removals.
descriptionNoNew suggestion goal for the list.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
okYesWhether noticed completed the operation.
dataNoThe operation result when ok is true.
errorNoA human-readable error when ok is false.

Schema Changelog

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

  1. Changed1 schema field changed
    • changedOutput schema / (root)
      Previous value: -nullNew value: +{
+  "$schema": "http://json-schema.org/draft-07/schema#",
+  "additionalProperties": true,
+  "properties": {
+    "data": {
+      "additionalProperties": true,
+      "description": "The operation result when ok is true.",
+      "properties": {
+        "ai_enabled": {
+          "type": "boolean"
+        },
+        "description": {
+          "type": [
+            "string",
+            "null"
+          ]
+        },
+        "list_id": {
+          "type": "string"
+        },
+        "member_count": {
+          "type": "number"
+        },
+        "name": {
+          "type": "string"
+        },
+        "organization_id": {
+          "$ref": "#/properties/data/properties/description"
+        },
+        "pending_count": {
+          "type": "number"
+        }
+      },
+      "required": [
+        "list_id",
+        "name"
+      ],
+      "type": "object"
+    },
+    "error": {
+      "description": "A human-readable error when ok is false.",
+      "type": "string"
+    },
+    "ok": {
+      "description": "Whether noticed completed the operation.",
+      "type": "boolean"
+    }
+  },
+  "required": [
+    "ok"
+  ],
+  "type": "object"
+}
  2. First observed

TDQS

C2.5/5.0
Behavior2/5

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

Annotations (readOnlyHint: false, idempotentHint: true, destructiveHint: true) already provide a safety profile, so the bar for added value is lower, but the description adds zero behavioral context about what is destructive (e.g., does disabling AI suggestions destroy existing goals?). The description does not contradict the annotations, but for a tool flagged as destructive, an agent is left uninformed about side effects.

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?

At 35 words across two sentences, the description is compact and non-redundant; the second sentence earns its place by clarifying the list-identification contract. However, the opening sentence crams in a garbled clause that forces re-reading, so the efficient structure is undercut by the confusing phrasing.

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

Completeness2/5

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

With 5 optional parameters and three distinct sub-behaviors, an agent needs a clear semantic map, but the description covers only the mechanics of renaming and toggling suggestions, while leaving the 'goal' concept opaque and failing to clarify the destructive implications flagged by destructiveHint: true. The presence of an output schema excuses the absence of return-value docs, but the core semantic gaps remain.

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 baseline 3 applies. The description adds a loose mental model connecting 'goal', 'suggestions', and the list, but this is done awkwardly, and the schema's own parameter descriptions (e.g., 'New suggestion goal for the list') are actually clearer than the top-level description's attempt at paraphrase. The description adds little beyond what the 5 well-documented parameters already convey.

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

Purpose3/5

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

The description names specific operations ('Rename a list', 'enable/disable AI suggestions') and clarifies identification semantics, which distinguishes it from sibling list tools like create_list, delete_list, and get_list. However, the middle clause 'change the specific goal noticed matches suggestions against' is garbled and obscures what the 'description' parameter actually does. This materially hurts an agent's ability to understand one of the three core operations.

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

Usage Guidelines2/5

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

There is no when-to-use guidance versus sibling tools like create_list, delete_list, add_to_list, or remove_from_list. The only routing nuance offered is that list identification can be by list_id or an unambiguous list_name, which is a genuine but thin hint, and there is no exclusion explaining when NOT to use list_name beyond unambiguity, nor any mention of preconditions.

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

All noticed toolsInspect
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TDQS

B3.4/5.0
Disambiguation3/5

The tool set is organized around distinct resources, and the descriptions work hard to separate them, but several close pairs remain easy to confuse: add_memory vs memory_save vs add_note, accept_identity_match vs suggest_identity_match, and dismiss_identity_match vs mark_different_people. An agent will often need to read very subtle signals (who originated the content, pending vs initiating a merge, soft vs durable rejection) to pick the right tool.

Naming Consistency3/5

Most tools follow a clear verb_noun snake_case pattern like create_list, update_person, and delete_view, which is readable and mostly predictable. However, the memory tools break the pattern (memory_save, memory_get, memory_search instead of save_memory/get_memory/search_memory), and a few noun-style names (my_profile, network_summary, account_status) add inconsistency.

Tool Count1/5

At 57 tools, this is an extremely large surface that exceeds the calibration threshold for an extreme mismatch. The scope is broad, but many tools are micro-specialized variations of the same concept, such as four memory-related tools and seven identity-match tools, which makes the count feel inflated rather than well-scoped.

Completeness4/5

The tool set provides thorough lifecycle coverage for the core domain: people can be added, updated, searched, and removed; lists, views, actions, and scheduled tasks have create/read/update/delete; and identity matching has accept, dismiss, differentiate, and suggest paths. Minor gaps exist, such as no direct memory/note deletion or intro deletion, but agents can generally complete workflows without hitting dead ends.

Resources