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noticed

by so.noticed.mcp

create_view

Create a saved live View over a personal or Team network. Its definition stores search, filters, sort, Team-member filters, relationship types, and visible columns.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameNoShort View name; generated when omitted.
definitionYes
descriptionYesWhat this View is for.
organization_idNoTeam id for a Team View; omit for personal.

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: +{
+  "$schema": "http://json-schema.org/draft-07/schema#",
+  "additionalProperties": true,
+  "properties": {
+    "data": {
+      "additionalProperties": true,
+      "description": "The operation result when ok is true.",
+      "properties": {
+        "created_at": {
+          "type": "string"
+        },
+        "definition": {
+          "additionalProperties": true,
+          "properties": {},
+          "type": "object"
+        },
+        "description": {
+          "type": [
+            "string",
+            "null"
+          ]
+        },
+        "effective_role": {
+          "type": "string"
+        },
+        "name": {
+          "type": "string"
+        },
+        "organization_id": {
+          "$ref": "#/properties/data/properties/description"
+        },
+        "updated_at": {
+          "type": "string"
+        },
+        "view_id": {
+          "type": "string"
+        }
+      },
+      "required": [
+        "view_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

A4.2/5.0
Behavior3/5

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

Annotations provide only false hints (readOnlyHint, idempotentHint, destructiveHint), so the description carries most of the behavioral disclosure burden. It states the view is 'saved' and 'live', implying persistence and real-time effects, but does not mention uniqueness constraints, overwrite behavior, permission requirements, or side effects. This is adequate but not comprehensive for a creation tool.

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?

Two sentences with no fluff. The primary purpose is front-loaded in the first sentence, and the second sentence enumerates the definition's components without redundancy. Every word contributes value, making it highly efficient for an agent to parse.

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 (nested definition object) and that an output schema exists (so return values are handled separately), the description covers the key aspects of what the view is and what it contains. It does not detail prerequisites like team membership or naming rules, but these are partially addressed by the schema (e.g., name optional). The description is nearly complete for an agent to understand the tool's role, though a mention of when team vs personal is chosen could add clarity.

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 75% (below the high threshold), so the description should add meaning beyond the schema. It does: it lists the components of the 'definition' object (search, filters, sort, Team-member filters, relationship types, visible columns) and clarifies 'personal or Team network' for organization_id. This gives the agent a conceptual map of what the definition parameter contains, supplementing the schema's structural detail.

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 begins with a specific verb ('Create') and a clear resource ('saved live View'), then scopes it to 'personal or Team network'. It distinguishes this from sibling tools like update_view, delete_view, and get_view, making the tool's role unambiguous. The enumeration of what the definition stores further clarifies its purpose without ambiguity.

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 verb 'Create' and the context of a 'saved live View' clearly indicate this is for creating new views, while siblings like update_view and delete_view exist for modifications and removals. However, the description does not explicitly mention alternatives or state when not to use this tool, leaving the differentiation largely to inference.

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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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