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Glama

get_list

Read-onlyIdempotent

Open one list: its members (ordered by relevance to the list's goal) and the people noticed is SUGGESTING to add or remove, each with the reasoning behind it. Identify the list by list_id (from list_lists) or by list_name.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
list_idNoThe list's id (from list_lists / create_list). Pass this OR list_name.
list_nameNoThe list's name, matched case-insensitively. Pass this OR list_id.

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: +{
      +  "$schema": "http://json-schema.org/draft-07/schema#",
      +  "additionalProperties": true,
      +  "properties": {
      +    "data": {
      +      "additionalProperties": true,
      +      "description": "The operation result when ok is true.",
      +      "properties": {
      +        "ai_enabled": {
      +          "type": "boolean"
      +        },
      +        "description": {
      +          "type": [
      +            "string",
      +            "null"
      +          ]
      +        },
      +        "list_id": {
      +          "type": "string"
      +        },
      +        "member_count": {
      +          "type": "number"
      +        },
      +        "members": {
      +          "items": {
      +            "additionalProperties": true,
      +            "properties": {},
      +            "type": "object"
      +          },
      +          "type": "array"
      +        },
      +        "name": {
      +          "type": "string"
      +        },
      +        "organization_id": {
      +          "$ref": "#/properties/data/properties/description"
      +        },
      +        "pending_count": {
      +          "type": "number"
      +        },
      +        "pending_total": {
      +          "type": "number"
      +        },
      +        "suggestions": {
      +          "$ref": "#/properties/data/properties/members"
      +        }
      +      },
      +      "required": [
      +        "list_id",
      +        "name",
      +        "members",
      +        "suggestions",
      +        "pending_total"
      +      ],
      +      "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

A3.5/5.0
Behavior4/5

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

Annotations already indicate read-only and idempotent behavior. The description adds that results are ordered by relevance and include suggestion reasoning, which is not covered by annotations. No contradiction detected.

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 a single sentence but contains a grammatical error ('people noticed is SUGGESTING') and is slightly convoluted. It could be more concise and direct.

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

Completeness3/5

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

The description mentions members and suggestions but does not specify the exact return structure (e.g., whether list metadata is included). Given no output schema is provided, this is acceptable but incomplete.

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?

The schema already provides full parameter descriptions ('Pass this OR list_id'), and the description simply echoes them without adding new details. It does not clarify edge cases like mutual exclusivity or defaults.

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 opens a list and returns its members (ordered by relevance) and suggestions for additions/removals with reasoning, distinguishing it from list-mutation tools like add_to_list. However, the phrasing is awkward ('people noticed is SUGGESTING') and could be clearer.

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 description implies usage for retrieving list contents but does not explicitly state when to prefer this over other list-related tools. It identifies parameters but lacks explicit guidance on selecting between list_id and list_name or when not to use it.

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.

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