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delete_list

Destructive

Permanently delete a list and its membership/suggestion ledger. People remain in the network. Identify it by list_id or an unambiguous list_name.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
list_idNoThe list id. Pass this OR list_name.
list_nameNoThe list 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": false,
      +      "description": "The operation result when ok is true.",
      +      "properties": {
      +        "deleted": {
      +          "type": "boolean"
      +        },
      +        "list_id": {
      +          "type": "string"
      +        }
      +      },
      +      "required": [
      +        "list_id",
      +        "deleted"
      +      ],
      +      "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

A4.4/5.0
Behavior4/5

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

Annotations already declare destructiveHint=true and readOnlyHint=false. The description adds meaningful context: it deletes 'its membership/suggestion ledger' and explicitly states 'People remain in the network'. This goes beyond the annotations by explaining what exactly is destroyed and what is preserved. No contradiction with annotations (both indicate a write/destructive operation).

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 three short sentences: purpose, key side-effect, and identification method. It is front-loaded with the primary action, then adds crucial non-destructive context, then parameter guidance. No filler words; every sentence earns its place.

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?

The description covers the essential aspects for a delete operation: what is deleted, what is preserved, and how to identify the target. It does not mention any prerequisites like permissions or confirmation, but given the annotations already flag destructive behavior and the tool has an output schema, this is sufficient. It could have mentioned alternatives but that is not necessary for correct invocation.

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 each parameter already has a description. The description adds the instruction 'unambiguous list_name', which is a useful semantic constraint not present in the schema (the schema only says 'matched case-insensitively'). It also reinforces the OR relationship between the two parameters. This adds value beyond the schema, so a score above baseline is warranted.

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 a specific verb ('delete') and resource ('list'), and clarifies the scope: 'its membership/suggestion ledger'. This distinguishes it from other delete tools like delete_action and delete_view. It also clarifies that 'People remain in the network', which differentiates from deleting people. The purpose is unambiguous and distinct from siblings.

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 gives useful context for when to use this tool: to delete a list and its ledger, while noting that people are not removed. However, it does not explicitly mention alternatives like remove_from_list for just removing a member, or reject_list_suggestion for discarding a suggestion. It implies the use case but does not explicitly route away from those alternatives. Still, it provides enough context for an agent to understand the intent.

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