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Castle MCP by usefulapi

Add an item to a list

castle_create_list_item
Destructive

Add an entry to a list — for example block an IP or an email. This changes live policy behaviour. Castle: POST /v1/lists/{list_id}/items.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
commentNoWhy this entry was added.
list_idYesThe list to add to.
author_typeYesWhat kind of actor is adding this entry.
primary_valueYesThe value to add, matching the list's primary_field.
secondary_valueNoValue for the list's secondary_field.
auto_archives_atNoISO-8601 time to archive the entry automatically.
author_identifierYesWho is adding it, e.g. the analyst's email address.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • changedInput schema / $schema
      Previous value: -"http://json-schema.org/draft-07/schema#"New value: +"https://json-schema.org/draft/2020-12/schema"
  2. First observed

TDQS

A3.8/5.0
Behavior4/5

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

Annotations only declare destructiveHint=true; the description earns credit by explaining why, stating 'This changes live policy behaviour,' which tells the agent the write has immediate enforcement impact rather than being an inert data edit. It still omits auth requirements, duplicate-handling/idempotency, and reversibility, so it is not fully transparent.

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 short sentences plus the endpoint reference, with the action front-loaded and the impact warning immediately after. No sentence is wasted and there is no padding.

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 mutation tool with no output schema, the description covers purpose, concrete use case, live-policy impact, and the backing endpoint, and the schema fully documents parameters. What remains uncovered is duplicate entries, error conditions (e.g. value not matching the list's primary_field), and the response shape.

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% with all seven parameters documented, so the baseline is 3. The description adds only the endpoint hint (POST /v1/lists/{list_id}/items) and no extra meaning for required fields such as author_type, author_identifier, or the primary/secondary value pairing.

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 gives a specific verb and resource ('Add an entry to a list') and reinforces intent with a concrete example ('block an IP or an email'), which makes the operation unambiguous. It does not, however, explicitly contrast itself with nearest siblings like castle_create_list or castle_update_list_item, so it falls just short of the top band.

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 example ('block an IP or an email') implies the usage context, but there is no explicit when-to-use or when-not-to-use statement and no named alternative among the many list-related siblings. An agent can infer intent, but the routing guidance is left 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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