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List posts

list-posts
Read-only

List posts for the current organization. Supports filtering by status and pagination.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "list-posts"
  }
}

Input Schema

NameRequiredDescriptionDefault
limitNoNumber of posts to return (max 50, default 20)
statusNoFilter posts by status (PENDING_APPROVAL = waiting for an owner/admin to approve)

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changed
    • changedInput schema / properties / status / description
      Previous value: -"Filter posts by status"New value: +"Filter posts by status (PENDING_APPROVAL = waiting for an owner/admin to approve)"
    • changedInput schema / properties / status / enum
      Previous value: -[
      -  "DRAFT",
      -  "SCHEDULED",
      -  "PUBLISHED"
      -]New value: +[
      +  "DRAFT",
      +  "SCHEDULED",
      +  "PUBLISHED",
      +  "PENDING_APPROVAL"
      +]
  2. First observed

TDQS

A3.6/5.0
Behavior3/5

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

The annotations already declare this as a safe, read-only, non-destructive operation, so the safety burden is covered. The description adds useful scoping context with 'current organization' and mentions status filtering and pagination, but it does not clarify return shape or how pagination actually works beyond the 'limit' parameter.

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 two tightly packed sentences with no wasted language. The key scope constraint and supported capabilities are front-loaded.

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 simple read-only list tool with full parameter descriptions and explicit safety annotations, the description provides enough context to invoke it correctly. The main remaining gap is that no output schema exists and the description does not describe return values, though for a standard list endpoint the gap is minor.

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%, and both parameters already have clear schema-level descriptions, including the status enum values and limit bounds. The description mentions status filtering and pagination but adds no syntax, defaults, or semantics beyond what the schema provides.

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 states a specific verb and resource: 'List posts for the current organization.' It is clear this is a collection-level read rather than a single-post lookup like the sibling get-post, though it does not explicitly name or differentiate against siblings.

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 by noting status filtering and pagination support, but it does not say when to choose list-posts over alternatives such as get-post or search-viral-tweets. The use case is inferable from the name and scope rather than explicitly guided.

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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