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GoodSender

by io.github.good-sender
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List Posts

list_posts
Read-onlyIdempotent

List all posts (draft and published) for the API key's workspace blog.

The only view of the blog a new post is written into, and the source for three things a draft would otherwise invent:

  • The byline: Author, AuthorURL and AuthorAvatarURL of the most recent post. upload_post_image returns URLs accepted for new author photos.

  • The taxonomy: the Tags and Categories already in use. Each distinct term generates its own public index page, so near-duplicates such as AI, ai and artificial-intelligence become three pages of one post instead of one page of three.

  • The house voice, and whether the topic has already been covered.

Also returns each post's PostID, Status and LastBroadcastAt.

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

No arguments

Output Schema

NameRequiredDescriptionDefault
PostsYesPosts for the workspace blog.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already declare read-only, idempotent, non-destructive behavior. The description adds useful context beyond that: drafts and published posts are both returned, each post includes PostID/Status/LastBroadcastAt, and taxonomy terms create public index pages. It does not mention ordering or volume, but the added behavioral context is substantive.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Front-loaded with the core purpose, then structured into three bullets for byline, taxonomy, and voice. Most sentences earn their place, though the 'a draft would otherwise invent' framing is slightly flourishy.

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 zero parameters, rich annotations, and an output schema, the description is largely complete. It explains why an agent should list posts before drafting and what kinds of data come back, though it omits any ordering or pagination expectations for a potentially large listing.

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?

The tool takes zero parameters, so there are no parameters for the description to clarify. Baseline 4 applies because no parameter-level guidance is needed.

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?

States a specific verb and resource ('List all posts') with clear scope ('draft and published', 'API key's workspace blog'), immediately distinguishing it from single-post siblings like get_post and write siblings like create_post.

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?

Gives explicit usage context: it is 'the only view of the blog a new post is written into' and the source for byline, taxonomy, and house voice. It clearly implies when to use it before drafting, though it does not state when not to use it or name a direct alternative.

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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