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Post Bridge

by io.github.jackfriks
OverviewDiscussionsAdmin

list_posts

Read-only

List your posts with optional filters. Returns post ID, caption, status (scheduled, processing, posted), is_draft flag, scheduled time, and associated accounts. Drafts have status 'scheduled' with is_draft: true and scheduled_at: null.

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 (default 50)
offsetNoOffset for pagination
statusNoFilter by status: scheduled, processing, or posted. Drafts have status 'scheduled' — use is_draft on results to distinguish.
platformNoFilter by platform (e.g. instagram, tiktok, youtube, twitter, facebook, linkedin, pinterest, bluesky, threads, google_business)

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.7/5.0
Behavior4/5

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

Annotations already mark the operation as read-only and non-destructive. The description adds meaningful behavioral context beyond that: drafts use status 'scheduled' with is_draft: true and scheduled_at: null, which is essential for correctly interpreting filtered results. This prevents a likely misinterpretation when filtering by status.

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 sentences deliver the purpose, return fields, and a subtle behavioral caveat with no wasted words. The core action is front-loaded and the additional draft clarification is directly relevant to interpreting results.

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

Completeness5/5

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 no required parameters and full schema coverage, the description is complete. It specifies the return fields, covers the tricky draft/status edge case, and benefits from annotations that already establish safety. No critical information needed to call the tool correctly is missing.

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%, so the parameters (limit, offset, status, platform) are already well documented. The description does not add parameter-specific details beyond what the schema provides, matching the baseline of 3.

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's function: 'List your posts with optional filters' and enumerates the returned fields (post ID, caption, status, is_draft, scheduled time, accounts). This distinguishes it from the more specific get_post sibling, though it does not explicitly name any alternative tool.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description gives no guidance about when to use this tool versus siblings like get_post or list_post_results. The phrase 'List your posts' implies the basic use case, but there are no explicit conditions, exclusions, or references to alternatives, leaving the agent to infer selection criteria.

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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