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Glama

get_post_queue

Read-only

Retrieve the posting plan of LinkedIn and X posts marked ready or scheduled across all projects, sorted by time, so you can review status and next actions.

Instructions

The posting plan: every LinkedIn and X post the user marked ready or that is scheduled, across all projects, sorted by time. Each has platform, session, title, text (X: also 'tweets'), media_path (the video to upload), status, at (iso, utc, local in the chosen tz, this_mac = the Mac's zone, which LinkedIn's scheduler uses) and 'action': what to do on that platform now (schedule, move, replace text, delete, or nothing). The user sets the times with [schedule] on the post tab, or asks you to pick them.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
draftsNoAlso list drafts (not marked ready yet), e.g. for a pipeline overview. Default false.
postedNoAlso list posts already live. Default false.
platformNoOptional: only this platform.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.7/5.0
Behavior4/5

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

Annotations already establish a safe read (readOnlyHint=true, destructiveHint=false, openWorldHint=false), and the description adds genuinely useful context beyond them: the per-item 'action' field values (schedule, move, replace text, delete, nothing) and the timezone semantics (this_mac vs LinkedIn's scheduler zone). This is meaningful behavioral context, not restatement.

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 resource definition before the field enumeration, and there is no filler. The single long sentence dense with parentheticals is slightly heavy but every clause (fields, timezone, action) carries information that would otherwise be missing.

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?

With no output schema, the description correctly compensates by enumerating the returned fields (platform, session, title, text/tweets, media_path, status, at, action) and explaining timezone behavior. Combined with fully-covered params and safety annotations, an agent has what it needs; only pagination/ordering edge behavior is unaddressed.

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 coverage is 100%, so all three optional params are documented in the schema and the baseline is 3. The description reinforces the default filter ('marked ready or that is scheduled', LinkedIn/X only) but adds no syntax or edge-case detail beyond the schema's enum and defaults.

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 names the resource precisely ('the posting plan') and scopes it clearly: LinkedIn and X posts that are marked ready or scheduled, across all projects, sorted by time. This distinguishes the default output from drafts and posted items. It stops short of naming a sibling to route against, so 4 rather than 5.

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?

Usage is implied through context ('The user sets the times with [schedule] on the post tab, or asks you to pick them'), which hints at when the queue is relevant. However, there is no explicit when-to-use statement or named alternative (e.g. post_history, get_plan), leaving selection to inference.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.