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PaperGraph MCP

PaperGraph MCP

by lotchuazzz-crypto
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Hybrid

workspace_get_reading_queue

Retrieve a persistent reading queue by ID to return ordered items, restoring saved paper lists for continuous study and focused follow-up.

Instructions

Return one persistent reading queue with ordered items.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "queue_id": "<queue_id>"
    },
    "name": "workspace_get_reading_queue"
  }
}

Input Schema

NameRequiredDescriptionDefault
queue_idYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv0.9.3

TDQS

B3.4/5.0
Behavior3/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It does add useful traits: the queue is persistent and the items are ordered. However, it does not disclose behavior for invalid or missing queue_id, whether the operation is read-only, or what the returned object structure looks like beyond 'ordered items'.

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 a single, front-loaded sentence with no filler. 'Persistent' and 'ordered items' are meaningful qualifiers that add value without bloating the text.

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

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The description conveys the core returned item concept: one persistent reading queue with ordered items. However, given no output schema and no annotations, it leaves gaps around error behavior, queue existence, and how this getter fits with related queue operations.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The description does not explain queue_id at all, and schema description coverage is 0%. The single parameter is inferable from its name and the tool's 'get' semantics, so this is not severely misleading, but the description fails to compensate for the missing schema descriptions.

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?

The description uses a specific verb ('Return') and names the exact resource ('one persistent reading queue') while adding that it contains ordered items. This clearly distinguishes it from sibling tools like workspace_list_reading_queues, which lists many queues, and workspace_create_reading_queue, which creates a queue.

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 on when to use this tool versus alternatives such as workspace_list_reading_queues or workspace_apply_reading_queue_to_session. There are no explicit conditions, prerequisites, or exclusions; the usage context is only implicitly suggested by the tool name and queue_id parameter.

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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