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PaperGraph MCP

PaperGraph MCP

by lotchuazzz-crypto
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Hybrid

workspace_apply_reading_queue_to_session

Apply reading queue items to a session as checkpoints, setting statuses to track progress and ensure systematic study.

Instructions

Apply reading queue items as checkpoints in a reading session.

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>",
      "session_id": "<session_id>"
    },
    "name": "workspace_apply_reading_queue_to_session"
  }
}

Input Schema

NameRequiredDescriptionDefault
statusNoqueued
queue_idYes
session_idYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv0.9.3

TDQS

C2.7/5.0
Behavior2/5

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 only implies mutation through 'apply' but does not state side effects such as whether checkpoints are created, whether the queue is modified, or whether existing session checkpoints are affected.

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?

The description is a single, front-loaded sentence with no filler. It conveys the essential operation efficiently, though it could add a bit more detail without becoming verbose.

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

Completeness2/5

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

Without annotations or an output schema, this minimal description is insufficient for a mutation-like tool. An agent is left to guess side effects, required preconditions, the role of the optional status parameter, and what the operation returns.

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?

Schema description coverage is 0%, and the description adds no meaning to queue_id, session_id, or the status parameter with default 'queued'. The parameter names are somewhat self-explanatory, but 'status' remains unexplained, and the description does not compensate for the schema gap.

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 action ('Apply reading queue items') and target context ('as checkpoints in a reading session'), which clarifies the tool's core purpose. It is distinguishable from siblings like workspace_record_reading_checkpoint, though it does not explicitly call out that distinction.

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?

No usage guidance is provided. The description does not explain when to choose this tool over workspace_record_reading_checkpoint or workspace_create_reading_queue, nor does it mention prerequisites like an existing session or queue.

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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