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goodnotes_run_study_board

Executes bounded steps of a prepared native learning board, verifying text, style, layout, and appearance after reload. Resumes from verified receipts without duplicate writes and stops uncertain writes for review.

Instructions

Execute bounded steps of a prepared native learning board. Each block verifies text/style/layout/appearance after reload; verified receipts resume without duplicate writes. Uncertain writes stop for review. Returns progress and timings.

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": {
      "workflowId": "<workflowId>"
    },
    "name": "goodnotes_run_study_board"
  }
}

Input Schema

NameRequiredDescriptionDefault
maxStepsNo
workflowIdYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.21.1

TDQS

A3.5/5.0
Behavior4/5

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

Annotations only declare readOnlyHint=false, destructiveHint=false and openWorldHint=true; the description adds substantial context: per-block verification of text/style/layout/appearance after reload, idempotent resume from verified receipts without duplicate writes, and a halt-for-review behavior on uncertain writes. It also discloses that progress and timings are returned. It does not say what happens to partially applied state when a halt occurs.

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?

Four short sentences, front-loaded with the action, then the correctness guarantees, then the return shape. No filler and nothing is buried.

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?

For a mutating, open-world tool with no output schema, the description covers the verification and resume semantics well and even names the return payload. However, it leaves the sole required parameter's provenance unexplained and omits what a 'halt for review' means operationally, which an agent needs in order to recover.

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% for two parameters, so the description must compensate and it does not: neither workflowId (where the ID originates, required) nor maxSteps (default 1, maximum 1) is mentioned. 'Bounded steps' only faintly gestures at maxSteps without explaining the effectively fixed step size.

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?

States a specific verb and resource: execute bounded steps of a prepared native learning board. The word 'board' distinguishes it from the run_study_collection and run_study_revision siblings, and 'prepared' signals the tool operates on already-planned state. It stops short of explicitly naming which sibling to use instead.

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?

'Prepared' implies a preceding goodnotes_prepare_study_board / plan step, and 'verified receipts resume' implies re-invocation after interruption, so usage context is inferable. No explicit when-to-use, when-not-to-use, or alternative-tool guidance is given, and the interplay with review_study_board or study_board_status is left unstated.

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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