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colab-drive-mcp

colab-drive-mcp

by YummyTastyCode
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

clear_local_outputs

Removes all cell outputs and execution counts from a local Jupyter notebook to reduce file size and reset the notebook state for sharing or version control.

Instructions

Clear outputs and execution counts from a local notebook.

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": {
      "path": "<path>"
    },
    "name": "clear_local_outputs"
  }
}

Input Schema

NameRequiredDescriptionDefault
pathYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.3

TDQS

C2.4/5.0
Behavior2/5

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

With no annotations, the description must fully disclose behavior. It states outputs are cleared, which is destructive, but does not mention if the operation is reversible, if it affects other parts of the notebook, or if specific permissions are needed. The behavioral impact is only partially described.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single sentence, making it concise, but it is too brief to be informative. It lacks structure and front-loads the key action but omits necessary details.

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?

Given the tool has one required parameter, no output schema, and no annotations, the description is insufficient. It does not explain what 'path' means, what the result of clearing outputs is, or how to handle the action. More context is needed for an agent to use it correctly.

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

Parameters1/5

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

The only parameter, 'path', is not explained in the description. With 0% schema description coverage, the agent has no idea what 'path' refers to (e.g., file path, notebook ID). This is a critical 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 clearly states the action ('clear outputs and execution counts') and the resource ('local notebook'), which is specific and distinct from siblings. However, it does not explicitly differentiate from similar tools like 'delete_local_cell' or 'update_local_cell'.

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 guidance is provided on when to use this tool versus alternatives. For example, it does not mention that this is useful for cleaning a notebook before sharing or that it is a destructive operation. No exclusions or when-not-to-use are given.

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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