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granoflow

Granoflow MCP Server

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by granoflow

granoflow_task_import

Import AI-agent task results into Granoflow. Use dry run to preview changes before writing.

Instructions

Import an AI-agent task result into Granoflow. Use dryRun first unless the user explicitly asks to write.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
inputYesJSON object sent to the Granoflow Local HTTP API.
dryRunNoWhen true, previews the request without writing.
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. It discloses the safe default behavior (dryRun preview) and mentions the local HTTP API, but lacks details on side effects, permissions, or whether the import is destructive. Some traits are transparent, but more is needed.

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 extremely concise at two sentences, with the purpose front-loaded and no wasted words. Every sentence adds necessary information, making it efficient for an agent to parse.

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?

Given the tool has two parameters and no output schema, the description is adequate but incomplete. It explains the core behavior (import with dryRun) but lacks details on return values, prerequisites (e.g., API availability), and positioning among siblings.

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

Parameters4/5

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

Schema description coverage is 100% for both parameters. The tool description adds value by providing a usage guideline for dryRun ('Use dryRun first'), which is beyond the schema's description. This enhances understanding beyond the baseline.

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 clearly states the purpose as 'Import an AI-agent task result into Granoflow,' using a specific verb and resource. It distinguishes this tool from siblings like granoflow_task_export and granoflow_task_create by focusing on importing a task result.

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?

The description provides a clear usage guideline: 'Use dryRun first unless the user explicitly asks to write.' However, it does not explain when to use this tool versus alternatives (e.g., task_create, task_complete) or exclude any contexts, leaving some ambiguity.

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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