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AIMFP

AIMFP

by aryanduntley
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

batch_update_progress

Update multiple project items atomically to maintain consistency after code generation or bulk operations.

Instructions

Update multiple project items atomically. Used after code generation or bulk operations to ensure consistency.

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": {
      "updates": "<updates>"
    },
    "name": "batch_update_progress"
  }
}

Input Schema

NameRequiredDescriptionDefault
updatesYesList of update objects: [{target_type, target_id, action, data}, ...]
transactionNoAll-or-nothing commit vs independent updates
continue_on_errorNoStop on first error or continue processing remaining updates

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.37.0

TDQS

A4.2/5.0
Behavior4/5

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

The description adds behavioral insight beyond annotations by stating 'atomically' and implying transactional integrity. Annotations already indicate non-destructive and non-idempotent behavior, but atomicity is a key additional trait disclosed here.

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 with two sentences. The first sentence states the purpose, the second provides usage context. No superfluous words, effectively front-loaded.

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

Completeness4/5

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

For a tool with three parameters and no output schema, the description covers the core purpose and usage context adequately. It does not detail return values or error handling, but given the annotations and schema, it is sufficient for an agent to use the tool correctly.

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

Parameters3/5

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

Schema coverage is 100%, so all parameters have descriptions. The tool-level description does not add extra meaning to parameters beyond what the schema provides, hence baseline score of 3.

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 tool updates multiple project items atomically, with a specific verb ('Update') and resource ('project items'). It distinguishes itself from siblings by emphasizing atomicity and batch operation, which is not available in individual update tools.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides explicit context: 'Used after code generation or bulk operations to ensure consistency.' This tells the agent when to use it, but it does not explicitly mention when not to use it or list alternative tools like individual updates. However, the context is clear.

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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