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flag_attention

Flag a task as awaiting your input or decision. Use the note to state what you need, making the task stand out and ring a bell until you respond.

Instructions

Flag a task as awaiting the user's attention — e.g. you need a decision or input to proceed. note should say what you need (a short question). This makes the task stand out and rings a bell in the user's interactive board. Call clear_attention once the user has responded.

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": {
      "task_id": "<task_id>"
    },
    "name": "flag_attention"
  }
}

Input Schema

Name	Required	Description	Default
`note`	No
`task_id`	Yes

Output Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Aug 1, 2026

TDQS

A4.7/5.0

Behavior4/5

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

No annotations are present, so the description carries the full behavioral burden. It explains the effect ('makes the task stand out and rings a bell'), what the note should contain, and the lifecycle (clearing via clear_attention). It does not mention permissions or failure modes, but for a simple flagging operation this is adequate.

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 three sentences, front-loaded with the main action. Every sentence contributes: purpose, note instruction, and the clear_attention follow-up. No wasted words.

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

Completeness5/5

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

For a simple 2-parameter tool with an output schema, the description fully covers what, when, and how to invoke, plus the complementary follow-up. It is sufficiently complete without needing to explain return values (handled by output schema).

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?

The schema has 0% description coverage, but the description explains `note` well: 'should say what you need (a short question).' The `task_id` parameter is self-explanatory from the tool's purpose (flagging a task), though not explicitly described. This largely compensates for the schema gap.

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 states a specific verb and resource: 'Flag a task as awaiting the user's attention.' This clearly distinguishes it from sibling tools like clear_attention (which removes the flag) and transition_task (which changes status).

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

Usage Guidelines5/5

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

It provides explicit when-to-use context: 'e.g. you need a decision or input to proceed.' It also names the complementary tool and follow-up action: 'Call clear_attention once the user has responded.' This offers clear guidance on usage and alternatives.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.