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edit_note

Modify existing notes in Remember The Milk by updating content, title, or linking to specific tasks and lists.

Instructions

Edit an existing note.

Args: note_id: ID of the note to edit note_text: New note content note_title: New title (optional) task_name: Task name to search for task_id: Specific task ID taskseries_id: Task series ID list_id: List ID

Returns: Updated note details

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
note_idYes
note_textYes
note_titleNo
task_nameNo
task_idNo
taskseries_idNo
list_idNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior2/5

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

No annotations are provided, so the description carries the full burden. It states 'Edit an existing note' and mentions returns 'Updated note details', which implies mutation but lacks details on permissions, error handling, or side effects. For a mutation tool with zero annotation coverage, this is insufficient, as it doesn't disclose behavioral traits like whether edits are reversible or require specific auth.

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 structured with a clear purpose statement and sections for Args and Returns, but it's verbose without adding necessary context. The Args section repeats parameter names without explanation, and the Returns section is vague. It could be more front-loaded and concise by integrating key details into the opening sentence.

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 complexity (7 parameters, mutation tool, no annotations) and the presence of an output schema, the description is partially complete. It states the purpose and lists parameters but lacks usage guidelines, behavioral details, and parameter semantics. The output schema helps, but the description should do more to compensate for missing annotations and low schema coverage.

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%, so the description must compensate. It lists parameters in an 'Args' section but provides no semantic meaning beyond names. For example, it doesn't explain what 'taskseries_id' or 'list_id' are, how they relate to the note, or why multiple task-related parameters exist. With 7 parameters and low coverage, this adds minimal value over the schema.

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 tool's purpose: 'Edit an existing note.' It specifies the verb ('Edit') and resource ('note'), distinguishing it from sibling tools like 'add_note' and 'delete_note'. However, it does not explicitly differentiate from similar tools like 'set_task_name' or 'rename_list', which might also involve editing, so it's not a perfect 5.

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?

The description provides no guidance on when to use this tool versus alternatives. It does not mention prerequisites, such as needing an existing note, or compare it to siblings like 'add_note' or 'delete_note'. Usage is implied by the name but not explicitly stated, leaving gaps for an AI agent.

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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