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label

Organize notebook sources into thematic groups with AI auto-categorization and manual actions for creating, renaming, moving sources, and deleting groups. Supports emoji and batch operations.

Instructions

Manage source labels in a notebook. Unified tool for all label operations.

Labels let you organize sources into thematic categories. Requires 5+ sources for auto-labeling. Sources can belong to multiple labels simultaneously.

Supports: auto, list, reorganize, create, rename, set_emoji, move_source, delete

Args: notebook_id: Notebook UUID action: Operation to perform: - auto: AI auto-labels all sources into thematic categories - list: List current labels (triggers AI if none exist) - reorganize: Force AI re-categorization (requires confirm=True unless unlabeled_only=True) - create: Create a new empty label (requires name) - rename: Rename a label (requires label_id, name) - set_emoji: Set or clear emoji on a label (requires label_id, emoji) - move_source: Assign a source to a label (requires label_id, source_id) - delete: Delete label(s) permanently (requires label_id or label_ids, confirm=True) label_id: Label UUID (required for rename, set_emoji, move_source, delete) label_ids: List of label UUIDs for batch delete (alternative to label_id) name: Label display name (required for create and rename) emoji: Emoji character for set_emoji (e.g. "📊"), or "" to clear source_id: Source UUID to assign (required for move_source) unlabeled_only: For reorganize: if True, only label sources not yet in any label. If False (default), replaces ALL existing labels from scratch (requires confirm=True). confirm: Must be True for delete action and for reorganize with unlabeled_only=False

Returns: Action-specific response with status

Example: label(notebook_id="abc", action="auto") label(notebook_id="abc", action="list") label(notebook_id="abc", action="reorganize", confirm=True) label(notebook_id="abc", action="reorganize", unlabeled_only=True) label(notebook_id="abc", action="create", name="Research", emoji="📚") label(notebook_id="abc", action="rename", label_id="xyz", name="Better Name") label(notebook_id="abc", action="set_emoji", label_id="xyz", emoji="🎯") label(notebook_id="abc", action="move_source", label_id="xyz", source_id="src-id") label(notebook_id="abc", action="delete", label_id="xyz", confirm=True)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
notebook_idYes
actionYes
label_idNo
label_idsNo
nameNo
emojiNo
source_idNo
unlabeled_onlyNo
confirmNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior5/5

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

With no annotations, the description fully bears the transparency burden. It details actions like auto, list, reorganize (including force re-categorization and unlabeled_only), create, rename, set_emoji, move_source, and delete (permanent, requires confirm). It also notes that sources can belong to multiple labels and that reorganize replaces all labels unless unlabeled_only=True.

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

Conciseness4/5

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

The description is well-structured with introductory text, a list of supported actions, a bulleted parameter breakdown, a returns line, and examples. It front-loads purpose and is efficient, though the examples add length. Still, every sentence adds value.

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?

Given the tool's complexity (9 parameters, multiple actions) and lack of annotations, the description is remarkably complete. It covers all actions, parameter dependencies, confirmation requirements, and provides examples. Output schema exists, so return values need not be explained.

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

Parameters5/5

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

Schema has 0% description coverage, so the description must compensate. It provides extensive parameter descriptions in the Arg section, explaining each parameter's purpose, when it's required, and default behaviors. Examples further clarify usage, making the parameter semantics very clear.

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?

Description clearly states 'Manage source labels in a notebook. Unified tool for all label operations.' It provides a specific verb (manage) and resource (source labels), and positions itself as the single tool for label tasks, distinguishing from sibling 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 explicitly states it is the unified tool for all label operations, implying when to use it. It mentions a prerequisite (5+ sources for auto-labeling) and explains each action's context, but does not explicitly state when not to use it or compare to alternatives.

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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