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label

Organize notebook sources into thematic labels. Auto-label sources, create, rename, or delete labels, assign sources, and set emojis.

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
nameNo
emojiNo
actionYes
confirmNo
label_idNo
label_idsNo
source_idNo
notebook_idYes
unlabeled_onlyNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior4/5

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

With no annotations provided, the description carries the full burden. It explains actions' behaviors, side effects (e.g., delete is permanent, reorganize replaces labels), and constraints (unlabeled_only). It does not cover rate limits or auth needs, but it provides sufficient operational transparency for the agent to avoid misuse.

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 an intro, action list, arg details, returns, and examples. It is slightly lengthy but every sentence adds value. Content is front-loaded with purpose. Minor efficiency improvements possible (e.g., tabular format for args), but solid overall.

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?

Given the tool's complexity (9 parameters, 8 actions) and that an output schema exists, the description is thorough. It covers all actions, parameter usage, and includes examples. It does not explicitly address error cases or edge conditions, but it is sufficient for an agent to use the tool correctly in most scenarios.

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 description coverage is 0%, so the description must compensate. It does so excellently by explaining each parameter's purpose, when it is required, and its expected format (e.g., emoji example, label_id vs label_ids). This adds critical context beyond the raw schema, fully enabling correct invocation.

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 it manages source labels in a notebook and lists all supported actions (auto, list, etc.), providing strong specificity. However, it does not explicitly distinguish from the sibling tool 'tag', which might perform similar metadata operations, so a slight deduction for missing differentiation.

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 detailed usage context for each action, including prerequisites (5+ sources for auto-labeling) and conditional requirements (confirm for delete/reorganize). It lacks explicit comparison to sibling tools or scenarios where this tool should not be used, but the provided guidance is clear and actionable.

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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