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bruhsb
by bruhsb

paperclip_create_label

Create a namespaced label (e.g., 'source:agent') with an optional hex color. Solves missing taxonomy labels for issue management.

Instructions

Create a new label for the current company.

Args:

  • name: string — Label name, typically namespaced (example: "source:agent")

  • color: string (optional) — 6-digit hex color (example: "#6366f1")

Returns: Returns the created label object: id, name, color, createdAt.

Examples:

  • Use when: seeding a missing taxonomy label (e.g. source:agent, type:bug) during Label Bootstrap

  • Don't use when: the label already exists — use paperclip_list_labels to check before creating

Error Handling:

  • 400: validation failure → check name is non-empty and color is valid hex if supplied

  • 401: authentication failed → check PAPERCLIP_API_KEY

  • 409: label name already exists → fetch existing ID from paperclip_list_labels

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYesLabel name (e.g. 'source:agent', 'type:bug')
colorNo6-digit hex color string (e.g. '#6366f1')
Behavior5/5

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

The description adds significant behavioral context beyond annotations: return shape (id, name, color, createdAt), error handling codes (400, 401, 409), and the suggestion to check for existing labels. Annotations only declare non-destructive and non-open-world, so description carries the burden and does so thoroughly.

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 well structured with clear sections (Args, Returns, Examples, Error Handling). It is concise, front-loaded with the main purpose, and every sentence adds value without redundancy.

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 no output schema, the description fully explains the return object, error scenarios, and usage context. It covers all essential information for an agent to correctly invoke the tool, making it highly complete.

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 baseline 3 is appropriate. The description repeats schema info for name and color, adding only minor nuance like 'typically namespaced' for name. No significant new meaning beyond what schema already provides.

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 'Create a new label for the current company' with a specific verb and resource. Among siblings, there is no other label creation tool, and paperclip_list_labels exists for listing, so it distinguishes well.

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?

Explicit guidance: 'Use when: seeding a missing taxonomy label... Don't use when: the label already exists — use paperclip_list_labels to check before creating.' Provides clear when-to-use and when-not-to-use with an alternative tool named.

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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