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create_dpp

Use this tool to issue the Digital Product Passport of a twin created with create_product_twin. Cycle validates conformance FIRST (ESPR mandatory field set) and REFUSES to create an incomplete passport - if fields are missing it returns exactly which ones. OUTPUT: the DPP dataset + its public URL. EU registry submission happens the moment the EU opens it for textile (Cycle is integrated and in approval as service provider). Requires an organisation API key.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
skuNo
product_idNo

TDQS

A4.1/5.0
Behavior5/5

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

The description goes far beyond the sparse annotations: it reveals that Cycle validates ESPR conformance first, refuses incomplete passports, returns the exact missing fields, outputs the DPP dataset plus public URL, queues EU registry submission, and requires an organisation API key. It also does not contradict the annotations.

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 dense but every sentence contributes operational value: purpose, validation behavior, output, registry side effect, and auth requirement. It is front-loaded and avoids redundant restatement of the tool name.

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?

It covers auth, validation, failure behavior, return output, and the registry side effect, which provides a strong overall picture. The missing piece is parameter semantics, which is a significant gap for a 2-parameter tool with no schema descriptions.

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

Parameters1/5

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

Schema description coverage is 0%, and the description never explains what sku or product_id mean, which is required, or how they identify the twin. An agent cannot reliably know whether to pass one, both, or what values they should come from.

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 a specific action - 'issue the Digital Product Passport of a twin' - and ties it to the precedent tool 'create_product_twin', which differentiates it from validation or requirement-checking siblings. The title 'Create a conformant DPP' reinforces the purpose.

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?

It explicitly positions this tool as the follow-up to create_product_twin and describes the conformance gate, giving clear context for when to use it. It does not explicitly name exclusionary conditions or alternatives like check_dpp_requirements or validate_dpp_readiness, but the predecessor relationship is a strong usage signal.

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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TDQS

A4.3/5.0
Disambiguation4/5

Each tool has a distinct role in a DPP/twin creation workflow, but create_product_twin and create_data_carrier both produce twin-resolving URLs and could be confused by an agent focused on QR generation. Similarly, check_dpp_requirements and validate_dpp_readiness are adjacent, though their descriptions clearly separate regulatory information from catalogue readiness.

Naming Consistency5/5

All tool names follow a consistent verb_noun snake_case pattern using check_, create_, or validate_. The naming makes the action and object clear across the entire set.

Tool Count5/5

Six tools cover the DPP lifecycle scope from requirements lookup through readiness validation, twin creation, DPP issuance, and data carrier generation. The set is well-scoped and each tool earns its place.

Completeness4/5

The core DPP/twin creation workflow is covered end-to-end, including pre-validation, GS1 identifier checks, twin creation, DPP issuance, and QR carrier generation. The set lacks read/update/delete operations for existing twins or DPPs, which is a minor but notable gap if lifecycle management is expected.

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