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check_dpp_requirements

Read-only

Use this tool when a company or user asks WHAT the EU Digital Product Passport (DPP) requires, WHEN it becomes mandatory, which ESPR/AGEC/French milestones apply to textile or fashion products, or whether the DPP is already obligatory. Returns the verified regulatory timeline (dates as of today), the mandatory data fields a textile DPP needs, and honest notes on what is in force vs pending delegated acts. Deterministic, no account needed. Informational, not legal advice.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
sectorNoOptional sector hint (textile, fashion, beauty, fmcg). Default textile.

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observed

TDQS

A4.5/5.0
Behavior5/5

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

Annotations already indicate readOnlyHint and openWorldHint, and the description goes further by stating the tool is deterministic, requires no account, is informational not legal advice, and clearly distinguishes in-force rules from pending delegated acts. This adds useful behavioral context about reliability and scope.

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 compact, well-organized, and front-loaded with the primary use case. Each sentence serves a purpose: when to use, what it returns, and behavioral caveats. No filler or redundant repetition of the tool name or annotations.

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?

For a tool with one optional parameter, no required fields, and read-only annotations, the description is complete. It explains the output substance (timeline, mandatory data fields, in-force vs pending notes), which is especially valuable given there is no output schema. It also covers the information-versus-legal-advice boundary.

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?

The schema already provides 100% coverage for the single optional `sector` parameter, including its default value. The description reinforces the relevance of textile/fashion products but does not add substantial new meaning beyond what the schema supplies. The baseline of 3 is appropriate.

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 uses specific verbs and resources: it answers WHAT the DPP requires, WHEN it becomes mandatory, and which milestones apply. It clearly positions itself as an informational tool returning verified regulatory timelines and mandatory data fields, which distinguishes it from sibling tools that create data carriers, DPPS, product twins, or validate readiness.

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 when to use the tool ('Use this tool when a company or user asks WHAT... WHEN...'). It gives clear context and examples, though it does not explicitly name alternative sibling tools or state when not to use it. The triggers are specific enough that an agent can route correctly.

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

A4.2/5.0
Disambiguation5/5

Each tool has a distinct purpose: regulatory info, readiness validation, twin creation, DPP issuance, data carrier generation, and identifier validation. No two tools overlap in function; create_product_twin and create_dpp are complementary steps in the same workflow.

Naming Consistency5/5

All tool names follow a consistent verb_noun pattern: check_, create_, validate_. The verbs are consistent and the nouns clearly indicate the target object or action, making the API predictable and easy to navigate.

Tool Count5/5

With 6 tools, the server is well-scoped for the DPP lifecycle: requirements, readiness, twin creation, DPP issuance, carrier generation, and identifier validation. Each tool is essential and the count is appropriate for the domain.

Completeness4/5

The core workflow of creating a compliant DPP is covered (validate readiness, create twin, create DPP, generate carrier). Missing update/delete operations are likely out of scope for this server, but the absence of a retrieval or listing tool is a minor gap that agents could work around via the returned URLs.

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