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provider_country_risk

Enrich provider dependencies with OECD economic risk: GDP, unemployment, CLI per provider country. DORA Art. 28-31 relevant.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
entity_idNoEntity ID

Schema Changelog

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

  1. First observed

TDQS

A3.7/5.0
Behavior2/5

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

With no annotations provided, the description carries the full burden of disclosing behavior. 'Enrich' implies modification but does not state whether this is read-only, updates provider dependencies, or requires special permissions. It also leaves 'CLI' unexplained, and the absence of any note on side effects or output limits is a significant transparency gap.

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 two concise sentences. The first conveys the core functionality with specific data points, and the second adds relevant regulatory context. No wasteful filler.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a single-parameter tool with no output schema and no annotations, the description provides the key data points and regulatory relevance. However, it does not clarify whether the tool returns enriched data or updates records, nor does it describe the output format. This leaves reasonable questions unanswered, so it is adequate but not 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?

The schema provides 100% coverage with a minimal description for entity_id ('Entity ID'). The description adds context that the tool operates on provider dependencies, but it does not explicitly map entity_id to a provider dependency or explain how the parameter affects the enrichment. This is adequate but not rich.

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 the tool's action: 'Enrich provider dependencies with OECD economic risk' and specifies the data elements (GDP, unemployment, CLI) per provider country. This distinguishes it from sibling tools like dependency_graph or whatif_provider by focusing on economic risk enrichment.

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 DORA Art. 28-31 reference provides clear context for when this tool is relevant (compliance with EU digital operational resilience). However, it does not explicitly exclude or compare against alternatives, so it falls short of a 5.

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

B3.1/5.0
Disambiguation3/5

Several tools overlap in purpose, particularly contract analysis (check_contract, contract_analyze, llm_clause_check) which could confuse agents. Assessment-related tools (readiness_check, assess_all, article_status) also have partially overlapping functionality. However, most tools have distinct resources and actions with detailed descriptions.

Naming Consistency4/5

Tool names are consistently snake_case and mostly follow a verb_noun pattern (e.g., create_entity, generate_report, register_provider). Minor deviations like contract_analyze and llm_clause_check invert the verb-noun order, but the overall pattern is predictable.

Tool Count2/5

50 tools is a very large surface for a single server, exceeding the threshold for 'too many' tools. While the DORA domain is broad, this breadth makes it challenging for agents to navigate and select the right tool efficiently.

Completeness4/5

The tool set covers the full DORA compliance lifecycle: entity onboarding, contract analysis, provider management, assessments, evidence, reporting, and incident workflows. Simulation and cross-regulation tools add depth. Minor missing CRUD operations (e.g., update/delete entity) but agents can work around.

Resources