get_full_dossierAggregator — 90+ fields about an entity in one call. Combines 4 ENTIA sources in parallel: identity, zone, BORME, VIES. Killer tool for due diligence/KYB.
| Name | Required | Description | Default |
|---|---|---|---|
| query | Yes | Company name, CIF/NIF, EU VAT, or LEI |
| Name | Required | Description | Default |
|---|---|---|---|
| _meta | No | ||
| found | No | ||
| query | No | ||
| entity | No | ||
| integrity | No | ||
| provenance | No | ||
| trust_score | No | ||
| verification | No | ||
| data_coverage | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and non-destructive behavior. The description adds useful behavioral context beyond annotations: it is an 'Aggregator' that combines four sources 'in parallel' and returns a large field set, which informs expectations about scope and data provenance.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is exceptionally compact: scope ('90+ fields in one call'), mechanics ('4 ENTIA sources in parallel'), and use case ('due diligence/KYB') each get a short, meaningful clause. There is no wasted text, and the key aggregation fact is front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With a read-only, idempotent annotation profile, a single well-documented parameter, and an output schema present, the description does not need to explain return values. It provides the essential behavioral identity, source composition, and intended use, leaving no significant gap for an agent deciding to invoke it.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%: the single 'query' parameter already documents accepted formats ('Company name, CIF/NIF, EU VAT, or LEI'). The description adds no additional parameter-level meaning beyond referring to the target as an entity, so the baseline of 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly identifies the tool as an aggregator returning '90+ fields about an entity in one call' and names the four combined sources. It conveys a broad entity dossier concept but does not explicitly contrast it with sibling lookup tools like entity_lookup or search_entities.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
It states a target use case ('Killer tool for due diligence/KYB'), indicating when an agent would want comprehensive entity intelligence. However, it does not provide explicit when-to-use vs alternatives guidance or exclusions, leaving selection partially to inference.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Most tools target distinct resources, but get_entia_home and get_entity_home_projection are near-duplicates representing the same Entia Home concept from slightly different technical angles. entity_lookup and get_full_dossier also overlap since entity_lookup already mentions returning the full paid dossier, and get_competitors is a specialized variant of search_entities.
The set mixes get_* names with bare action names like entity_lookup, search_entities, verify_vat, and professional_lookup, so there is no single consistent verb_noun pattern. The names are still readable and somewhat predictable, but the inconsistency is noticeable and get_entia_home vs get_entity_home_projection adds confusion.
Twelve tools is within a reasonable range for an entity-verification server, and most tools serve a distinct due-diligence purpose. However, a few tools are auxiliary or redundant: get_showcase and get_platform_stats are exploratory rather than core verification, and the two Entia Home retrieval tools could be consolidated.
The server covers the core verification lifecycle well: entity lookup by identifiers, flexible search, VAT validation, professional verification, competitor discovery, full dossiers, and risk auditing. Minor gaps exist, such as no direct way to fetch a raw single source like VIES or BORME independently and no entity relationship/ownership endpoint, but these are workable for typical KYB workflows.