Entities most similar to a given one — the nearest corpus dossier cards ('more like this') for peer discovery. Pass an entity id from search_entities / semantic_search. COVERAGE IS PARTIAL — only entities in the embedded risk-scored subset (~1.9% of the corpus and growing) return peers; an entity outside it returns empty for now, not an error.
| Name | Required | Description | Default |
|---|---|---|---|
| k | No | ||
| entity_id | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already cover readOnly/idempotent/non-destructive, so the description's added value is the partial-coverage caveat and the empty-not-error behavior. These are important behavioral details beyond the structured annotations, though no additional details like response format are provided.
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 compact and front-loaded with purpose, then adds a key edge case warning. Every part earns its place; no filler or redundancy.
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?
For a simple 2-parameter tool with no output schema, the description covers purpose, input source, coverage limitations, and empty-result behavior. It stops short of fully specifying the return shape and the exact effect of k on results.
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 has 0% description coverage, so the description must compensate. It explains entity_id well by saying to use an id from search_entities or semantic_search, but it does not explain what k controls, leaving an otherwise meaningful 'top-k' parameter ambiguous.
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 states the tool finds entities most similar to a given one, explicitly calling it 'more like this' for peer discovery. It also distinguishes itself by requiring an entity id rather than a query, which separates it from search tools.
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 gives concrete usage context: pass an entity id from search_entities or semantic_search, and it explicitly warns that entities outside the embedded subset return empty. It does not explicitly name alternatives or when-not-to-use, but the context is strong enough to guide selection.
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 have distinct purposes (search, lookup, get details, graph traversal, coverage maps, payment). Some overlap exists between lookup_company and lookup_by_identifier (both resolve identifiers, though one is UK-specific), and between get_entity vs get_company_details, but descriptions clarify distinctions. find_similar and semantic_search both find similar entities but different mechanisms.
Uses a mix of verb_noun and noun_phrases: buy_dossier, claim_dossier, check_offshore_exposure, find_similar, get_pricing, get_pulse, graph_neighbourhood, list_asset_coverage, lookup_by_identifier, search_entities, trace_ownership_path. While most use underscores and verbs like get/lookup/search/list, there are inconsistencies like 'graph_neighbourhood' (noun start) vs 'trace_ownership_path' (verb start). Overall readable but not perfectly consistent.
23 tools is at the high end but justifiable for a comprehensive intelligence server covering search, lookup, graph, coverage, payments, and entity details. 'buy_dossier' is considered one of the tools and adds bulk but not excessive. It is appropriate for the scope.
Covers a wide range: search (search_entities, search_companies, semantic_search), identifier lookup (lookup_by_identifier, lookup_company), entity details (get_entity, get_company_details, get_financials), graph (graph_neighbourhood, graph_path, trace_ownership_path), coverage maps (list_jurisdictions, list_asset_coverage), sanctions (get_sanctions, check_offshore_exposure), plus payment flow (get_pricing, buy_dossier, claim_dossier, get_payment_link). Missing perhaps a 'get_relationships' separate tool but get_entity includes direct relationships. Also no explicit 'list_entities' but search covers it. Minor gaps like no bulk operations besides resolve.
