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resolve_company

Resolve companies to canonical AnchorIDs using domain, name, city/state, or external identifiers. Returns resolution status, confidence scores, and ambiguous candidates for identity verification.

Instructions

Resolve a company to an AnchorID using domain, name, city/state, or external identifiers. Returns status (resolved | needs_review | not_found), confidence score, the canonical AnchorID, match reasons, and any ambiguous candidates.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
domainNoCompany domain (e.g. acme.com)
nameNoCompany name
cityNoCity for geo-matching
stateNoState for geo-matching
identifiersNoExternal system identifiers
min_confidenceNoMinimum confidence threshold (0-1)
Behavior4/5

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

With no annotations provided, the description carries the full burden of explaining behavior. It effectively discloses the ternary resolution states (resolved | needs_review | not_found), explains the confidence scoring mechanism, and warns about ambiguous candidates—critical context for an entity resolution tool. Does not mention rate limits or side effects, but covers the resolution logic thoroughly.

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?

Two sentences with zero waste: first covers inputs/purpose, second covers return values. Front-loaded with the core action and output type. Every clause provides distinct information (resolution method, return statuses, data elements) without redundancy.

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?

Despite lacking an output schema, the description comprehensively explains the return contract (status values, confidence score, AnchorID, match reasons, ambiguous candidates). For a 6-parameter entity resolution tool with nested objects, this covers the critical resolution outcomes. Minor gap: does not note that all parameters are optional (0 required), which is unusual and relevant for invocation strategy.

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?

Schema description coverage is 100%, establishing a baseline of 3. The description maps parameter groups conceptually ('city/state' as geo-matching, 'external identifiers' for the identifiers object) but adds no syntax details, validation rules, or usage examples beyond what the schema already provides.

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?

States the specific action (resolve), target resource (company), and output format (AnchorID) using clear verbs. The mention of 'AnchorID' distinguishes it from sibling get_entity (which likely retrieves by ID), while listing input methods (domain, name, city/state, external identifiers) clarifies the entity resolution pattern versus simple lookup.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Describes what inputs can be used but provides no explicit guidance on when to select this tool versus resolve_company_batch (batch alternative) or get_entity (direct retrieval by ID). No mention of prerequisites like minimum data requirements or when to prefer external identifiers over name/geo.

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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