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Resolve Company Identity

resolve_company_identity
Idempotent

Resolve company names, domains, or LinkedIn URLs into one canonical identity with confidence scores, cross-checks, and conflict flags.

Instructions

Resolve any combination of company name, domain, or LinkedIn URL into one canonical company identity: the name, primary domain, and LinkedIn company URL, each with a 0-100 confidence score plus an overall score and a match method. Cross-checks the inputs you give it, resolves the ones you do not, and flags conflicts (a domain and a LinkedIn slug that disagree) instead of merging them. A LinkedIn URL the actor finds is returned only when verified against the company site or the name, with the reason in linkedin_verification. Provide at least one of company_name, domain, or linkedin_url. Use this to reconcile or deduplicate records you already hold; use resolve_linkedin_url instead when you only need the LinkedIn company URL for a domain or name. Reads public data and writes nothing; requires an APIFY_TOKEN and consumes Apify credits per call.

Input Schema

NameRequiredDescriptionDefault
domainNoBare company domain, e.g. stripe.com. The strongest canonical key when provided.
skipCacheNoForce a fresh resolution and ignore the 7 day result cache.
company_nameNoCompany name, e.g. Stripe. Provide at least one of company_name, domain, or linkedin_url.
linkedin_urlNoLinkedIn company URL (https://www.linkedin.com/company/stripe) or bare slug (stripe).
max_charge_usdNoOptional spending cap for this call, in USD, passed to the actor as max_charge_usd. The run stops before any charge that would take it past this amount and keeps every row already charged. Leave empty to rely only on the maximum charge per run set on your Apify account.
minLinkedinConfidenceNoA LinkedIn page the actor finds is returned only when its linkedin_confidence is at least this value, 0 to 100. Default "70". A LinkedIn URL you provide is always returned as given. Sent as a string for Clay compatibility.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv1.14.0
    • addedInput schema / properties / max_charge_usd
      Added value: +{
+  "description": "Optional spending cap for this call, in USD, passed to the actor as max_charge_usd. The run stops before any charge that would take it past this amount and keeps every row already charged. Leave empty to rely only on the maximum charge per run set on your Apify account.",
+  "minimum": 0,
+  "type": "number"
+}
  2. Changed1 schema field changedv1.1.1
    • addedInput schema / properties / minLinkedinConfidence
      Added value: +{
+  "description": "A LinkedIn page the actor finds is returned only when its linkedin_confidence is at least this value, 0 to 100. Default \"70\". A LinkedIn URL you provide is always returned as given. Sent as a string for Clay compatibility.",
+  "pattern": "^\\s*(100|[1-9]?[0-9])?\\s*$",
+  "type": "string"
+}
  3. Addedv1.1.0

TDQS

A4.8/5.0
Behavior5/5

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

Adds substantial context beyond the annotations: conflict detection instead of merging, LinkedIn URLs returned only when verified with the reason surfaced in linkedin_verification, live public-data reads with no data writes, an APIFY_TOKEN requirement, and per-call Apify credit consumption. The credit/actor-run side effect is exactly what reconciles the non-read-only annotation with the 'writes nothing' phrasing, so an agent is not misled.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Purpose is front-loaded and every sentence carries information (behavior, conflict policy, verification, alternative routing, auth, cost). It is one dense block rather than cleanly separated purpose/usage/behavior sections, which slightly hurts scanability for a description of this length.

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?

No output schema exists, and the description covers the return shape (name, primary domain, LinkedIn URL, per-field 0-100 confidence, overall score, match method, linkedin_verification). It also covers auth, cost, input preconditions, and the sibling alternative, so nothing an agent needs to call it correctly is missing.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so the baseline is 3, but the description adds real semantics the schema lacks: the three identity inputs are cross-checked against each other, unspecified ones are resolved, and disagreeing domain/LinkedIn inputs are flagged rather than merged. It also restates the at-least-one-input rule that the zero-required-parameter schema does not enforce via anyOf.

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 a precise verb + resource + outcome: resolve name/domain/LinkedIn URL into one canonical identity with per-field confidence scores, an overall score, and a match method. It explicitly differentiates itself from the sibling resolve_linkedin_url ('use resolve_linkedin_url instead when you only need the LinkedIn company URL'), so an agent can route without opening either schema.

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

Usage Guidelines5/5

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

Gives an explicit condition and alternative: 'Use this to reconcile or deduplicate records you already hold; use resolve_linkedin_url instead when you only need the LinkedIn company URL for a domain or name.' It also states the input precondition ('Provide at least one of company_name, domain, or linkedin_url'), leaving nothing to inference.

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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