apollo-salesforce-mapper
Server Details
Apollo->Salesforce Lead mapper. No LLM. Strict-fail required fields. PASS/REPAIR/FAIL verdict.
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP
- URL
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Tool Definition Quality
Score is being calculated. Check back soon.
Available Tools
1 toolapollo_to_salesforce_leadApollo → Salesforce Lead MapperAInspect
Maps an Apollo contact payload to a Salesforce Lead object. Accepts the full Apollo CSV export column set. Strict-fail if FirstName, LastName, or Phone cannot be resolved. All other Salesforce fields are populated when source data is present, silently omitted otherwise. Returns a Deterministic Receipt (task_id, verdict, confidence, diff[]) embedded in every non-FAIL response.
| Name | Required | Description | Default |
|---|---|---|---|
| zip | No | Alternate ZIP key → PostalCode. | |
| cell | No | Primary phone (legacy key). Accepts E.164, 10-digit US, formatted strings. | |
| city | No | City → City. | |
| No | Contact email → Email. | ||
| phone | No | Apollo 'Phone' column — alternate primary phone key. | |
| state | No | State / province → State. | |
| title | No | Job title → Title. | |
| source | No | Apollo 'Source' column → LeadSource. | |
| street | No | Street address → Street. | |
| company | No | Company name → Company. | |
| country | No | Country → Country. | |
| website | No | Company website → Website. | |
| headline | No | LinkedIn headline captured by Apollo → Description. | |
| industry | No | Industry → Industry. | |
| keywords | No | Apollo keywords/tags → Description. | |
| No | Alternate LinkedIn key → LinkedIn__c. | ||
| employees | No | Alternate employees key. | |
| full_name | No | Full name — must have ≥2 whitespace-separated tokens. Use this OR provide first_name + last_name. Example: 'Jane Doe' | |
| job_title | No | Apollo 'Job Title' column → Title. | |
| last_name | No | Last name (Apollo split export). Use with first_name instead of full_name. | |
| prop_addr | No | Full property address string (legacy v1 key) → PropertyAddress. | |
| seniority | No | Apollo seniority level → Description. | |
| first_name | No | First name (Apollo split export). Use with last_name instead of full_name. | |
| work_phone | No | Apollo 'Work Phone' column — lowest-priority fallback. | |
| departments | No | Apollo departments string → Description. | |
| lead_source | No | Lead source string → LeadSource (mapped to Salesforce picklist values). | |
| person_city | No | Apollo 'Person City' column → City. | |
| postal_code | No | ZIP / postal code → PostalCode. | |
| twitter_url | No | Twitter/X URL → Twitter__c. | |
| account_name | No | Apollo 'Account Name' column → Company. | |
| linkedin_url | No | LinkedIn profile URL → LinkedIn__c. | |
| mobile_phone | No | Apollo 'Mobile Phone' column. Maps to MobilePhone if a primary phone exists. | |
| organization | No | Apollo 'Organization' column → Company. | |
| person_state | No | Apollo 'Person State' column → State. | |
| num_employees | No | Alternate employees key. | |
| annual_revenue | No | Annual revenue string, e.g. '$1.2M', '500000' → AnnualRevenue (number). | |
| person_country | No | Apollo 'Person Country' → Country. | |
| company_website | No | Apollo 'Company Website' → Website. | |
| person_postal_code | No | Apollo 'Person Postal Code' → PostalCode. | |
| number_of_employees | No | Employee count or range (e.g. '500-1000') → NumberOfEmployees. | |
| estimated_annual_revenue | No | Apollo estimated revenue → AnnualRevenue. |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. Discloses critical behaviors: strict-fail validation, silent omission of optional fields, and return structure (Deterministic Receipt with task_id, verdict, confidence, diff[]). Minor gap: ambiguous whether this writes to Salesforce or purely returns mapped payload.
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?
Four sentences with zero waste: 1) purpose, 2) input scope, 3) validation behavior, 4) return format. Dense but scannable, front-loaded with the core mapping function.
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?
Excellent for 41-param transformation tool without output schema. Explains mapping coverage (full Apollo CSV set), validation strictness, failure modes, and return receipt structure. Would be 5 if it clarified sync vs. async behavior or side-effects on Salesforce.
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 100% description coverage (baseline 3). Description adds crucial semantic context: 'Accepts the full Apollo CSV export column set' explains param origin, and 'Strict-fail if FirstName, LastName, or Phone cannot be resolved' clarifies effective required fields that schema doesn't enforce (schema shows 0 required).
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?
Excellent specificity: 'Maps an Apollo contact payload to a Salesforce Lead object' provides exact verb (Maps), source system (Apollo), and target (Salesforce Lead). The title reinforces this transformation purpose.
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?
Clear validation rules stated: 'Strict-fail if FirstName, LastName, or Phone cannot be resolved' and 'silently omitted otherwise' explains error vs. success behaviors. Lacks explicit 'use when' workflow guidance, but validation logic effectively constrains usage context.
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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