{"passport":{"unfragile":{"@version":"1.0","version":"2026-05","artifact":{"id":"tool_worgit-ai","slug":"worgit-ai","name":"Worgit.ai","type":"product","url":"https://worgit.ai","page_url":"https://unfragile.ai/worgit-ai","categories":["automation"],"tags":[],"pricing":{"model":"freemium","free":true,"starting_price":null},"status":"active","verified":false},"capabilities":[{"id":"tool_worgit-ai__cap_0","uri":"capability://text.generation.language.ai.driven.email.and.outreach.content.generation","name":"ai-driven email and outreach content generation","description":"Generates personalized marketing emails, sales outreach sequences, and HR communication templates using prompt-based LLM orchestration. The system likely maintains context about recipient profiles (from CRM data or manual input) and applies tone/style templates to produce on-brand messaging. Outputs are editable drafts that preserve user control over final messaging before sending.","intents":["Generate personalized cold outreach emails at scale without manual copywriting","Draft professional HR communications (offer letters, rejection emails) with consistent tone","Create marketing campaign email sequences with dynamic personalization tokens","Quickly iterate on email copy variations to test messaging effectiveness"],"best_for":["Sales teams conducting outreach campaigns with 50-500 prospects","Marketing teams managing multi-touch email sequences","HR teams handling high-volume candidate communications"],"limitations":["No A/B testing framework built-in — requires manual variant creation and external analytics","Personalization limited to fields available in contact records — cannot infer deep behavioral context","No native email deliverability optimization (DKIM, SPF, bounce handling) — relies on third-party SMTP","Generated content may require significant editing for brand voice consistency across teams"],"requires":["Contact/candidate data with at least name and email fields","API connection to email service provider (Gmail, Outlook, or SMTP server)","Active Worgit.ai account with email generation module enabled"],"input_types":["structured contact data (CSV, CRM export, manual entry)","campaign brief or email template instructions","recipient profile fields (company, role, industry)"],"output_types":["plain text email drafts","HTML email templates with inline styling","email sequences (multi-step workflows)"],"categories":["text-generation-language","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_worgit-ai__cap_1","uri":"capability://text.generation.language.job.description.and.recruitment.content.generation","name":"job description and recruitment content generation","description":"Generates job descriptions, candidate screening criteria, and recruitment messaging from high-level role requirements using templated LLM prompts. The system accepts job title, department, and key responsibilities as input and produces structured job postings with sections for qualifications, compensation guidance, and company culture messaging. Likely includes pre-built templates for common roles (engineer, sales, HR) to accelerate generation.","intents":["Create job descriptions quickly without HR writing expertise","Generate consistent job posting format across multiple open roles","Draft candidate screening questions aligned to job requirements","Produce recruitment email templates to attract passive candidates"],"best_for":["Mid-market companies with 50-500 employees hiring across multiple departments","Startups scaling hiring without dedicated HR content writers","Recruiting teams managing 10+ concurrent open positions"],"limitations":["Generated descriptions may lack company-specific culture voice — requires manual editing","No integration with ATS (Applicant Tracking System) to auto-post to job boards","Cannot automatically adjust compensation ranges based on market data or location","Screening criteria generated may not account for internal skill gaps or team dynamics"],"requires":["Job title, department, and key responsibilities as input","Active Worgit.ai account with HR/recruitment module","Optional: company culture guidelines or previous job posting examples for style matching"],"input_types":["text description of role and responsibilities","department and seniority level","optional: company culture/brand guidelines"],"output_types":["formatted job description (plain text or HTML)","screening question lists","candidate persona summaries","recruitment email templates"],"categories":["text-generation-language","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_worgit-ai__cap_2","uri":"capability://data.processing.analysis.lead.qualification.and.scoring.via.ai.analysis","name":"lead qualification and scoring via ai analysis","description":"Analyzes incoming leads against predefined qualification criteria using LLM-based classification. The system accepts lead data (company size, industry, engagement signals) and applies rule-based or LLM-driven scoring to rank leads by sales-readiness. Likely integrates with CRM data to enrich lead profiles and surface high-priority prospects for sales follow-up. Outputs include qualification scores and recommended next actions.","intents":["Automatically prioritize leads for sales team follow-up based on fit and engagement","Reduce time spent on manual lead qualification by 50%+","Identify leads that don't meet ICP (Ideal Customer Profile) to avoid wasted outreach","Route leads to appropriate sales rep based on territory or specialization"],"best_for":["Sales teams managing 100+ inbound leads per month","B2B companies with defined ICPs and sales cycles","Organizations seeking to improve sales efficiency without hiring additional SDRs"],"limitations":["Qualification logic limited to structured data fields — cannot analyze unstructured email or call notes without manual input","No real-time lead scoring updates — requires batch processing or manual refresh","Cannot predict churn or expansion opportunities within existing customers","Scoring criteria must be manually configured — no automatic learning from past conversions"],"requires":["Lead data with at least company name, industry, and company size","Predefined ICP or qualification criteria (e.g., 'companies with 50-500 employees in SaaS')","CRM integration or CSV import to populate lead database","Active Worgit.ai account with sales module"],"input_types":["structured lead data (company, industry, size, engagement signals)","ICP definition or qualification rules","optional: historical conversion data for model training"],"output_types":["lead qualification scores (numeric or categorical)","recommended actions (e.g., 'contact immediately', 'nurture', 'disqualify')","lead routing assignments","qualification reasoning (why a lead scored high/low)"],"categories":["data-processing-analysis","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_worgit-ai__cap_3","uri":"capability://text.generation.language.marketing.campaign.content.and.copy.generation","name":"marketing campaign content and copy generation","description":"Generates marketing copy, social media posts, ad headlines, and campaign messaging using prompt-based LLM generation with brand guidelines as context. The system accepts campaign brief, target audience, and marketing channel (email, social, ads) as input and produces multiple copy variations optimized for each channel. Likely includes templates for common campaign types (product launch, webinar promotion, seasonal offers) to accelerate generation.","intents":["Create social media post variations for multi-channel campaigns without hiring copywriters","Generate ad copy and headlines for Google Ads or LinkedIn campaigns","Draft landing page copy and CTAs aligned to campaign objectives","Produce marketing email subject lines and body copy variations for testing"],"best_for":["Marketing teams with 1-3 people managing multiple campaigns","Startups and SMBs without dedicated copywriting resources","Teams seeking to reduce time-to-launch for marketing campaigns"],"limitations":["Generated copy may lack brand voice consistency — requires manual review and editing","No built-in A/B testing framework — requires manual setup in ad platforms or email tools","Cannot optimize copy based on historical campaign performance data","Limited understanding of audience psychology or market positioning — produces generic messaging"],"requires":["Campaign brief with key message, target audience, and channel","Brand guidelines or tone/style examples for consistency","Active Worgit.ai account with marketing module","Optional: product/service description for context"],"input_types":["campaign brief (objective, target audience, key message)","marketing channel (email, social, ads, landing page)","brand guidelines or tone preferences","optional: competitor messaging or product details"],"output_types":["social media post copy (multiple variations)","ad headlines and body copy","email subject lines and preview text","landing page headlines and CTAs","campaign messaging frameworks"],"categories":["text-generation-language","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_worgit-ai__cap_4","uri":"capability://data.processing.analysis.candidate.screening.and.interview.preparation","name":"candidate screening and interview preparation","description":"Analyzes candidate resumes and applications against job requirements using LLM-based text analysis to extract qualifications, experience, and fit signals. The system produces screening summaries, interview question recommendations, and fit assessments. Likely uses prompt-based extraction to identify key skills, years of experience, and relevant projects from unstructured resume text, then compares against job description requirements.","intents":["Screen 50+ resumes in minutes instead of hours of manual review","Identify top candidates based on job fit without reading full resumes","Generate interview questions tailored to candidate background and role requirements","Flag red flags or gaps in candidate qualifications automatically"],"best_for":["Recruiting teams managing high-volume hiring (50+ applications per role)","Companies without dedicated recruiters or screening resources","Organizations seeking to reduce time-to-hire and improve candidate experience"],"limitations":["Resume parsing limited to text-based PDFs and documents — may fail on non-standard formats","Cannot assess soft skills, cultural fit, or communication ability from resume alone","No integration with video interview platforms — requires manual candidate outreach","Screening logic may have bias if trained on historical hiring data with demographic skew","Cannot verify credentials or employment history — requires manual background check"],"requires":["Job description with required and preferred qualifications","Candidate resumes in PDF, DOCX, or plain text format","Active Worgit.ai account with HR/recruitment module","Optional: company hiring guidelines or candidate persona for fit assessment"],"input_types":["candidate resume (PDF, DOCX, or text)","job description with requirements","optional: interview guidelines or assessment criteria"],"output_types":["candidate screening summary (qualifications, experience, fit score)","interview question recommendations","red flag alerts (missing qualifications, employment gaps)","candidate ranking or comparison matrix","interview preparation notes"],"categories":["data-processing-analysis","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_worgit-ai__cap_5","uri":"capability://automation.workflow.cross.functional.workflow.automation.and.task.orchestration","name":"cross-functional workflow automation and task orchestration","description":"Orchestrates multi-step workflows across marketing, sales, and HR modules using trigger-action rules and conditional logic. The system accepts workflow definitions (e.g., 'when lead scores above 80, send email and assign to sales rep') and executes them automatically based on data changes or scheduled intervals. Likely uses a state machine or workflow engine to manage dependencies and error handling across module boundaries.","intents":["Automate lead routing from marketing to sales when qualification criteria are met","Trigger candidate screening and interview scheduling when applications arrive","Execute multi-step campaigns (email → SMS → follow-up) without manual intervention","Sync data across marketing, sales, and HR systems to eliminate manual data entry"],"best_for":["Teams managing cross-functional processes (marketing → sales → customer success)","Organizations seeking to reduce manual handoffs and improve process efficiency","Companies with 20-200 employees where workflow automation has high ROI"],"limitations":["Workflow builder likely limited to simple if-then logic — cannot handle complex branching or loops","No native integration with external tools (Slack, Zapier, webhooks) — limited to Worgit modules","Workflow execution may have latency (minutes to hours) — not suitable for real-time use cases","No audit trail or workflow versioning — difficult to debug or rollback changes","Error handling and retry logic may be basic — requires manual intervention for failures"],"requires":["Defined workflow logic (triggers, conditions, actions)","Data sources configured in Worgit (CRM, email, HR module)","Active Worgit.ai account with workflow automation enabled","Optional: API keys for third-party integrations (if supported)"],"input_types":["workflow definition (trigger, conditions, actions)","data from Worgit modules (leads, candidates, campaigns)","optional: external data via API or webhook"],"output_types":["automated actions (emails sent, tasks created, data synced)","workflow execution logs and status","notifications to users or external systems"],"categories":["automation-workflow","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_worgit-ai__cap_6","uri":"capability://data.processing.analysis.crm.data.enrichment.and.contact.intelligence","name":"crm data enrichment and contact intelligence","description":"Enriches contact and company records with additional data fields (company size, industry, revenue, decision-maker titles) using LLM-based inference or third-party data lookups. The system accepts partial contact information and fills in missing fields to create more complete prospect profiles. Likely uses prompt-based extraction from web data or integrates with data enrichment APIs to populate fields.","intents":["Automatically populate missing company and contact information in CRM","Identify decision-makers and key contacts at target accounts","Enrich leads with industry, company size, and revenue data for better targeting","Create complete prospect profiles without manual research"],"best_for":["Sales teams managing large prospect lists with incomplete data","Organizations seeking to improve lead quality without manual research","B2B companies targeting specific company profiles or decision-maker titles"],"limitations":["Data enrichment accuracy depends on third-party data sources — may contain outdated or incorrect information","Cannot identify decision-makers at smaller companies or private organizations with limited online presence","Enrichment may violate data privacy regulations (GDPR, CCPA) if not properly configured","No real-time updates — enriched data may become stale over time","Limited to fields supported by data providers — cannot infer custom attributes"],"requires":["Contact information (name, email, company) or company name alone","Active Worgit.ai account with CRM or sales module","Optional: API keys for third-party data enrichment services (if used)"],"input_types":["partial contact data (name, email, company, or company name alone)","optional: industry or company size filters"],"output_types":["enriched contact records (company size, industry, revenue, titles)","decision-maker identification","company profile summaries","data quality scores or confidence levels"],"categories":["data-processing-analysis","memory-knowledge"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_worgit-ai__cap_7","uri":"capability://data.processing.analysis.performance.analytics.and.reporting.across.modules","name":"performance analytics and reporting across modules","description":"Aggregates metrics and KPIs across marketing, sales, and HR modules to provide cross-functional visibility into business performance. The system tracks campaign performance (open rates, click-through rates), sales metrics (pipeline value, conversion rates), and HR metrics (time-to-hire, candidate quality). Likely uses a data warehouse or analytics layer to consolidate data from multiple modules and generate dashboards and reports.","intents":["Track marketing campaign performance (opens, clicks, conversions) in a single dashboard","Monitor sales pipeline health and conversion rates by stage","Measure recruitment efficiency (time-to-hire, cost-per-hire, quality metrics)","Generate executive reports showing cross-functional business metrics"],"best_for":["Leadership teams seeking unified visibility into marketing, sales, and HR performance","Mid-market companies managing multiple departments without integrated analytics","Organizations seeking to identify bottlenecks and optimize cross-functional processes"],"limitations":["Analytics limited to data within Worgit modules — cannot incorporate external data sources","No custom metric or KPI definition — limited to pre-built metrics","Reporting may have latency (hours to days) — not suitable for real-time dashboards","No predictive analytics or forecasting — limited to historical reporting","Export options may be limited (PDF, CSV) — no native BI tool integration"],"requires":["Active Worgit.ai account with analytics module enabled","Data from at least one Worgit module (marketing, sales, or HR)","Optional: historical data for trend analysis"],"input_types":["data from Worgit modules (campaigns, leads, candidates, conversions)"],"output_types":["dashboards with KPI cards and charts","performance reports (PDF, CSV, email)","trend analysis and comparisons","alerts for anomalies or missed targets"],"categories":["data-processing-analysis","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_worgit-ai__cap_8","uri":"capability://automation.workflow.template.library.and.workflow.reuse.across.teams","name":"template library and workflow reuse across teams","description":"Maintains a library of pre-built templates for common business processes (email sequences, job descriptions, campaign briefs, interview questions) that teams can customize and reuse. The system stores templates with variable placeholders (e.g., {{company_name}}, {{recipient_email}}) and allows users to apply templates to new use cases with minimal customization. Likely includes version control and approval workflows to ensure template consistency.","intents":["Reuse proven email sequences and campaign templates across multiple campaigns","Standardize job descriptions and recruitment messaging across departments","Ensure brand consistency in marketing copy and HR communications","Reduce time-to-launch by starting with pre-built templates instead of blank slate"],"best_for":["Teams with repeatable processes (email campaigns, job postings, outreach sequences)","Organizations seeking to enforce brand and messaging consistency","Companies with multiple team members who need to follow standardized workflows"],"limitations":["Template library limited to pre-built templates — no community or third-party template marketplace","No template versioning or rollback — difficult to manage template changes across teams","Template customization limited to variable substitution — cannot modify template structure","No approval workflow for template changes — risk of inconsistent messaging","Templates may become outdated without regular maintenance"],"requires":["Active Worgit.ai account with template library access","Optional: brand guidelines or messaging framework for template creation"],"input_types":["template selection from library","variable values (company name, recipient email, etc.)","optional: custom template creation"],"output_types":["customized documents or messages ready for use","template usage analytics (which templates are most used)"],"categories":["automation-workflow","memory-knowledge"],"confidence":0.5,"matches":0,"success_rate":0}],"trust":{"score":40,"verified":false,"data_access_risk":"high","permissions":["Contact/candidate data with at least name and email fields","API connection to email service provider (Gmail, Outlook, or SMTP server)","Active Worgit.ai account with email generation module enabled","Job title, department, and key responsibilities as input","Active Worgit.ai account with HR/recruitment module","Optional: company culture guidelines or previous job posting examples for style matching","Lead data with at least company name, industry, and company size","Predefined ICP or qualification criteria (e.g., 'companies with 50-500 employees in SaaS')","CRM integration or CSV import to populate lead database","Active Worgit.ai account with sales module"],"failure_modes":["No A/B testing framework built-in — requires manual variant creation and external analytics","Personalization limited to fields available in contact records — cannot infer deep behavioral context","No native email deliverability optimization (DKIM, SPF, bounce handling) — relies on third-party SMTP","Generated content may require significant editing for brand voice consistency across teams","Generated descriptions may lack company-specific culture voice — requires manual editing","No integration with ATS (Applicant Tracking System) to auto-post to job boards","Cannot automatically adjust compensation ranges based on market data or location","Screening criteria generated may not account for internal skill gaps or team dynamics","Qualification logic limited to structured data fields — cannot analyze unstructured email or call notes without manual input","No real-time lead scoring updates — requires batch processing or manual refresh","builder identity is not verified yet","no observed match outcomes yet"],"rank_breakdown":{"adoption":0.31666666666666665,"quality":0.67,"ecosystem":0.25,"match_graph":0.25,"freshness":0.75,"weights":{"adoption":0.25,"quality":0.25,"ecosystem":0.1,"match_graph":0.35,"freshness":0.05}},"observed_outcomes":{"matches":0,"success_rate":0,"avg_confidence":0,"top_intents":[],"last_matched_at":null},"maintenance":{"status":"active","updated_at":"2026-05-24T12:16:34.117Z","last_scraped_at":"2026-04-05T13:23:42.553Z","last_commit":null},"community":{"stars":null,"forks":null,"weekly_downloads":null,"model_downloads":null,"model_likes":null}},"distribution":{"claim_url":"https://unfragile.ai/submit?claim=worgit-ai","compare_url":"https://unfragile.ai/compare?artifact=worgit-ai"}},"signature":"cTM+ECw0rYSsHS/xIlkadl4U/6aHKj8H08BfuxzyKjsDMpU/93a4hJmdK9sU5nnpRUjfIqdN5EbIzMZC8fBjAQ==","signedAt":"2026-06-20T18:47:49.452Z","signedBy":"unfragile.ai","version":1},"_links":{"self":"https://unfragile.ai/api/v1/passport/worgit-ai","artifact":"https://unfragile.ai/worgit-ai","verify":"https://unfragile.ai/api/v1/verify?slug=worgit-ai","publicKey":"https://unfragile.ai/api/v1/trust-passport-public-key","spec":"https://unfragile.ai/trust","schema":"https://unfragile.ai/schema.json","docs":"https://unfragile.ai/docs"}}