{"passport":{"unfragile":{"@version":"1.0","version":"2026-05","artifact":{"id":"tool_hirelakeai","slug":"hirelakeai","name":"HireLakeAI","type":"product","url":"https://hirelake.ai","page_url":"https://unfragile.ai/hirelakeai","categories":["automation"],"tags":[],"pricing":{"model":"free","free":true,"starting_price":null},"status":"active","verified":false},"capabilities":[{"id":"tool_hirelakeai__cap_0","uri":"capability://data.processing.analysis.resume.parsing.and.structured.data.extraction","name":"resume parsing and structured data extraction","description":"Automatically extracts and structures key information from unformatted resume documents (PDFs, Word docs, plain text) into standardized fields including contact details, work history, education, skills, and certifications. Uses document layout analysis combined with NLP entity recognition to identify sections and parse hierarchical information, handling variable resume formats without requiring manual template configuration.","intents":["I need to automatically extract candidate contact info, work experience, and skills from hundreds of resumes without manual data entry","I want to standardize resume data into a consistent format so I can programmatically compare candidates","I need to quickly identify key qualifications from resumes to pre-screen candidates at scale"],"best_for":["Recruiting agencies processing high-volume candidate pipelines","Small to mid-sized companies without existing ATS infrastructure","Independent recruiters managing multiple job openings simultaneously"],"limitations":["Parsing accuracy degrades with non-standard resume formats, handwritten sections, or image-heavy layouts","No built-in handling for non-English resumes or specialized domain terminology (medical, legal, technical certifications)","Extracted data quality depends on resume completeness — sparse or poorly formatted resumes may have missing or misclassified fields","No version control or audit trail for extracted data changes"],"requires":["Resume documents in PDF, DOCX, or plain text format","Minimum 50-100 character resume content for reliable parsing","Internet connection for cloud-based parsing service"],"input_types":["PDF documents","DOCX (Microsoft Word)","plain text","potentially image-based resumes"],"output_types":["structured JSON with standardized fields","CSV export for bulk candidate data","database records in candidate management system"],"categories":["data-processing-analysis","document-processing"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_hirelakeai__cap_1","uri":"capability://search.retrieval.semantic.candidate.to.job.matching","name":"semantic candidate-to-job matching","description":"Compares candidate profiles against job requirements using semantic similarity matching rather than keyword matching, leveraging embeddings-based search to identify candidates whose skills, experience, and background align with job descriptions even when terminology differs. Likely uses transformer models to encode both job descriptions and candidate data into vector space, then ranks candidates by cosine similarity to job requirements.","intents":["I want to find candidates whose experience matches a job opening even if they use different terminology than the job description","I need to rank candidates by relevance to a specific role without manually reviewing each resume","I want to identify candidates who are overqualified or underqualified for a position based on experience level"],"best_for":["Recruiting teams screening large candidate pools (100+ candidates per opening)","Companies with diverse candidate databases and multiple job openings","Recruiters seeking to reduce unconscious bias in initial candidate screening"],"limitations":["Semantic matching may miss hard requirements (e.g., specific certifications, security clearances) that require exact matching","Ranking quality depends on job description quality — vague or poorly written job specs produce unreliable matches","No built-in handling for role-specific context (e.g., startup vs enterprise experience, industry-specific knowledge)","Embeddings-based approach may conflate similar-sounding but distinct skills (e.g., 'project management' vs 'program management')"],"requires":["Structured candidate profiles with parsed skills and experience","Job description with clear requirements and preferred qualifications","Minimum 3-5 candidate profiles for meaningful ranking"],"input_types":["structured candidate data (skills, experience, education)","job description text","candidate profiles from resume parsing"],"output_types":["ranked candidate list with match scores","similarity scores per candidate","match breakdown by skill/experience category"],"categories":["search-retrieval","data-processing-analysis"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_hirelakeai__cap_2","uri":"capability://planning.reasoning.ai.powered.candidate.assessment.and.scoring","name":"ai-powered candidate assessment and scoring","description":"Automatically evaluates candidate qualifications against job requirements using LLM-based assessment, generating standardized scores and evaluation summaries. Likely prompts an LLM with candidate profile, job description, and evaluation criteria to produce structured assessment output including skill match scores, experience level assessment, and hiring recommendation rationale.","intents":["I want an objective, consistent scoring system to compare candidates across different job openings","I need to quickly identify top candidates without manually reviewing each resume and cover letter","I want to reduce hiring bias by using standardized AI assessment criteria instead of subjective human judgment"],"best_for":["Recruiting teams seeking consistent, repeatable candidate evaluation","Companies building data-driven hiring processes with benchmarkable metrics","Agencies managing multiple client job openings with varying requirements"],"limitations":["Assessment quality depends on LLM hallucination rates — may generate plausible but inaccurate evaluation rationales","No built-in validation that assessment criteria align with actual job success factors or legal hiring requirements","Scoring may reflect biases present in training data (e.g., overvaluing certain educational backgrounds or company names)","No explainability for individual score components — difficult to audit why a candidate received a specific score","Cannot assess soft skills, cultural fit, or interpersonal qualities that require human judgment"],"requires":["Structured candidate profile with parsed skills, experience, education","Job description with clear requirements and evaluation criteria","LLM API access (likely OpenAI, Anthropic, or similar)"],"input_types":["structured candidate data","job description","optional custom evaluation rubric"],"output_types":["numerical assessment scores (0-100 scale or similar)","evaluation summary text","skill-by-skill match breakdown","hiring recommendation (strong/moderate/weak candidate)"],"categories":["planning-reasoning","data-processing-analysis"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_hirelakeai__cap_3","uri":"capability://automation.workflow.batch.candidate.processing.and.pipeline.management","name":"batch candidate processing and pipeline management","description":"Processes multiple candidates through the full pipeline (parsing, matching, assessment) in batch mode, enabling bulk operations on candidate databases without per-candidate manual intervention. Likely implements job queue or async processing to handle large candidate volumes, with progress tracking and result aggregation across the pipeline stages.","intents":["I need to process 500+ resumes for a single job opening and get ranked candidate lists automatically","I want to re-evaluate my entire candidate database against new job openings without manual work","I need to generate assessment reports for multiple candidates to share with hiring managers"],"best_for":["Recruiting agencies with high-volume candidate pipelines","Companies conducting bulk hiring for multiple positions","Recruiters managing evergreen candidate databases"],"limitations":["Batch processing latency scales with candidate volume — processing 1000+ candidates may take minutes to hours","No real-time feedback during processing — results only available after batch completion","Batch operations cannot be paused or resumed mid-process in most implementations","Error handling for partial batch failures may result in incomplete candidate assessments","No built-in deduplication — duplicate resumes in batch may be processed separately"],"requires":["Candidate database with 10+ candidates minimum for meaningful batch processing","Job description or evaluation criteria for batch matching/assessment","Sufficient API quota for batch LLM calls (if assessment is included)"],"input_types":["bulk resume uploads (CSV, ZIP, or directory)","candidate database export","job description for matching/assessment"],"output_types":["ranked candidate list with scores","batch assessment report (CSV or JSON)","processing summary with success/failure counts"],"categories":["automation-workflow","data-processing-analysis"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_hirelakeai__cap_4","uri":"capability://memory.knowledge.candidate.database.storage.and.retrieval","name":"candidate database storage and retrieval","description":"Stores parsed candidate profiles and assessment results in a searchable database, enabling recruiters to query and retrieve candidates by skills, experience, location, or other attributes without re-parsing resumes. Likely implements indexed storage with full-text search and filtering capabilities to support rapid candidate lookups across large databases.","intents":["I want to search my candidate database for people with specific skills or experience for new job openings","I need to maintain a persistent database of candidates I've already parsed so I don't re-process resumes","I want to filter candidates by location, salary expectations, or availability status"],"best_for":["Recruiting agencies maintaining evergreen candidate pools","Companies with ongoing hiring needs across multiple positions","Recruiters seeking to reuse candidate data across multiple job openings"],"limitations":["No transparent information about data retention policies — unclear how long candidate data is stored","No documented GDPR/privacy compliance for storing sensitive candidate information","Search functionality likely limited to basic filters — no advanced query syntax or custom field support","No built-in candidate consent management or opt-out mechanisms","Database size limits unknown — unclear if free tier supports 10K+ candidate profiles"],"requires":["Candidate profiles with parsed data (skills, experience, contact info)","Account with HireLakeAI to access database","Internet connection for cloud-based database access"],"input_types":["parsed candidate profiles","search queries (skills, experience, location)","filter criteria"],"output_types":["candidate profile records","filtered candidate lists","candidate details with assessment history"],"categories":["memory-knowledge","data-processing-analysis"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_hirelakeai__cap_5","uri":"capability://data.processing.analysis.job.description.analysis.and.requirement.extraction","name":"job description analysis and requirement extraction","description":"Analyzes job descriptions to extract and structure key requirements, qualifications, and responsibilities using NLP techniques. Likely parses job description text to identify required skills, experience levels, education requirements, and nice-to-have qualifications, enabling standardized comparison against candidate profiles without manual requirement definition.","intents":["I want to automatically extract key requirements from a job description so I can match candidates without manual analysis","I need to identify required vs nice-to-have skills from a job posting to set matching thresholds","I want to standardize job requirements across multiple openings to enable consistent candidate evaluation"],"best_for":["Recruiting teams managing multiple job openings with varying requirement formats","Agencies seeking to standardize job requirement extraction across client postings","Companies building data-driven hiring processes with structured requirement tracking"],"limitations":["Extraction accuracy depends on job description clarity — poorly written or vague job specs produce unreliable requirement lists","No built-in handling for implicit requirements (e.g., 'startup experience' or 'fast-paced environment')","Cannot distinguish between hard requirements and aspirational qualifications without explicit job description structure","No validation that extracted requirements are actually predictive of job success","May miss domain-specific requirements or certifications that use non-standard terminology"],"requires":["Job description text (plain text, HTML, or PDF)","Minimum 200-300 character job description for reliable extraction"],"input_types":["job description text","job posting HTML","job description documents"],"output_types":["structured requirement list (skills, experience, education)","required vs optional qualification breakdown","experience level assessment","JSON-formatted job requirements"],"categories":["data-processing-analysis","text-generation-language"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_hirelakeai__cap_6","uri":"capability://planning.reasoning.candidate.ranking.and.recommendation.generation","name":"candidate ranking and recommendation generation","description":"Generates ranked candidate lists with hiring recommendations based on combined matching scores and assessment results. Integrates parsing, semantic matching, and AI assessment outputs into a unified ranking algorithm that produces prioritized candidate lists with explanations for hiring managers. Likely weights multiple signals (skill match, experience level, assessment score) to produce final ranking.","intents":["I want a prioritized list of top candidates for a job opening ranked by overall fit","I need to present hiring managers with candidate recommendations and explanations for why each candidate is suitable","I want to identify candidates who are strong matches but might be overlooked in manual screening"],"best_for":["Hiring managers seeking data-driven candidate recommendations","Recruiting teams presenting candidate shortlists to stakeholders","Companies seeking to standardize candidate ranking across multiple openings"],"limitations":["Ranking algorithm weights are likely opaque — unclear how different factors (skill match, experience, assessment score) are weighted","No built-in handling for hard constraints (e.g., must have security clearance, must be local) that should disqualify candidates","Recommendations may reflect biases in training data or assessment criteria","No A/B testing or feedback loop to validate that ranked candidates actually perform better in hiring outcomes","Ranking cannot account for unmeasurable factors like cultural fit or team dynamics"],"requires":["Parsed candidate profiles with skills and experience","Job description with requirements","Assessment scores for candidates (if assessment is enabled)"],"input_types":["candidate profiles","matching scores","assessment results","job description"],"output_types":["ranked candidate list with scores","recommendation summary per candidate","ranking explanation (why candidate ranked #1, #2, etc.)","candidate comparison matrix"],"categories":["planning-reasoning","data-processing-analysis"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_hirelakeai__cap_7","uri":"capability://automation.workflow.candidate.communication.and.status.tracking","name":"candidate communication and status tracking","description":"Tracks candidate status through the hiring pipeline (screened, interviewed, rejected, offered) and potentially enables communication with candidates through the platform. Likely maintains candidate state and interaction history, enabling recruiters to track where each candidate is in the hiring process and manage follow-up communications.","intents":["I want to track which candidates I've screened, interviewed, or rejected for a job opening","I need to manage candidate communications and follow-ups without switching between multiple tools","I want to maintain a history of candidate interactions and decisions for compliance and reference"],"best_for":["Recruiting teams managing multiple candidates across different hiring stages","Agencies coordinating with multiple hiring managers on candidate progress","Companies seeking to consolidate candidate management in a single platform"],"limitations":["No documented email integration or communication templates","Unclear if platform supports automated candidate notifications or status updates","No built-in interview scheduling or calendar integration","Limited visibility into whether communication features are available on free tier","No documented GDPR compliance for candidate communication records"],"requires":["Candidate profiles in HireLakeAI database","Job opening with associated candidates","Recruiter account with access to candidate management features"],"input_types":["candidate status updates","communication messages","interview feedback"],"output_types":["candidate status history","pipeline stage tracking","candidate interaction log","communication records"],"categories":["automation-workflow","memory-knowledge"],"confidence":0.5,"matches":0,"success_rate":0}],"trust":{"score":39,"verified":false,"data_access_risk":"high","permissions":["Resume documents in PDF, DOCX, or plain text format","Minimum 50-100 character resume content for reliable parsing","Internet connection for cloud-based parsing service","Structured candidate profiles with parsed skills and experience","Job description with clear requirements and preferred qualifications","Minimum 3-5 candidate profiles for meaningful ranking","Structured candidate profile with parsed skills, experience, education","Job description with clear requirements and evaluation criteria","LLM API access (likely OpenAI, Anthropic, or similar)","Candidate database with 10+ candidates minimum for meaningful batch processing"],"failure_modes":["Parsing accuracy degrades with non-standard resume formats, handwritten sections, or image-heavy layouts","No built-in handling for non-English resumes or specialized domain terminology (medical, legal, technical certifications)","Extracted data quality depends on resume completeness — sparse or poorly formatted resumes may have missing or misclassified fields","No version control or audit trail for extracted data changes","Semantic matching may miss hard requirements (e.g., specific certifications, security clearances) that require exact matching","Ranking quality depends on job description quality — vague or poorly written job specs produce unreliable matches","No built-in handling for role-specific context (e.g., startup vs enterprise experience, industry-specific knowledge)","Embeddings-based approach may conflate similar-sounding but distinct skills (e.g., 'project management' vs 'program management')","Assessment quality depends on LLM hallucination rates — may generate plausible but inaccurate evaluation rationales","No built-in validation that assessment criteria align with actual job success factors or legal hiring requirements","builder identity is not verified yet","no observed match outcomes yet"],"rank_breakdown":{"adoption":0.31666666666666665,"quality":0.67,"ecosystem":0.15000000000000002,"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":"2026-05-24T12:16:30.893Z","last_scraped_at":"2026-04-05T13:23:42.560Z","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=hirelakeai","compare_url":"https://unfragile.ai/compare?artifact=hirelakeai"}},"signature":"MIYfKOmv2OF2jWFRmkaetkdeOelzODY8zlTZNEJ8okIL5W9ngxHe4DtH8DCRFdR8+a4zuLTWeIRmw2a5h9+6Bw==","signedAt":"2026-06-20T09:49:36.419Z","signedBy":"unfragile.ai","version":1},"_links":{"self":"https://unfragile.ai/api/v1/passport/hirelakeai","artifact":"https://unfragile.ai/hirelakeai","verify":"https://unfragile.ai/api/v1/verify?slug=hirelakeai","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"}}