{"passport":{"unfragile":{"@version":"1.0","version":"2026-05","artifact":{"id":"tool_anse","slug":"anse","name":"Anse","type":"webapp","url":"https://anse.app","page_url":"https://unfragile.ai/anse","categories":["data-pipelines"],"tags":[],"pricing":{"model":"paid","free":false,"starting_price":null},"status":"active","verified":false},"capabilities":[{"id":"tool_anse__cap_0","uri":"capability://data.processing.analysis.visual.web.scraping.interface.with.point.and.click.selection","name":"visual-web-scraping-interface-with-point-and-click-selection","description":"Provides a browser-based visual interface where users click on page elements to define extraction patterns without writing code. The system likely uses DOM inspection APIs and CSS selector generation to map user clicks to structural selectors, then converts these selections into reusable extraction rules that can be applied across multiple pages with similar DOM structures.","intents":["I need to extract data from a website but don't know how to write scraping code","I want to quickly prototype a data extraction workflow without setting up a development environment","I need to define extraction rules by example rather than by writing XPath or CSS selectors manually"],"best_for":["Non-technical business analysts and researchers needing one-off data extraction","Small teams without dedicated data engineering resources","Users prototyping scraping workflows before investing in custom infrastructure"],"limitations":["Point-and-click selection requires consistent DOM structure across target pages—fails on heavily templated or dynamically restructured content","Visual interface abstracts away fine-grained control over extraction logic, limiting ability to handle edge cases or complex conditional extraction","No programmatic API for bulk rule definition—each extraction pattern must be created through the UI"],"requires":["Modern web browser with JavaScript enabled","Active internet connection","Anse account with active subscription"],"input_types":["web URLs","HTML pages"],"output_types":["structured data (JSON, CSV)","extraction rules (reusable selectors)"],"categories":["data-processing-analysis","web-scraping"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_anse__cap_1","uri":"capability://data.processing.analysis.dynamic.content.rendering.with.javascript.execution","name":"dynamic-content-rendering-with-javascript-execution","description":"Handles JavaScript-rendered pages by executing page scripts in a headless browser environment before extraction, rather than parsing raw HTML. This allows extraction from single-page applications and dynamically-loaded content that would be invisible to simple HTTP-based scrapers. The system likely maintains a browser pool and manages page lifecycle (load, wait for selectors, extract) to handle async content loading.","intents":["I need to scrape data from a React/Vue/Angular SPA that loads content dynamically","I want to extract data that only appears after JavaScript execution and DOM manipulation","I need to handle pages with lazy-loaded content or infinite scroll patterns"],"best_for":["Teams scraping modern web applications with heavy client-side rendering","Researchers extracting data from JavaScript-heavy sites where traditional HTTP scraping fails","Projects requiring extraction from sites with anti-bot protections that detect headless browsers"],"limitations":["JavaScript execution adds 2-10 second latency per page compared to raw HTML parsing, making large-scale scraping slower and more resource-intensive","Headless browser execution consumes significant memory and CPU—not suitable for scraping millions of pages without distributed infrastructure","Cannot handle pages requiring user interaction (login, CAPTCHA, multi-step navigation) without additional configuration","Execution timeout limits prevent scraping pages with very slow or infinite-loading content"],"requires":["Anse subscription tier supporting JavaScript rendering","Target pages must be publicly accessible without authentication","Reasonable page load times (typically <30 seconds)"],"input_types":["web URLs","SPA endpoints"],"output_types":["rendered HTML","structured data from rendered DOM"],"categories":["data-processing-analysis","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_anse__cap_2","uri":"capability://data.processing.analysis.automated.data.validation.and.schema.enforcement","name":"automated-data-validation-and-schema-enforcement","description":"Applies schema-based validation to extracted data, checking field types, required fields, format constraints, and value ranges before returning results. The system likely uses a declarative schema definition (JSON Schema or similar) that users configure through the UI, then validates each extracted record against this schema, optionally cleaning or rejecting invalid data based on configured rules.","intents":["I need to ensure extracted data matches expected types and formats before using it downstream","I want to automatically clean or reject malformed data without manual post-processing","I need to enforce business rules on extracted fields (e.g., prices must be positive numbers, emails must be valid)"],"best_for":["Data pipelines requiring high data quality without manual validation steps","Teams building ETL workflows where invalid data causes downstream failures","Projects with strict data governance requirements or compliance needs"],"limitations":["Schema definition through UI may be cumbersome for complex nested structures or conditional validation rules","Validation rules are static—cannot adapt based on page context or dynamic requirements","No built-in fuzzy matching or tolerance for minor format variations (e.g., phone number formatting differences)","Rejected records are typically discarded rather than logged for manual review"],"requires":["Schema definition configured in Anse UI or API","Clear understanding of expected data types and constraints"],"input_types":["extracted structured data (JSON, CSV)"],"output_types":["validated data (JSON, CSV)","validation error logs"],"categories":["data-processing-analysis","safety-moderation"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_anse__cap_3","uri":"capability://data.processing.analysis.multi.page.extraction.with.pattern.reuse","name":"multi-page-extraction-with-pattern-reuse","description":"Allows users to define extraction patterns once and apply them across multiple pages with similar structure, automatically handling pagination and URL pattern matching. The system likely uses template matching or structural similarity detection to identify pages that match a defined pattern, then applies the same extraction rules to each matched page, aggregating results into a single dataset.","intents":["I need to scrape data from multiple pages of a website with consistent structure (e.g., product listings across pages)","I want to extract data from a list of similar URLs without defining rules for each URL individually","I need to handle pagination automatically without manually specifying next-page selectors"],"best_for":["Bulk data extraction projects requiring consistent rules across many pages","E-commerce and directory scraping where pages follow a template pattern","Research projects collecting data from multiple similar sources"],"limitations":["Requires consistent DOM structure across pages—fails if page layouts vary significantly","Pattern matching may incorrectly identify non-matching pages as valid targets, leading to malformed data","No built-in handling for pages with different pagination mechanisms (offset-based, cursor-based, infinite scroll)","Extraction across many pages may hit rate limits or IP blocks without built-in retry/proxy logic"],"requires":["Target pages must have consistent structural patterns","Anse subscription tier supporting batch extraction","Clear URL patterns or pagination rules"],"input_types":["URL patterns","page lists"],"output_types":["aggregated structured data (JSON, CSV)","extraction statistics and error logs"],"categories":["data-processing-analysis","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_anse__cap_4","uri":"capability://data.processing.analysis.data.cleaning.and.transformation.pipeline","name":"data-cleaning-and-transformation-pipeline","description":"Provides built-in transformations for extracted data such as text normalization, whitespace trimming, date parsing, unit conversion, and field mapping. The system likely exposes a library of transformation functions through the UI that users can chain together, applying them to extracted fields before output. Transformations may include regex-based text extraction, conditional field mapping, and aggregation operations.","intents":["I need to clean extracted text (remove extra whitespace, normalize case, strip HTML tags)","I want to parse dates in various formats into a standard format","I need to convert units or perform calculations on extracted numeric values"],"best_for":["Data cleaning workflows where extracted data requires normalization before use","Teams avoiding post-processing scripts by embedding transformations in the extraction pipeline","Projects with strict data format requirements (e.g., standardized date formats, currency normalization)"],"limitations":["Transformation library is likely limited to common operations—complex custom logic requires external processing","No support for conditional transformations based on field values or context","Transformation rules are static and cannot adapt based on data patterns or anomalies","No audit trail or rollback capability if transformations produce unexpected results"],"requires":["Clear understanding of required transformations","Anse UI access to configure transformation rules"],"input_types":["extracted structured data (JSON, CSV)"],"output_types":["transformed structured data (JSON, CSV)"],"categories":["data-processing-analysis"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_anse__cap_5","uri":"capability://automation.workflow.scheduled.extraction.with.change.detection","name":"scheduled-extraction-with-change-detection","description":"Enables users to schedule recurring scraping jobs that run at specified intervals and optionally detect changes in extracted data compared to previous runs. The system likely maintains a job scheduler (cron-based or similar) and stores historical snapshots of extracted data, comparing new extractions against previous versions to identify additions, deletions, or modifications. Change detection may trigger notifications or webhooks.","intents":["I need to monitor a website for price changes or new product listings","I want to track changes in competitor data or market information over time","I need to run extraction jobs on a schedule without manual intervention"],"best_for":["Monitoring and alerting use cases where data changes trigger actions","Time-series data collection for trend analysis or historical tracking","Automated workflows that depend on periodic data updates"],"limitations":["Scheduling granularity is typically limited to hourly or daily intervals—cannot handle sub-minute frequency requirements","Change detection requires storing historical snapshots, which increases storage costs and may hit quota limits for large datasets","No built-in deduplication or fuzzy matching for detecting semantic changes (e.g., price changes of <1%)","Webhook delivery is not guaranteed—failed notifications may not be retried or logged"],"requires":["Anse subscription tier supporting scheduled jobs","Webhook endpoint or notification channel configured","Sufficient storage quota for historical data retention"],"input_types":["extraction rules","schedule configuration"],"output_types":["scheduled extraction results","change detection alerts","historical data snapshots"],"categories":["automation-workflow","monitoring"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_anse__cap_6","uri":"capability://tool.use.integration.export.and.integration.with.external.systems","name":"export-and-integration-with-external-systems","description":"Supports exporting extracted data to multiple formats and external systems including CSV, JSON, databases, and cloud storage (S3, Google Cloud Storage). The system likely provides pre-built connectors for common destinations and may support webhook-based push to custom endpoints. Export may be triggered manually or automatically as part of scheduled jobs.","intents":["I need to export extracted data to CSV or JSON for analysis in Excel or Python","I want to automatically push extracted data to a database or data warehouse","I need to integrate scraped data into my existing data pipeline or BI tool"],"best_for":["Teams integrating scraped data into existing data infrastructure","Projects requiring data in multiple formats for different downstream consumers","Workflows where extracted data feeds into analytics or reporting systems"],"limitations":["Export connectors are limited to pre-built integrations—custom destinations require webhook or API integration","Large exports may be rate-limited or split into multiple files, requiring client-side reassembly","No built-in retry logic for failed exports—failed deliveries may require manual intervention","Export credentials (database passwords, API keys) must be stored in Anse, creating security considerations"],"requires":["Destination system credentials or API keys","Anse subscription tier supporting the target export format","Network connectivity to destination systems"],"input_types":["extracted structured data (JSON, CSV)"],"output_types":["CSV files","JSON files","database records","cloud storage objects"],"categories":["tool-use-integration","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_anse__cap_7","uri":"capability://automation.workflow.proxy.and.rate.limiting.management","name":"proxy-and-rate-limiting-management","description":"Manages HTTP requests through configurable proxy pools and rate limiting to avoid IP blocks and respect target site policies. The system likely maintains a pool of proxy servers and distributes requests across them, with configurable delays between requests and per-domain rate limits. Users may configure proxy rotation strategies and request headers to mimic browser behavior.","intents":["I need to scrape a site that blocks rapid requests or IP-based rate limiting","I want to rotate through multiple IP addresses to avoid being blocked","I need to respect a website's rate limits while extracting data efficiently"],"best_for":["Large-scale scraping projects requiring distributed request handling","Sites with strict rate limiting or IP-based blocking","Teams needing to balance extraction speed with ethical scraping practices"],"limitations":["Proxy management adds latency and cost—each request must route through proxy infrastructure","Proxy quality varies; some proxies may be blocked or slow, reducing overall throughput","Rate limiting is static and cannot adapt to dynamic server responses or changing site policies","No built-in detection of CAPTCHA or other anti-bot mechanisms—requests may fail silently","Proxy credentials and configuration are stored in Anse, creating security and compliance considerations"],"requires":["Anse subscription tier supporting proxy management","Proxy server credentials or access to proxy pool","Configuration of rate limits and proxy rotation strategy"],"input_types":["proxy configuration","rate limit rules"],"output_types":["proxied HTTP requests","request logs with proxy information"],"categories":["automation-workflow","safety-moderation"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_anse__cap_8","uri":"capability://automation.workflow.extraction.rule.versioning.and.maintenance","name":"extraction-rule-versioning-and-maintenance","description":"Tracks versions of extraction rules and allows users to update rules when target site structure changes, with optional rollback to previous versions. The system likely maintains a version history of each extraction rule and may provide alerts when extraction fails (indicating potential site structure changes). Users can test updated rules against sample pages before deploying to production.","intents":["I need to update extraction rules when a website changes its HTML structure","I want to test rule changes on sample data before applying them to production jobs","I need to track changes to extraction rules and maintain a history for audit purposes"],"best_for":["Long-running scraping projects where target sites frequently change structure","Teams managing multiple extraction rules across different sites","Projects with compliance or audit requirements for tracking rule changes"],"limitations":["Version history may consume significant storage for rules with many iterations","No automatic detection of site structure changes—users must manually update rules or rely on extraction failures","Testing UI may not accurately reflect production behavior if pages are dynamic or personalized","Rollback to previous versions may not work if target site structure has changed significantly"],"requires":["Anse UI access to manage rule versions","Sample pages or test data for validating rule changes"],"input_types":["extraction rules","test pages"],"output_types":["rule versions","test results","change history"],"categories":["automation-workflow","planning-reasoning"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_anse__cap_9","uri":"capability://tool.use.integration.api.based.programmatic.access.to.extraction","name":"api-based-programmatic-access-to-extraction","description":"Exposes extraction capabilities through a REST or GraphQL API, allowing developers to trigger scraping jobs, retrieve results, and manage rules programmatically. The system likely provides authentication via API keys and supports both synchronous (wait for results) and asynchronous (poll for results) request patterns. API responses include structured data and metadata about extraction success/failure.","intents":["I need to integrate Anse scraping into my application or backend service","I want to trigger scraping jobs programmatically based on application events","I need to retrieve extracted data via API for real-time processing"],"best_for":["Developers building applications that require dynamic scraping capabilities","Backend services that need to trigger scraping as part of larger workflows","Teams integrating Anse with custom applications or microservices"],"limitations":["API rate limits may restrict the frequency of extraction requests, requiring queuing or batching","Synchronous API calls may timeout for slow-loading pages, forcing users to implement polling logic","API documentation may be incomplete or lack examples for complex use cases","Authentication via API keys requires secure credential management in client applications"],"requires":["Anse API key with appropriate permissions","API documentation and endpoint reference","HTTP client library or SDK (if provided)"],"input_types":["API requests with extraction rule IDs or inline rule definitions","URL parameters"],"output_types":["JSON responses with extracted data","extraction status and metadata"],"categories":["tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0}],"trust":{"score":40,"verified":false,"data_access_risk":"high","permissions":["Modern web browser with JavaScript enabled","Active internet connection","Anse account with active subscription","Anse subscription tier supporting JavaScript rendering","Target pages must be publicly accessible without authentication","Reasonable page load times (typically <30 seconds)","Schema definition configured in Anse UI or API","Clear understanding of expected data types and constraints","Target pages must have consistent structural patterns","Anse subscription tier supporting batch extraction"],"failure_modes":["Point-and-click selection requires consistent DOM structure across target pages—fails on heavily templated or dynamically restructured content","Visual interface abstracts away fine-grained control over extraction logic, limiting ability to handle edge cases or complex conditional extraction","No programmatic API for bulk rule definition—each extraction pattern must be created through the UI","JavaScript execution adds 2-10 second latency per page compared to raw HTML parsing, making large-scale scraping slower and more resource-intensive","Headless browser execution consumes significant memory and CPU—not suitable for scraping millions of pages without distributed infrastructure","Cannot handle pages requiring user interaction (login, CAPTCHA, multi-step navigation) without additional configuration","Execution timeout limits prevent scraping pages with very slow or infinite-loading content","Schema definition through UI may be cumbersome for complex nested structures or conditional validation rules","Validation rules are static—cannot adapt based on page context or dynamic requirements","No built-in fuzzy matching or tolerance for minor format variations (e.g., phone number formatting differences)","builder identity is not verified yet","no observed match outcomes yet"],"rank_breakdown":{"adoption":0.31666666666666665,"quality":0.72,"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":"2026-05-24T12:16:29.133Z","last_scraped_at":"2026-04-05T13:23:42.561Z","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=anse","compare_url":"https://unfragile.ai/compare?artifact=anse"}},"signature":"LnvYAOyFqmKJr4D8BYgJTujTYE4DWnMRDC9kTHM8Inm/xR7ER1o4eRqi8PU2naxRnYSfUjk5bJpNbk4qabmtDg==","signedAt":"2026-06-19T22:22:15.487Z","signedBy":"unfragile.ai","version":1},"_links":{"self":"https://unfragile.ai/api/v1/passport/anse","artifact":"https://unfragile.ai/anse","verify":"https://unfragile.ai/api/v1/verify?slug=anse","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"}}