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Supports multi-turn conversation to refine queries iteratively.","intents":["I want to ask questions about my data in plain English without writing SQL","I need to quickly prototype queries without memorizing database-specific syntax","I want the AI to explain what query it generated and why"],"best_for":["non-technical stakeholders querying databases without SQL knowledge","developers rapidly prototyping data exploration without context switching to query editors","teams using multiple database types who want a unified query interface"],"limitations":["LLM hallucination risk — generated queries may be syntactically valid but semantically incorrect without human review","Schema context size limited by LLM token window — very large schemas (1000+ tables) may be truncated or summarized","No automatic query optimization — generated queries may be inefficient for large datasets","Requires API key for external LLM provider (OpenAI, Anthropic, etc.) — no local-only option documented"],"requires":["Active LLM API key (OpenAI, Anthropic, or compatible provider)","Network connectivity to LLM provider","Database connection already established","Schema introspection completed for context injection"],"input_types":["natural language text (conversational questions)","multi-turn chat history for context"],"output_types":["generated query in database-specific syntax","query execution results (rows, documents, nodes)","natural language explanation of the query"],"categories":["text-generation-language","data-processing-analysis"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-whodb__cap_10","uri":"capability://automation.workflow.command.line.scripting.and.automation.with.query.templates","name":"command-line scripting and automation with query templates","description":"Supports writing shell scripts or CLI commands that execute templated queries with variable substitution, conditional logic, and output formatting. Enables automation of repetitive database tasks (backups, data exports, cleanup jobs) without writing application code. Integrates with standard Unix pipes and redirection for composability with other tools.","intents":["I want to automate a daily data export task without writing a Python script","I need to run a parameterized query from a cron job with different values each time","I want to pipe database results to other Unix tools for processing"],"best_for":["DevOps engineers automating database maintenance tasks","developers building lightweight ETL scripts","system administrators scheduling database backups and exports"],"limitations":["Shell scripting complexity increases with conditional logic — may require external script files","Variable substitution may be vulnerable to injection if not properly escaped","Output formatting limited to CLI-native formats (CSV, JSON, TSV) — no custom formatting","Error handling in scripts requires explicit exit code checking"],"requires":["Shell environment (bash, zsh, sh, etc.)","Query templates with variable placeholders","Optional: cron or task scheduler for automation"],"input_types":["query template with variable placeholders","environment variables or CLI arguments for substitution","optional conditional logic"],"output_types":["formatted query results (CSV, JSON, TSV)","piped output to other commands","exit codes for error handling"],"categories":["automation-workflow","code-generation-editing"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-whodb__cap_2","uri":"capability://data.processing.analysis.interactive.query.result.browsing.and.filtering","name":"interactive query result browsing and filtering","description":"Displays query results in a paginated, interactive TUI (terminal user interface) with column sorting, row filtering, and data type-aware formatting. Supports exporting results to CSV, JSON, or other formats. Implements keyboard navigation and search across result sets without requiring additional tools or context switching.","intents":["I want to explore query results interactively without piping to grep or awk","I need to sort and filter results by multiple columns to find specific records","I want to export results in a format compatible with downstream tools"],"best_for":["database administrators performing ad-hoc data exploration","developers debugging data issues in production databases","analysts extracting subsets of data for reporting"],"limitations":["Large result sets (100k+ rows) may cause TUI lag or memory overhead","Filtering is client-side only — no pushdown to database for optimization","Column width auto-sizing may truncate wide text fields without horizontal scrolling","No built-in visualization (charts, graphs) — export required for analysis tools"],"requires":["Terminal with TUI support (most modern terminals)","Query execution completed with results in memory"],"input_types":["query result set (rows/documents/nodes)","keyboard input for navigation and filtering"],"output_types":["formatted TUI display","exported files (CSV, JSON, TSV, etc.)"],"categories":["data-processing-analysis","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-whodb__cap_3","uri":"capability://data.processing.analysis.database.agnostic.query.syntax.translation.and.execution","name":"database-agnostic query syntax translation and execution","description":"Translates queries between database-specific syntaxes or executes queries written in a normalized intermediate format across different database types. For example, a single query structure can be executed against PostgreSQL, MongoDB, and Neo4j with automatic syntax adaptation. Uses a query abstraction layer that maps common operations (filter, project, join, aggregate) to database-native implementations.","intents":["I want to write a query once and run it against multiple databases","I need to migrate queries from one database type to another","I want a consistent query interface regardless of which database I'm connected to"],"best_for":["teams managing polyglot data architectures with multiple database types","data engineers building cross-database ETL pipelines","developers migrating data between different database systems"],"limitations":["Abstraction layer may not support database-specific advanced features (e.g., PostgreSQL window functions, MongoDB aggregation stages)","Performance varies significantly across databases — optimization hints may not translate","Complex joins across different database types not supported — requires manual federation","Normalized syntax may be less expressive than native query languages"],"requires":["Multiple database connections established","Query written in normalized intermediate format or auto-translated from native syntax"],"input_types":["normalized query format","native query syntax (with auto-translation)"],"output_types":["query execution results from target database","translated query in target database syntax"],"categories":["data-processing-analysis","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-whodb__cap_4","uri":"capability://automation.workflow.connection.profile.management.and.persistence","name":"connection profile management and persistence","description":"Stores and manages database connection profiles (credentials, connection strings, authentication methods) in a local encrypted or plaintext configuration file. Supports quick switching between saved connections via CLI flags or interactive selection. Implements credential management patterns to avoid hardcoding secrets in command history or shell scripts.","intents":["I want to save my database connections so I don't have to re-enter credentials each time","I need to switch between development, staging, and production databases quickly","I want to share connection profiles with my team securely"],"best_for":["developers managing multiple database environments","teams sharing database access configurations","DevOps engineers automating database exploration in CI/CD pipelines"],"limitations":["Credentials stored locally — no centralized secret management integration (e.g., HashiCorp Vault, AWS Secrets Manager)","Encryption implementation unknown — may store credentials in plaintext depending on configuration","No audit logging of connection profile access or modifications","Profile sharing requires manual file distribution — no built-in team collaboration features"],"requires":["Local filesystem write access for configuration storage","Optional: encryption key or passphrase for credential protection"],"input_types":["connection parameters (host, port, username, password, database name)","CLI flags or interactive prompts"],"output_types":["saved connection profile","list of available profiles"],"categories":["automation-workflow","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-whodb__cap_5","uri":"capability://automation.workflow.real.time.database.monitoring.and.change.detection","name":"real-time database monitoring and change detection","description":"Watches connected databases for schema changes, new tables/collections, or data modifications and alerts the user via CLI notifications or logs. Implements polling or event-based monitoring depending on database capabilities (e.g., PostgreSQL LISTEN/NOTIFY, MongoDB change streams, Redis keyspace notifications). Tracks changes over time with optional historical logging.","intents":["I want to be notified when the database schema changes","I need to detect when new tables or collections are added to a shared database","I want to monitor for unexpected data modifications in production"],"best_for":["database administrators monitoring production databases","developers debugging data consistency issues","teams detecting unauthorized schema changes"],"limitations":["Polling-based monitoring adds database load — may impact performance on high-traffic systems","Event-based monitoring requires database-specific features (not all databases support change streams)","No alerting integration — notifications limited to CLI output or local logs","Historical change tracking requires persistent storage — no built-in change log database"],"requires":["Active database connection","Database support for change detection (polling works universally, events require native support)","Optional: persistent storage for change history"],"input_types":["monitoring configuration (tables/collections to watch, polling interval)","filter criteria for change detection"],"output_types":["change notifications (schema changes, new objects, data modifications)","change history logs"],"categories":["automation-workflow","safety-moderation"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-whodb__cap_6","uri":"capability://data.processing.analysis.data.import.and.bulk.loading.from.external.sources","name":"data import and bulk loading from external sources","description":"Imports data from CSV, JSON, Parquet, or other formats into connected databases with automatic type inference and schema mapping. Supports batch inserts, upserts, and conflict resolution strategies. Implements streaming for large files to avoid memory exhaustion and provides progress tracking and error reporting for failed records.","intents":["I want to load a CSV file into my database without writing INSERT statements","I need to bulk import data from multiple sources with automatic type detection","I want to handle import errors gracefully and retry failed records"],"best_for":["data engineers loading data into data warehouses or lakes","developers seeding test databases with fixture data","analysts importing external datasets for analysis"],"limitations":["Type inference may be incorrect for ambiguous data (e.g., '123' as string vs integer)","No built-in data validation or cleansing — requires pre-processing for dirty data","Conflict resolution strategies limited to basic insert/update/ignore — no custom merge logic","Large file streaming may still consume significant memory for wide tables"],"requires":["Source file in supported format (CSV, JSON, Parquet, etc.)","Target database connection and write permissions","Optional: schema definition or auto-detection configuration"],"input_types":["file path or stream (CSV, JSON, Parquet, TSV, etc.)","mapping configuration (column names, types, target table)"],"output_types":["import status and statistics (rows inserted, errors, warnings)","error log with failed records and reasons"],"categories":["data-processing-analysis","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-whodb__cap_7","uri":"capability://memory.knowledge.query.history.and.saved.query.management","name":"query history and saved query management","description":"Maintains a searchable history of executed queries with timestamps and results metadata. Allows users to save frequently-used queries with names and descriptions, organize them into collections, and re-execute with parameter substitution. Implements full-text search over query history and saved queries for quick retrieval.","intents":["I want to find and re-run a query I executed yesterday without retyping it","I need to save common queries for my team to reuse","I want to search my query history to understand what data I've accessed"],"best_for":["database administrators performing repetitive queries","teams standardizing common data access patterns","developers auditing data access for compliance"],"limitations":["Query history stored locally — no centralized repository for team sharing","No version control for saved queries — overwrites lose previous versions","Parameter substitution may be limited to simple string replacement","Search performance degrades with very large query histories (10k+ queries)"],"requires":["Local filesystem for query history storage","Optional: team collaboration setup for sharing saved queries"],"input_types":["executed queries (captured automatically)","manual query save with name and description","search terms for query history"],"output_types":["query history list with metadata","saved query with parameter placeholders","search results"],"categories":["memory-knowledge","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-whodb__cap_8","uri":"capability://data.processing.analysis.data.visualization.and.summary.statistics.generation","name":"data visualization and summary statistics generation","description":"Generates summary statistics (count, min, max, average, percentiles) for numeric columns and frequency distributions for categorical data. Provides simple ASCII-based visualizations (histograms, bar charts) in the terminal or exports data for external visualization tools. Supports aggregation and grouping to create pivot-like summaries.","intents":["I want to understand the distribution of values in a column without exporting to Excel","I need to generate summary statistics for a dataset quickly","I want to create a pivot table-like summary grouped by multiple columns"],"best_for":["analysts exploring data distributions in the terminal","developers understanding data quality and outliers","data engineers validating data loads"],"limitations":["ASCII visualizations limited to simple charts — no advanced graphics","Aggregation performance degrades on very large datasets (100M+ rows)","No statistical tests or hypothesis testing built-in","Grouping limited to a few columns — complex multi-dimensional analysis requires export"],"requires":["Query result set with numeric or categorical data","Optional: aggregation and grouping configuration"],"input_types":["query result set","column selection for analysis","grouping and aggregation parameters"],"output_types":["summary statistics (JSON, text, or ASCII table)","ASCII visualizations (histograms, bar charts)","exported data for external tools"],"categories":["data-processing-analysis","search-retrieval"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-whodb__cap_9","uri":"capability://data.processing.analysis.database.comparison.and.diff.generation","name":"database comparison and diff generation","description":"Compares schemas or data between two connected databases and generates a diff report highlighting additions, deletions, and modifications. Supports schema-only comparison (table/collection structure) or full data comparison with row-level diffs. Useful for validating migrations, replication, or backup integrity. Generates migration scripts or sync commands to reconcile differences.","intents":["I want to verify that my database backup matches the production database","I need to check if a migration was applied correctly across multiple environments","I want to detect data inconsistencies between a primary and replica database"],"best_for":["database administrators validating backups and replicas","DevOps engineers verifying database migrations","teams detecting data drift between environments"],"limitations":["Full data comparison is slow for large tables (100M+ rows) — requires sampling or key-based comparison","Schema comparison may miss database-specific features (constraints, triggers, stored procedures)","Generated migration scripts may require manual review for complex changes","No support for comparing databases of different types (e.g., PostgreSQL vs MongoDB)"],"requires":["Two active database connections","Read permissions on both databases","Optional: schema or data filtering to limit comparison scope"],"input_types":["two database connections","comparison scope (schema, data, or both)","optional filters or key columns for data comparison"],"output_types":["diff report (schema additions/deletions/modifications)","data diff (row-level changes)","generated migration or sync scripts"],"categories":["data-processing-analysis","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0}],"trust":{"score":24,"verified":false,"data_access_risk":"high","permissions":["Network access to target database servers","Valid credentials (connection strings with auth embedded or environment variables)","Database drivers installed for each supported database type","Active LLM API key (OpenAI, Anthropic, or compatible provider)","Network connectivity to LLM provider","Database connection already established","Schema introspection completed for context injection","Shell environment (bash, zsh, sh, etc.)","Query templates with variable placeholders","Optional: cron or task scheduler for automation"],"failure_modes":["Schema introspection latency increases with database size (100k+ tables may take seconds)","Connection pooling not built-in — each CLI invocation creates fresh connections","No support for database-specific features like PostgreSQL JSON operators or MongoDB aggregation pipeline optimization hints","LLM hallucination risk — generated queries may be syntactically valid but semantically incorrect without human review","Schema context size limited by LLM token window — very large schemas (1000+ tables) may be truncated or summarized","No automatic query optimization — generated queries may be inefficient for large datasets","Requires API key for external LLM provider (OpenAI, Anthropic, etc.) — no local-only option documented","Shell scripting complexity increases with conditional logic — may require external script files","Variable substitution may be vulnerable to injection if not properly escaped","Output formatting limited to CLI-native formats (CSV, JSON, TSV) — no custom formatting","builder identity is not verified yet","no observed match outcomes yet"],"rank_breakdown":{"adoption":0.05,"quality":0.32,"ecosystem":0.39999999999999997,"match_graph":0.25,"freshness":0.52,"weights":{"adoption":0.3,"quality":0.2,"ecosystem":0.15,"match_graph":0.3,"freshness":0.05}},"observed_outcomes":{"matches":0,"success_rate":0,"avg_confidence":0,"top_intents":[],"last_matched_at":null},"maintenance":{"status":"active","updated_at":"2026-06-17T09:51:04.689Z","last_scraped_at":"2026-05-03T14:00:23.056Z","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=whodb","compare_url":"https://unfragile.ai/compare?artifact=whodb"}},"signature":"Hj6+d+guNEenpCB6v02aUwJrSKZgYa5ufGt18P88qKc7IHxTCp8glXr/5/Rhogc39Pm+gL0uHJknnsWZm1x0Bw==","signedAt":"2026-06-22T02:46:26.826Z","signedBy":"unfragile.ai","version":1},"_links":{"self":"https://unfragile.ai/api/v1/passport/whodb","artifact":"https://unfragile.ai/whodb","verify":"https://unfragile.ai/api/v1/verify?slug=whodb","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"}}