{"passport":{"unfragile":{"@version":"1.0","version":"2026-05","artifact":{"id":"observable","slug":"observable","name":"Observable","type":"webapp","url":"https://observablehq.com","page_url":"https://unfragile.ai/observable","categories":["data-analysis"],"tags":[],"pricing":{"model":"free","free":true,"starting_price":null},"status":"active","verified":false},"capabilities":[{"id":"observable__cap_0","uri":"capability://code.generation.editing.reactive.javascript.notebook.execution.with.automatic.dependency.tracking","name":"reactive javascript notebook execution with automatic dependency tracking","description":"Executes JavaScript code in browser-isolated cells with automatic reactive dependency graph computation. When a variable changes, Observable's runtime automatically identifies and re-executes all dependent cells in topological order without manual refresh. Uses a declarative cell-based model where each cell declares its inputs and outputs, enabling fine-grained reactivity similar to spreadsheet formulas but for arbitrary code.","intents":["I want to write exploratory data analysis code where changing one variable automatically updates all downstream visualizations","I need to prototype interactive analyses without setting up a local development environment","I want to iterate on data transformations and see results immediately without manual re-running"],"best_for":["data analysts and scientists doing exploratory data analysis","visualization developers prototyping interactive charts","researchers iterating on analyses with immediate feedback"],"limitations":["All computation happens in browser — limited by client machine RAM (typically 2-8GB available), single-threaded JavaScript execution","No persistent state between sessions — data must be reloaded from external sources on each notebook load","Reactive graph complexity can cause performance degradation with hundreds of interdependent cells","No server-side execution option — cannot offload heavy computation to backend"],"requires":["Modern web browser (Chrome, Firefox, Safari, Edge)","JavaScript proficiency to write cell code","Internet connection for notebook loading and data fetching"],"input_types":["JavaScript code","Variable references from other cells","External data via API/database/file imports"],"output_types":["Computed values","DOM elements (visualizations, tables, text)","Side effects (API calls, DOM mutations)"],"categories":["code-generation-editing","reactive-programming"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"observable__cap_1","uri":"capability://image.visual.declarative.data.visualization.via.observable.plot.api.with.mark.based.composition","name":"declarative data visualization via observable plot api with mark-based composition","description":"Provides a declarative, mark-based charting library (Observable Plot) that composes visualizations from primitive marks (dots, lines, cells, bars) with data encoding specifications. Plot uses a functional composition pattern where marks are combined with data transformations (grouping, normalization, windowing) to create complex charts. Supports 20+ mark types and integrates with D3 for custom visualization needs, rendering to SVG with automatic axis/legend generation.","intents":["I want to create publication-quality charts without writing D3 boilerplate code","I need to build interactive dashboards with multiple coordinated visualizations","I want to explore data visually by quickly iterating on chart specifications"],"best_for":["data journalists creating data-driven stories","business intelligence teams building dashboards","visualization developers prototyping chart designs","analysts who want declarative syntax over imperative D3"],"limitations":["SVG rendering limits performance with 10,000+ data points — no Canvas fallback mentioned","Custom mark types require D3 knowledge — Plot API covers common charts but not all specialized visualizations","No built-in interactivity beyond Observable Inputs — tooltips, brushing, linked selection require custom code","Maximum dataset size constrained by browser memory — large datasets must be pre-aggregated or sampled"],"requires":["JavaScript knowledge to write Plot specifications","Data in JavaScript-accessible format (arrays, objects, or fetched from API/database)","Observable notebook environment or Observable Framework for deployment"],"input_types":["JavaScript arrays or objects (tabular data)","Data transformations (grouping, filtering, aggregation)","D3 scale specifications for custom encodings"],"output_types":["SVG-rendered charts","Interactive visualizations with Observable Inputs integration","Embedded charts with optional watermark (removable on Pro tier)"],"categories":["image-visual","data-processing-analysis"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"observable__cap_10","uri":"capability://automation.workflow.observable.framework.static.site.generation.for.data.app.deployment","name":"observable framework static site generation for data app deployment","description":"Open-source static site generator that compiles Observable notebooks into standalone HTML/JavaScript applications deployable to any static hosting (Vercel, Netlify, GitHub Pages, etc.). Supports multiple pages, navigation, and integration with JavaScript/TypeScript for custom logic. Notebooks are pre-executed at build time, generating static HTML with embedded data, reducing runtime dependencies and improving performance.","intents":["I want to deploy a data dashboard to static hosting without Observable infrastructure","I need to build a multi-page data app with custom navigation","I want to avoid vendor lock-in by hosting my data app independently"],"best_for":["teams building data products for independent deployment","organizations with static hosting infrastructure (Vercel, Netlify)","developers wanting to avoid Observable vendor lock-in","projects requiring custom domain and branding"],"limitations":["Open-source but separate from Observable.com — requires local development environment setup","Build-time execution — cannot use scheduled notebook runs or dynamic data fetching at runtime (must pre-fetch at build)","No multiplayer editing — Framework apps are deployed, not collaboratively edited","Deployment complexity — requires Node.js, build tools, and hosting knowledge","Data freshness — static generation means data is stale until next build (no real-time updates)"],"requires":["Node.js 18+ for local development","Observable Framework CLI (npm install)","Static hosting provider (Vercel, Netlify, GitHub Pages, etc.)","Git repository for version control"],"input_types":["Observable notebook files (.md with JavaScript code blocks)","Custom JavaScript/TypeScript files","Data files (CSV, JSON, etc.)"],"output_types":["Static HTML/JavaScript site","Deployable to any static host","Self-contained with no Observable.com dependency"],"categories":["automation-workflow","code-generation-editing"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"observable__cap_11","uri":"capability://automation.workflow.workspace.level.access.control.and.guest.management.with.role.based.permissions","name":"workspace-level access control and guest management with role-based permissions","description":"Manages team access at the workspace level (Pro tier only), allowing workspace owners to invite guests with specific roles and permissions. Supports different access levels: editors (can create/edit notebooks), viewers (read-only access to published notebooks), and potentially other roles. Guest access is managed separately from notebook-level sharing, enabling organization-wide permission hierarchies.","intents":["I want to invite a team member to my workspace so they can edit multiple notebooks","I need to give a stakeholder read-only access to all dashboards in my workspace","I want to manage team permissions centrally rather than per-notebook"],"best_for":["organizations with multiple teams using Observable","teams requiring centralized access control","enterprises with compliance requirements for permission auditing"],"limitations":["Pro tier only — free tier does not support workspace guest management","Role granularity unknown — unclear what roles are available beyond editor/viewer","Permission inheritance unclear — how notebook-level permissions interact with workspace-level permissions","Audit logging unknown — unclear if guest access changes are logged","No SAML/SSO mentioned — unclear if enterprise authentication is supported"],"requires":["Pro tier subscription ($22/month per editor)","Workspace ownership or admin role","Guest email addresses or Observable accounts"],"input_types":["Guest email addresses","Role assignments","Permission configurations"],"output_types":["Access control configuration","Guest invitations","Permission audit trail (if available)"],"categories":["automation-workflow","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"observable__cap_12","uri":"capability://automation.workflow.observable.canvases.collaborative.whiteboarding.with.embedded.queries.and.visualizations","name":"observable canvases collaborative whiteboarding with embedded queries and visualizations","description":"Separate product (limited details available) that combines collaborative whiteboards with embedded data queries, tables, charts, sketches, and notes. Allows teams to mix structured data analysis (queries, visualizations) with unstructured collaboration (sketches, text notes) in a single canvas. Real-time collaboration enables multiple users to work on the same canvas simultaneously.","intents":["I want to collaborate on data analysis while also sketching ideas and taking notes","I need a space where my team can mix data exploration with brainstorming","I want to embed live data queries in a collaborative whiteboard"],"best_for":["teams combining data analysis with creative brainstorming","organizations wanting to move beyond separate tools (Figma + notebooks)","cross-functional teams mixing technical and non-technical collaboration"],"limitations":["Product details sparse — limited public documentation available","Pricing unknown — unclear if separate from Observable subscription or included","Feature completeness unknown — unclear what query types and visualizations are supported","Integration with Observable notebooks unclear — how Canvases relate to existing notebooks","Maturity unknown — appears to be new product (2025), stability/reliability unproven"],"requires":["Observable account (pricing/tier requirements unclear)","Access to Observable Canvases (may be limited availability)"],"input_types":["Data queries (SQL, API calls)","Sketches and drawings","Text notes and annotations","Chart specifications"],"output_types":["Collaborative canvas with mixed content","Embedded visualizations and tables","Shared whiteboard state"],"categories":["automation-workflow","data-processing-analysis"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"observable__cap_13","uri":"capability://image.visual.d3.js.integration.and.custom.visualization.authoring.with.full.dom.control","name":"d3.js integration and custom visualization authoring with full dom control","description":"Provides direct access to D3.js library within notebooks, enabling custom visualization development beyond Observable Plot's mark-based API. Developers can write imperative D3 code to create specialized charts, interactive graphics, and data-driven animations. D3 selections, scales, axes, and transitions are fully available, with Observable's reactive system automatically re-running D3 code when dependencies change.","intents":["I want to create a custom visualization that Observable Plot doesn't support","I need to build an interactive graphic with complex interactions and animations","I want to leverage D3's full power for specialized data visualization"],"best_for":["visualization specialists and data artists","teams building custom interactive graphics","developers with deep D3 expertise"],"limitations":["Requires D3 knowledge — steep learning curve for developers unfamiliar with D3","Imperative code is harder to reason about than Observable Plot's declarative API","Reactive re-execution of D3 code can cause performance issues — D3 mutations may not be idempotent","No D3 version pinning mentioned — unclear which D3 version is available","Debugging D3 code in notebooks is harder than in local development environment"],"requires":["D3.js knowledge and experience","JavaScript proficiency","Understanding of SVG and DOM manipulation"],"input_types":["D3 code (selections, scales, axes, transitions)","Data arrays/objects","DOM element references"],"output_types":["SVG/Canvas visualizations","Interactive graphics with event handlers","Animated transitions"],"categories":["image-visual","code-generation-editing"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"observable__cap_2","uri":"capability://automation.workflow.real.time.multiplayer.notebook.editing.with.conflict.free.collaborative.state","name":"real-time multiplayer notebook editing with conflict-free collaborative state","description":"Enables multiple users to edit the same notebook simultaneously with real-time synchronization of code changes, cell execution, and outputs. Uses operational transformation or CRDT-like mechanisms (implementation details not disclosed) to merge concurrent edits without conflicts. Changes from one editor appear instantly to others, and cell re-execution is coordinated across all collaborators to maintain consistent state.","intents":["I want my team to collaborate on data analysis without passing files back and forth","I need to pair-program on a visualization with a colleague in real-time","I want to review and edit a colleague's notebook while they're working on it"],"best_for":["data teams collaborating on shared analyses","pair programming sessions for visualization development","code review workflows where reviewers can edit directly"],"limitations":["Pro tier only — free tier does not support multiplayer editing","Real-time sync overhead increases latency with many concurrent editors (exact threshold unknown)","No offline editing — requires persistent internet connection for collaborative features","Conflict resolution strategy not disclosed — potential for unexpected merge behavior in edge cases"],"requires":["Pro tier subscription ($22/month per editor)","All collaborators must have Observable accounts","Shared notebook with appropriate access permissions"],"input_types":["Code edits from multiple users","Cell execution triggers","Variable mutations"],"output_types":["Synchronized notebook state across all editors","Real-time cell execution results visible to all collaborators","Shared version history"],"categories":["automation-workflow","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"observable__cap_3","uri":"capability://automation.workflow.scheduled.notebook.execution.with.automated.data.refresh.and.result.persistence","name":"scheduled notebook execution with automated data refresh and result persistence","description":"Runs notebooks on a server-side schedule (frequency/timing unspecified) to automatically refresh data, recompute analyses, and persist results. Triggered execution fetches fresh data from connected sources (databases, APIs, cloud files), re-executes all cells, and stores outputs for later retrieval. Enables automation of recurring analyses without manual intervention, such as daily dashboards or weekly reports.","intents":["I want my dashboard to update automatically every morning with fresh data","I need to run a weekly analysis without manually triggering it","I want to cache computed results so viewers see fast-loading dashboards"],"best_for":["teams publishing automated reports and dashboards","analysts creating recurring analyses that need fresh data","organizations building data products with scheduled updates"],"limitations":["Pro tier only — free tier does not support scheduled execution","Execution frequency limits unknown — unclear if hourly, daily, or custom schedules supported","Timeout limits unknown — unclear how long a scheduled run can execute before termination","No conditional execution — cannot skip runs based on data freshness or other criteria","Execution environment constraints unknown — unclear if scheduled runs have different resource limits than interactive execution"],"requires":["Pro tier subscription ($22/month per editor)","Notebook with data sources that support automated refresh (databases, APIs, cloud files)","Schedule configuration (frequency/time not detailed in public docs)"],"input_types":["Notebook code with data fetch operations","Schedule specification (frequency, time of day)","Data source credentials for automated access"],"output_types":["Persisted notebook state after execution","Updated visualizations and computed results","Execution logs (availability unknown)"],"categories":["automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"observable__cap_4","uri":"capability://data.processing.analysis.sql.query.execution.with.direct.database.connectivity.and.result.materialization","name":"sql query execution with direct database connectivity and result materialization","description":"Executes SQL queries directly against connected databases (drivers/providers unspecified) from within notebook cells, returning results as JavaScript arrays/objects for further processing. Supports parameterized queries where cell variables can be interpolated into SQL, enabling dynamic queries based on user inputs or upstream computations. Results are materialized into memory for visualization and analysis.","intents":["I want to query my database directly from a notebook without writing Python/Node.js code","I need to create a dashboard that pulls fresh data from a SQL database on each load","I want to parameterize SQL queries based on user inputs or other cell values"],"best_for":["data analysts familiar with SQL who want to avoid learning JavaScript","teams with existing SQL-based data pipelines","organizations querying data warehouses (Snowflake, BigQuery, Redshift, etc.)"],"limitations":["Database drivers/providers supported unknown — unclear which databases are officially supported","Query result size limits unknown — large result sets may exhaust browser memory","No query optimization or execution planning — slow queries will block notebook execution","Authentication mechanism unclear — how credentials are stored and passed to database","No transaction support mentioned — unclear if multi-statement queries or transactions are supported"],"requires":["Database connection credentials (stored in Observable workspace, security model unclear)","SQL knowledge","Database that Observable supports (specific list not provided)"],"input_types":["SQL query strings","Query parameters from cell variables","Database connection configuration"],"output_types":["JavaScript arrays of objects (rows)","Queryable result sets for visualization","Error messages if query fails"],"categories":["data-processing-analysis","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"observable__cap_5","uri":"capability://data.processing.analysis.cloud.file.and.api.data.import.with.automatic.format.detection.and.caching","name":"cloud file and api data import with automatic format detection and caching","description":"Fetches data from cloud storage (S3, GCS, Azure Blob — providers unspecified) and web APIs, automatically detecting and parsing formats (CSV, JSON, Parquet, etc.). Caches fetched data within the notebook session to avoid redundant network requests. Supports both one-time imports and reactive data fetching where changes to parameters trigger fresh API calls.","intents":["I want to load a CSV from cloud storage without downloading it locally","I need to fetch data from a REST API and visualize it in a chart","I want my dashboard to refresh data from an API when a user changes a filter"],"best_for":["analysts working with cloud-native data sources","teams building dashboards from public APIs","organizations avoiding local data downloads for security/compliance reasons"],"limitations":["Cloud storage providers supported unknown — unclear which S3-compatible services work","API authentication mechanisms unclear — how OAuth, API keys, or other credentials are handled","Rate limiting not mentioned — unclear if Observable enforces or respects API rate limits","Data size limits unknown — large files may timeout or exhaust browser memory","Format support incomplete — Parquet and other binary formats may have limitations"],"requires":["Cloud storage credentials or public file URLs","API endpoint URLs and authentication tokens (if required)","Network connectivity"],"input_types":["Cloud file URLs (S3, GCS, etc.)","REST API endpoints","Authentication credentials (API keys, OAuth tokens)"],"output_types":["Parsed data as JavaScript arrays/objects","Cached data available to downstream cells","Error messages if fetch fails"],"categories":["data-processing-analysis","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"observable__cap_6","uri":"capability://tool.use.integration.interactive.input.components.with.reactive.binding.to.notebook.variables","name":"interactive input components with reactive binding to notebook variables","description":"Provides a library of UI input components (Observable Inputs: sliders, text inputs, dropdowns, date pickers, tables, buttons) that bind directly to notebook variables. When a user interacts with an input component, the bound variable updates and triggers reactive re-execution of dependent cells. Supports two-way binding where cell values can update input state.","intents":["I want users to filter a dashboard by selecting values from a dropdown","I need to create a slider that controls a visualization parameter","I want to build an interactive form that updates a table when submitted"],"best_for":["analysts building interactive dashboards for non-technical users","teams creating data exploration tools with user-facing controls","developers prototyping interactive applications quickly"],"limitations":["Component library limited to basic inputs — no advanced UI components like date range pickers or multi-select with search","Styling customization unclear — limited control over component appearance","Accessibility features unknown — unclear if components meet WCAG standards","No form validation framework — validation must be implemented manually in cells"],"requires":["Observable Inputs library (included in Observable environment)","JavaScript knowledge to bind inputs to variables","Understanding of reactive cell dependencies"],"input_types":["User interactions (clicks, text input, selections)","Initial values from cell variables"],"output_types":["Updated variable values","Triggered cell re-execution","DOM elements (rendered input components)"],"categories":["tool-use-integration","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"observable__cap_7","uri":"capability://automation.workflow.notebook.version.control.and.git.like.history.with.rollback.capability","name":"notebook version control and git-like history with rollback capability","description":"Maintains a version history of notebook changes (commits) with the ability to view, compare, and rollback to previous versions. Each save creates a snapshot of the notebook state. Provides a timeline view showing who made changes and when, enabling audit trails and recovery from accidental edits. Implementation uses Observable's proprietary version control (not Git).","intents":["I want to see what changed in a notebook between two points in time","I need to revert a notebook to a previous version after a mistake","I want to track who made changes to a shared notebook and when"],"best_for":["teams collaborating on shared notebooks","analysts who want to experiment safely with rollback capability","organizations requiring audit trails for compliance"],"limitations":["Proprietary version control — not compatible with Git, cannot be exported to Git repositories","Comparison view limitations unknown — unclear if diffs show code changes, output changes, or both","Retention policy unknown — unclear how long version history is retained","No branching mentioned — cannot create feature branches or parallel versions","Merge conflicts not mentioned — unclear how to handle conflicting changes from multiple editors"],"requires":["Observable notebook (version control is built-in)","No additional configuration needed"],"input_types":["Notebook code changes","Cell execution results"],"output_types":["Version history timeline","Diff view between versions","Rollback to previous state"],"categories":["automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"observable__cap_8","uri":"capability://automation.workflow.notebook.embedding.and.sharing.with.watermark.control.and.viewer.access.management","name":"notebook embedding and sharing with watermark control and viewer access management","description":"Publishes notebooks as embeddable HTML snippets that can be inserted into external websites or documents. Embeds include an Observable watermark by default (removable on Pro tier). Supports public sharing (anyone with link can view) and private sharing (access control via Observable accounts). Viewer tier allows read-only access without edit permissions, enabling sharing at scale without giving edit access.","intents":["I want to embed an interactive chart on my website without hosting it myself","I need to share a dashboard with stakeholders who should only view, not edit","I want to publish a data story with embedded visualizations"],"best_for":["data journalists publishing interactive stories","organizations sharing dashboards with external stakeholders","teams embedding visualizations in documentation or reports"],"limitations":["Watermark removal requires Pro tier ($22/month) — free tier always shows Observable branding","Viewer tier costs $10/month per viewer — expensive for large audiences (e.g., 100 viewers = $1000/month)","Embed customization limited — unclear if custom styling or sizing options available","Performance of embedded notebooks unknown — unclear if embedding adds latency or resource overhead","Viewer permissions granular only at notebook level — cannot restrict access to specific cells or outputs"],"requires":["Pro tier for watermark removal ($22/month per editor)","Viewer tier for read-only access ($10/month per viewer)","Public or private sharing configuration"],"input_types":["Notebook URL","Embed configuration (size, styling)"],"output_types":["Embeddable HTML snippet","Shared notebook URL","Access control configuration"],"categories":["automation-workflow","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"observable__cap_9","uri":"capability://code.generation.editing.ai.assisted.code.generation.and.suggestion.with.context.aware.completions","name":"ai-assisted code generation and suggestion with context-aware completions","description":"Provides an 'AI Assist' feature that generates code suggestions and completions within notebook cells. The AI model (provider and name unknown) analyzes notebook context (previous cells, data types, imports) to suggest relevant code. Supports both inline completions and full cell generation from natural language descriptions. Available on both free and Pro tiers.","intents":["I want to generate a chart specification without writing Plot code from scratch","I need help writing a SQL query based on my data schema","I want to quickly scaffold a data transformation without looking up syntax"],"best_for":["developers new to Observable or JavaScript","analysts who prefer natural language over code","teams accelerating prototyping with AI-generated scaffolding"],"limitations":["AI model provider unknown — unclear if using OpenAI, Anthropic, or proprietary model","Model capabilities unknown — unclear what types of code it can generate (Plot, D3, SQL, etc.)","Context window size unknown — unclear how much notebook history is provided to the model","Accuracy not specified — no information on hallucination rates or code quality","No fine-tuning mentioned — model is generic, not specialized for Observable patterns","Rate limits unknown — unclear if there are usage quotas on free tier"],"requires":["Observable notebook 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development environment setup","Build-time execution — cannot use scheduled notebook runs or dynamic data fetching at runtime (must pre-fetch at build)","builder identity is not verified yet","no observed match outcomes 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