{"passport":{"unfragile":{"@version":"1.0","version":"2026-05","artifact":{"id":"vscode-multi-multi","slug":"multi-frontier-ai-coding-agent","name":"Multi – Frontier AI Coding Agent","type":"agent","url":"https://marketplace.visualstudio.com/items?itemName=Multi.multi","page_url":"https://unfragile.ai/multi-frontier-ai-coding-agent","categories":["ai-agents"],"tags":["agent","ai","anthropic","assistant","automation","claude","cline","code generation","copilot","debugging","gemini","gemini cli","large language model","llm","multi","openai","pair programmer","refactoring","testing"],"pricing":{"model":"freemium","free":true,"starting_price":null},"status":"active","verified":false},"capabilities":[{"id":"vscode-multi-multi__cap_0","uri":"capability://tool.use.integration.multi.provider.llm.model.orchestration.with.profile.based.switching","name":"multi-provider llm model orchestration with profile-based switching","description":"Abstracts 30+ LLM providers (Claude, Gemini, OpenAI, OpenRouter, Ollama, etc.) behind a unified interface, allowing users to define reusable 'Profiles' that bundle provider credentials, model selection, and configuration parameters. Profiles persist across sessions and enable instant model switching without reconfiguring API keys or parameters, supporting both cloud-hosted and locally-deployed models through a single configuration layer.","intents":["I want to compare Claude and GPT-4 outputs on the same coding task without reconfiguring credentials each time","I need to switch between expensive frontier models and cheaper local Ollama instances based on task complexity","I want to lock my team to specific model versions and providers via shared profile configurations"],"best_for":["teams evaluating multiple LLM providers for cost-performance tradeoffs","developers building multi-model agent systems who need rapid provider switching","organizations with hybrid cloud/local model deployments"],"limitations":["Profile switching requires manual selection — no automatic provider selection based on task type or cost","API key storage mechanism not documented — unclear if keys are encrypted or stored in plaintext","No built-in rate limiting or quota management across providers","Model-specific capabilities (e.g., vision, function calling) not abstracted — users must know provider-specific APIs"],"requires":["API keys for at least one supported provider (OpenAI, Anthropic, Google, etc.)","VS Code 1.80+ or compatible JetBrains IDE","Network access to provider APIs (or local Ollama instance for offline use)"],"input_types":["provider name (string)","model identifier (string)","API key (credential)","configuration parameters (JSON-like object)"],"output_types":["active profile metadata (JSON)","model availability status (boolean)","provider health check (status code)"],"categories":["tool-use-integration","multi-provider-abstraction"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"vscode-multi-multi__cap_1","uri":"capability://planning.reasoning.autonomous.codebase.aware.task.decomposition.and.execution","name":"autonomous codebase-aware task decomposition and execution","description":"Parses user intent into discrete subtasks, autonomously reads/writes/edits files, executes shell commands, and searches the codebase to gather context — all without blocking the developer's active editing. The agent maintains task state and can fork execution branches (creating isolated worktrees) to explore alternative solutions in parallel, then restore previous states if a branch fails. Context awareness includes project structure, file dependencies, and web-fetched documentation.","intents":["I want to refactor a legacy module — the agent should identify all dependent files, plan the refactoring steps, and execute them while I continue coding","I need to implement a feature but want the agent to explore two different architectural approaches in parallel branches","I want the agent to automatically fetch API documentation, understand my codebase structure, and generate implementation code without me manually copying context"],"best_for":["solo developers and small teams shipping features rapidly without context-switching overhead","developers working on large, interconnected codebases where manual context gathering is expensive","teams using trunk-based development or feature branches where isolated task exploration is valuable"],"limitations":["Task decomposition quality depends on LLM reasoning — complex multi-step refactorings may fail if the agent misunderstands dependencies","Worktree isolation adds ~500ms-2s overhead per branch fork/restore cycle (git operations)","No built-in rollback mechanism if file writes corrupt the codebase — approval workflows are the only safeguard","Context window limitations mean large codebases (>50k lines) may not fit in a single task context","Shell command execution is unrestricted once approved — no sandboxing or command whitelisting"],"requires":["Git repository initialized in the project (for worktree branching)","Write permissions on the project directory","Shell access (bash, zsh, PowerShell, etc.)","Sufficient disk space for worktree clones if using branch isolation"],"input_types":["natural language task description (string)","codebase files (text, code)","shell command output (text)","web page content (HTML, markdown)"],"output_types":["modified source files (code)","shell command results (text, exit codes)","task execution log (structured JSON)","branch state snapshots (git refs)"],"categories":["planning-reasoning","automation-workflow","code-generation-editing"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"vscode-multi-multi__cap_10","uri":"capability://tool.use.integration.multi.platform.ide.integration.with.consistent.ux","name":"multi-platform ide integration with consistent ux","description":"Provides a unified agent interface across VS Code and 9+ JetBrains IDEs (IntelliJ, PyCharm, WebStorm, GoLand, CLion, RustRover, Android Studio, Rider, PhpStorm, RubyMine) plus alternative editors (Cursor, Windsurf, Kiro, Antigravity). The same profiles, configurations, and capabilities work across all platforms, enabling developers to switch IDEs without reconfiguring the agent. Integration is achieved through IDE-specific plugins that expose a common API.","intents":["I want to use the same AI agent across VS Code and PyCharm without reconfiguring credentials or settings","I need my team to use a consistent agent across different IDEs and operating systems","I want to switch from VS Code to Cursor without losing my agent configuration"],"best_for":["teams with heterogeneous IDE preferences (some use VS Code, others use JetBrains)","developers who switch between IDEs for different projects","organizations standardizing on a single AI agent across all development tools"],"limitations":["IDE-specific features may not be available across all platforms — unclear which capabilities are limited to specific IDEs","UI/UX may differ between IDE implementations — no guarantee of consistent user experience","Installation and configuration process differs per IDE — no unified setup flow","Performance and latency may vary across IDE implementations","Alternative editor support (Cursor, Windsurf, Kiro, Antigravity) is mentioned but not documented — unclear if these are first-class integrations or community-maintained"],"requires":["VS Code 1.80+ OR JetBrains IDE (version not specified) OR compatible alternative editor","Multi extension installed for the target IDE"],"input_types":["IDE identifier (string: 'vscode', 'intellij', 'pycharm', etc.)"],"output_types":["IDE compatibility status (supported/unsupported)","installation instructions (markdown)"],"categories":["tool-use-integration","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"vscode-multi-multi__cap_11","uri":"capability://automation.workflow.freemium.pricing.with.usage.based.monetization","name":"freemium pricing with usage-based monetization","description":"Offers free access to the core agent capabilities with limitations on usage (likely API call limits, task execution limits, or model access restrictions). Premium tiers unlock higher usage limits, priority support, or access to frontier models. The pricing model is not fully documented, but the extension is listed as 'freemium' on the marketplace, suggesting a free tier with paid upgrades.","intents":["I want to try the agent for free before committing to a paid plan","I need unlimited task execution and model access for my team","I want to understand the cost of using the agent at scale"],"best_for":["individual developers and small teams evaluating the agent","organizations with high usage who need predictable pricing","developers who want to avoid vendor lock-in with a free tier"],"limitations":["Pricing details are not documented — unclear what the free tier includes or what premium tiers cost","Usage limits are not specified — unclear if limits are per-day, per-month, or per-task","No public pricing page or calculator available","Monetization strategy is unclear — unclear if users pay for API calls, task execution, or model access","No information on how pricing scales with team size or usage"],"requires":["Multi extension installed","Optional: paid subscription for premium features"],"input_types":["subscription tier (enum: free, premium, enterprise)"],"output_types":["usage limits (JSON: api_calls_per_month, tasks_per_day, etc.)","pricing information (JSON: cost, billing_cycle, etc.)"],"categories":["automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"vscode-multi-multi__cap_2","uri":"capability://safety.moderation.configurable.approval.workflows.for.file.and.shell.operations","name":"configurable approval workflows for file and shell operations","description":"Implements a granular permission system where users define approval thresholds for file reads, file writes, shell command execution, and todo list updates. Approval levels can be set to auto-approve (no prompt), require explicit approval per operation, or block operations entirely. The approval state is persisted in profiles, enabling team-wide security policies (e.g., 'auto-approve reads, require approval for writes, block shell commands').","intents":["I want to let the agent read files and search the codebase freely, but require my approval before it modifies anything","I need to enforce a team policy where shell commands are never auto-approved to prevent accidental destructive operations","I want to audit all file modifications the agent makes — I need a log of what was approved and when"],"best_for":["teams with security or compliance requirements (e.g., financial services, healthcare)","organizations onboarding AI agents and need gradual trust escalation","developers working on production codebases who want human-in-the-loop verification"],"limitations":["Approval prompts are synchronous — they block task execution until the user responds, negating the 'background execution' benefit","No audit logging built-in — approval decisions are not persisted to a log file or external system","Approval granularity is coarse (file reads/writes/shell) — no per-file or per-command whitelisting","No time-based approval expiry — once a user approves an operation type, it remains approved for the entire session","Approval UI/UX not documented — unclear if approvals are modal dialogs, sidebar notifications, or command palette prompts"],"requires":["VS Code or JetBrains IDE with Multi extension installed","User interaction capability (keyboard/mouse for approval prompts)"],"input_types":["operation type (string: 'file-read', 'file-write', 'shell-exec', 'todo-update')","approval level (enum: 'auto', 'prompt', 'block')","operation details (file path, command, etc.)"],"output_types":["approval decision (boolean: approved/denied)","approval timestamp (ISO 8601)","approval reason (string, if denied)"],"categories":["safety-moderation","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"vscode-multi-multi__cap_3","uri":"capability://search.retrieval.codebase.wide.semantic.search.and.context.retrieval","name":"codebase-wide semantic search and context retrieval","description":"Indexes the project codebase and enables the agent to search for files, functions, and patterns using semantic queries (not just regex). The search results are automatically injected into the agent's context window, allowing it to understand dependencies, locate relevant code, and generate contextually-aware implementations. Search can be triggered manually by the user or automatically by the agent during task planning.","intents":["I want the agent to find all usages of a deprecated function and generate a migration plan","I need the agent to understand the project's architecture by searching for key patterns (e.g., all service classes, all API routes)","I want to search for similar code patterns to ensure my new implementation is consistent with the codebase style"],"best_for":["developers working on large, unfamiliar codebases who need rapid context gathering","teams refactoring legacy code and need to identify all affected areas","developers building on top of existing frameworks and need to understand the codebase structure"],"limitations":["Search index is not documented — unclear if it's built on tree-sitter, AST parsing, or simple text indexing","Semantic search quality depends on LLM embeddings — may miss relevant code if the query is phrased differently than the code","No search result ranking or relevance scoring — unclear how results are ordered","Search scope is project-wide — no filtering by file type, directory, or module","Index freshness not documented — unclear if the index updates in real-time or requires manual refresh"],"requires":["Project files accessible on disk","Sufficient memory to index the codebase (large projects may require >1GB)"],"input_types":["search query (natural language string or regex pattern)","file type filter (optional, string)","directory scope (optional, path)"],"output_types":["search results (array of file paths and line numbers)","code snippets (text)","relevance scores (numeric, if available)"],"categories":["search-retrieval","memory-knowledge"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"vscode-multi-multi__cap_4","uri":"capability://search.retrieval.web.page.fetching.and.documentation.integration","name":"web page fetching and documentation integration","description":"The agent can autonomously fetch web pages (API documentation, tutorials, Stack Overflow answers, etc.) and inject the content into its context window during task execution. This enables the agent to implement features using up-to-date external documentation without the developer manually copying and pasting content. Web fetching is triggered automatically when the agent detects a need for external context (e.g., 'I need to call the Stripe API').","intents":["I want the agent to implement a Stripe payment integration — it should fetch the Stripe API docs and generate code without me manually copying documentation","I need the agent to understand a new library I'm using — it should fetch the official docs and use them as context for code generation","I want the agent to research best practices for a specific pattern (e.g., React hooks) and implement accordingly"],"best_for":["developers integrating third-party APIs and services","teams adopting new libraries or frameworks and need rapid onboarding","developers working with rapidly-evolving APIs where local documentation is stale"],"limitations":["Web fetching adds latency (~1-5s per fetch) to task execution, negating some background execution benefits","No caching mechanism documented — each task may re-fetch the same documentation","HTML parsing quality not documented — may fail on complex or JavaScript-heavy pages","No authentication support — cannot fetch documentation behind paywalls or login walls","Context window limits mean large documentation pages may be truncated","No filtering for relevant sections — entire pages are fetched, wasting context tokens"],"requires":["Network access to the internet","Target URLs must be publicly accessible (no authentication)"],"input_types":["URL (string)","optional: query or section to extract (string)"],"output_types":["page content (HTML or markdown)","extracted text (string)","fetch status (success/failure)"],"categories":["search-retrieval","memory-knowledge"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"vscode-multi-multi__cap_5","uri":"capability://automation.workflow.shell.command.execution.with.background.task.management","name":"shell command execution with background task management","description":"Executes arbitrary shell commands (bash, zsh, PowerShell, etc.) in the background while the developer continues editing. Commands run asynchronously and their output is captured and injected back into the agent's context for further processing. The agent can chain multiple commands, parse their output, and make decisions based on exit codes. Background execution prevents blocking the IDE, enabling parallel development workflows.","intents":["I want the agent to run tests, linting, and build commands in the background while I continue coding","I need the agent to execute deployment scripts and monitor their progress without blocking my editor","I want the agent to run database migrations and report results back to me asynchronously"],"best_for":["developers using CI/CD-heavy workflows where build/test cycles are frequent","teams with long-running tasks (tests, builds, deployments) that would block manual execution","developers building automation scripts that need to run in parallel with coding"],"limitations":["Shell commands are unrestricted once approved — no sandboxing, no command whitelisting, no resource limits","No timeout mechanism documented — long-running commands may hang indefinitely","Output capture is unbounded — large command outputs (>100MB) may exhaust memory","No environment variable isolation — commands inherit the IDE process environment, which may be incomplete","Cross-platform compatibility not documented — shell syntax differs between bash, zsh, PowerShell","No built-in error recovery — if a command fails, the agent must be programmed to handle the failure"],"requires":["Shell interpreter available on the system (bash, zsh, PowerShell, etc.)","Write permissions on the project directory (for commands that create files)","Network access (for commands that make HTTP requests, git operations, etc.)"],"input_types":["shell command (string)","working directory (path)","environment variables (key-value pairs)"],"output_types":["command output (stdout, text)","error output (stderr, text)","exit code (integer)","execution time (milliseconds)"],"categories":["automation-workflow","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"vscode-multi-multi__cap_6","uri":"capability://code.generation.editing.file.read.write.and.edit.operations.with.diff.based.updates","name":"file read, write, and edit operations with diff-based updates","description":"The agent can autonomously read files from the project, write new files, and edit existing files using diff-based updates (rather than full file replacement). Diff-based edits preserve file structure and minimize changes, reducing merge conflicts and making changes easier to review. File operations are subject to the approval workflow and can be logged for audit purposes.","intents":["I want the agent to generate a new module and add it to the project without me manually creating files","I need the agent to refactor a function in-place, preserving comments and formatting","I want to review all file changes the agent makes before they're committed"],"best_for":["developers using code review workflows where all changes must be audited","teams working on large files where full-file replacement would cause merge conflicts","developers who want to preserve file structure and comments during refactoring"],"limitations":["Diff-based editing requires understanding the file structure — may fail on malformed or unusual file formats","No conflict detection — if multiple agents or developers edit the same file simultaneously, conflicts are not detected","File encoding not documented — unclear if the agent handles UTF-8, ASCII, or other encodings","Binary file support not documented — likely limited to text files","No version control integration — file changes are not automatically committed or staged"],"requires":["Write permissions on the project directory","File must be readable (for edit operations)"],"input_types":["file path (string)","file content (string, for write operations)","diff patch (unified diff format, for edit operations)"],"output_types":["file content (string, for read operations)","write status (success/failure)","edit status (success/failure, with conflict details if applicable)"],"categories":["code-generation-editing","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"vscode-multi-multi__cap_7","uri":"capability://automation.workflow.task.state.forking.and.restoration.with.git.worktrees","name":"task state forking and restoration with git worktrees","description":"The agent can fork the current task execution into an isolated git worktree (a separate working directory linked to the same repository), explore alternative solutions in parallel, and restore previous states if a branch fails. This enables risk-free experimentation without affecting the main codebase. Worktree isolation is transparent to the developer — the agent manages branch creation, switching, and cleanup automatically.","intents":["I want the agent to explore two different refactoring approaches in parallel and show me the results side-by-side","I need the agent to try a risky change (e.g., major dependency upgrade) in an isolated branch and roll back if it breaks tests","I want to compare the performance of two different implementations without manually creating branches"],"best_for":["developers working on complex refactorings where multiple approaches should be evaluated","teams using trunk-based development and need safe experimentation","developers who want to avoid manual branch management overhead"],"limitations":["Worktree creation adds ~500ms-2s overhead per fork (git operations)","Worktree cleanup is not documented — orphaned worktrees may accumulate and waste disk space","No automatic comparison or diff generation between branches — user must manually review results","Worktree isolation is file-system level only — shared state (databases, caches) may cause conflicts","Git history is not isolated — commits in worktrees are visible in the main repository","Large repositories may have significant overhead when creating multiple worktrees"],"requires":["Git repository initialized in the project","Sufficient disk space for worktree clones (typically 2-5x the project size)"],"input_types":["branch name (string)","base branch (string, defaults to current branch)"],"output_types":["worktree path (string)","branch reference (git ref)","worktree status (active/inactive)"],"categories":["automation-workflow","planning-reasoning"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"vscode-multi-multi__cap_8","uri":"capability://code.generation.editing.stack.aware.code.generation.with.project.context.injection","name":"stack-aware code generation with project context injection","description":"The agent claims to be 'fully aware of your stack, flow, and deadlines' by analyzing the project structure, detecting frameworks and libraries in use, and injecting this context into code generation prompts. This enables the agent to generate code that matches the project's style, patterns, and conventions without explicit instruction. Stack detection likely includes language detection, framework identification (React, Django, etc.), and dependency analysis from package managers.","intents":["I want the agent to generate a new React component that matches my project's existing component patterns and styling","I need the agent to implement a feature using the same architectural patterns as the rest of the codebase","I want the agent to generate code that respects my project's linting rules and code style"],"best_for":["developers working on projects with strong architectural patterns or conventions","teams with diverse tech stacks who need the agent to adapt to each project","developers who want generated code to be immediately usable without refactoring"],"limitations":["Stack detection mechanism is not documented — unclear how frameworks and patterns are identified","No explicit configuration for stack preferences — detection is automatic and may be inaccurate","Pattern detection is limited to common frameworks — custom or proprietary patterns may not be recognized","No feedback mechanism to correct misdetected stacks","Deadline awareness is mentioned but not explained — unclear how deadlines are factored into code generation"],"requires":["Project files accessible on disk","Package manager files (package.json, requirements.txt, go.mod, etc.) for dependency detection"],"input_types":["project directory (path)","optional: explicit stack configuration (JSON)"],"output_types":["detected stack metadata (JSON: languages, frameworks, libraries)","generated code (text, matching detected patterns)"],"categories":["code-generation-editing","memory-knowledge"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"vscode-multi-multi__cap_9","uri":"capability://automation.workflow.todo.list.management.and.task.tracking","name":"todo list management and task tracking","description":"The agent can create, update, and track todo items as it executes tasks, maintaining a persistent task list that survives across sessions. Todos can be marked as complete, and the agent can reference them during planning to understand task dependencies and progress. Todo updates are subject to the approval workflow, allowing users to control what tasks the agent creates.","intents":["I want the agent to break down a large feature into subtasks and track progress as it implements each one","I need a persistent record of what the agent has done and what remains to be done","I want to manually add todos that the agent should prioritize in future executions"],"best_for":["developers working on large, multi-step projects where task tracking is valuable","teams using todo-driven development or task-based workflows","developers who want visibility into the agent's task decomposition and progress"],"limitations":["Todo storage mechanism is not documented — unclear if todos are stored in a file, database, or extension state","No integration with external task management tools (Jira, GitHub Issues, Asana, etc.)","Todo format is not specified — unclear if todos are plain text, markdown, or structured data","No priority or dependency tracking between todos","No notification system for completed todos or blocked tasks"],"requires":["VS Code or JetBrains IDE with Multi extension installed"],"input_types":["todo text (string)","optional: priority (enum: low/medium/high)","optional: due date (ISO 8601)"],"output_types":["todo list (array of todo objects)","todo status (completed/pending/blocked)"],"categories":["automation-workflow","planning-reasoning"],"confidence":0.5,"matches":0,"success_rate":0}],"trust":{"score":38,"verified":false,"data_access_risk":"high","permissions":["API keys for at least one supported provider (OpenAI, Anthropic, Google, etc.)","VS Code 1.80+ or compatible JetBrains IDE","Network access to provider APIs (or local Ollama instance for offline use)","Git repository initialized in the project (for worktree branching)","Write permissions on the project directory","Shell access (bash, zsh, PowerShell, etc.)","Sufficient disk space for worktree clones if using branch isolation","VS Code 1.80+ OR JetBrains IDE (version not specified) OR compatible alternative editor","Multi extension installed for the target IDE","Multi extension installed"],"failure_modes":["Profile switching requires manual selection — no automatic provider selection based on task type or cost","API key storage mechanism not documented — unclear if keys are encrypted or stored in plaintext","No built-in rate limiting or quota management across providers","Model-specific capabilities (e.g., vision, function calling) not abstracted — users must know provider-specific APIs","Task decomposition quality depends on LLM reasoning — complex multi-step refactorings may fail if the agent misunderstands dependencies","Worktree isolation adds ~500ms-2s overhead per branch fork/restore cycle (git operations)","No built-in rollback mechanism if file writes corrupt the codebase — approval workflows are the only safeguard","Context window limitations mean large codebases (>50k lines) may not fit in a single task context","Shell command execution is unrestricted once approved — no sandboxing or command whitelisting","IDE-specific features may not be available across all platforms — unclear which capabilities are limited to specific IDEs","builder identity is not verified yet","no observed match outcomes yet"],"rank_breakdown":{"adoption":0.39,"quality":0.34,"ecosystem":0.35000000000000003,"match_graph":0.25,"freshness":0.75,"weights":{"adoption":0.25,"quality":0.25,"ecosystem":0.1,"match_graph":0.28,"freshness":0.12}},"observed_outcomes":{"matches":0,"success_rate":0,"avg_confidence":0,"top_intents":[],"last_matched_at":null},"maintenance":{"status":"active","updated_at":"2026-05-24T12:16:34.803Z","last_scraped_at":"2026-05-03T15:20:33.198Z","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=multi-frontier-ai-coding-agent","compare_url":"https://unfragile.ai/compare?artifact=multi-frontier-ai-coding-agent"}},"signature":"BD7qq//iUnsevtXvN3WQqqZQ+KWLPVWmAvhXoiB9WJkbv9EgF1nojJXZtkWnDc9SjkmrJFcACKMaiqRakwOtDQ==","signedAt":"2026-06-20T20:45:41.203Z","signedBy":"unfragile.ai","version":1},"_links":{"self":"https://unfragile.ai/api/v1/passport/multi-frontier-ai-coding-agent","artifact":"https://unfragile.ai/multi-frontier-ai-coding-agent","verify":"https://unfragile.ai/api/v1/verify?slug=multi-frontier-ai-coding-agent","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"}}