{"passport":{"unfragile":{"@version":"1.0","version":"2026-05","artifact":{"id":"vscode-kilocode-kilo-code","slug":"kilo-code-ai-coding-agent-copilot-and-autocomplete","name":"Kilo Code: AI Coding Agent, Copilot, and Autocomplete","type":"agent","url":"https://marketplace.visualstudio.com/items?itemName=kilocode.Kilo-Code","page_url":"https://unfragile.ai/kilo-code-ai-coding-agent-copilot-and-autocomplete","categories":["code-editors"],"tags":["agent","ai","autonomous","chatgpt","claude","coding","dev","keybindings","kilo","Kilo Code","kilocode","llama","mcp","openrouter","sonnet","terminal"],"pricing":{"model":"freemium","free":true,"starting_price":null},"status":"active","verified":false},"capabilities":[{"id":"vscode-kilocode-kilo-code__cap_0","uri":"capability://code.generation.editing.natural.language.to.code.generation.with.self.verification","name":"natural-language-to-code generation with self-verification","description":"Converts natural language descriptions into executable code by routing prompts through a configurable AI model (Claude, Gemini, GPT-4, or 500+ alternatives via OpenRouter). Implements a self-verification loop where the generated code is re-evaluated by the same or different model to check correctness before insertion into the editor. Supports multi-turn refinement where users can iteratively request changes to generated code within the same context window.","intents":["I want to describe what a function should do in plain English and have it written automatically","I need to generate boilerplate code quickly without typing it manually","I want the AI to verify its own code output before showing it to me"],"best_for":["solo developers building prototypes quickly","teams reducing boilerplate-writing overhead","developers working in unfamiliar languages or frameworks"],"limitations":["Self-verification mechanism implementation is undocumented — unclear if it uses separate model calls, token-based scoring, or syntax validation","No built-in version control integration — generated code is not automatically committed or tracked","Context window limited by selected model — large codebases may exceed token limits","No guarantee of correctness — verification is heuristic-based, not formal proof"],"requires":["VS Code 1.80+ (inferred from extension architecture)","API key for at least one supported model provider (OpenAI, Anthropic, Google, or OpenRouter account)","Network connectivity for remote model inference"],"input_types":["natural language text description","current file context (auto-included)","optional code snippet for context"],"output_types":["generated code (inserted into editor)","verification feedback (displayed in UI)"],"categories":["code-generation-editing","planning-reasoning"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"vscode-kilocode-kilo-code__cap_1","uri":"capability://code.generation.editing.inline.real.time.code.autocomplete.with.streaming","name":"inline real-time code autocomplete with streaming","description":"Provides context-aware code completion suggestions as the user types, triggered automatically or on-demand via keybinding. Integrates with VS Code's InlineCompletionItemProvider API to display suggestions inline without interrupting editor flow. Streams completions from selected AI model (Claude, GPT-4, Gemini, or 500+ alternatives) with latency optimized for real-time interaction. Respects user's current file context, language syntax, and project structure to generate relevant suggestions.","intents":["I want code suggestions to appear as I type, like GitHub Copilot","I need faster autocomplete that doesn't interrupt my workflow","I want to use my preferred AI model for completions instead of being locked to one provider"],"best_for":["developers writing code in supported languages (JavaScript, Python, TypeScript, Go, Rust, etc.)","teams standardizing on a specific AI model for consistency","developers with low-latency network connections to model providers"],"limitations":["Streaming latency depends on model provider and network — no local inference option documented","Inline completion may conflict with other completion providers (GitHub Copilot, Codeium) if both are enabled","No language-specific tuning documented — same model used for all languages","Completion quality varies by model — smaller models (Llama 2) may produce lower-quality suggestions than Claude or GPT-4"],"requires":["VS Code 1.80+ with InlineCompletionItemProvider support","API key for selected model provider","Network connectivity with <500ms latency for acceptable UX"],"input_types":["current file content","cursor position","language identifier","project context (inferred)"],"output_types":["inline completion suggestion text","completion metadata (confidence, source model)"],"categories":["code-generation-editing"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"vscode-kilocode-kilo-code__cap_10","uri":"capability://tool.use.integration.transparent.pricing.with.provider.rate.matching","name":"transparent pricing with provider rate matching","description":"Implements transparent pricing model where users are charged at provider rates (OpenAI, Anthropic, Google) without markup. Billing is aggregated through OpenRouter or direct provider APIs, and users see per-token costs for each request. No subscription required — users pay only for tokens consumed. Pricing is displayed in UI before requests are sent, enabling users to make informed decisions about model selection.","intents":["I want to understand the cost of using different AI models","I need to control my AI spending by choosing cheaper models","I want transparent pricing without hidden fees or markups"],"best_for":["cost-conscious developers evaluating AI tools","organizations with strict budgets for AI services","developers experimenting with multiple models"],"limitations":["Pricing display is undocumented — unclear if costs are shown before or after request","No spending limits or quotas documented — users may accidentally incur high costs","Pricing varies by model and provider — users must understand per-token costs","No cost optimization recommendations documented — users must manually choose cheaper models"],"requires":["API key for model provider or OpenRouter account","Understanding of per-token pricing for selected models"],"input_types":["model selection","request parameters (tokens, model)"],"output_types":["cost estimate","actual cost after request"],"categories":["tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"vscode-kilocode-kilo-code__cap_11","uri":"capability://tool.use.integration.api.key.management.with.optional.authentication","name":"api key management with optional authentication","description":"Manages API keys for model providers (OpenAI, Anthropic, Google, OpenRouter) with optional user account creation. Users can provide their own API keys (stored locally in VS Code settings) or create a Kilo Code account to access shared API keys. Account creation is optional — users can use the extension without creating an account if they provide their own API keys. Key storage mechanism is undocumented but likely uses VS Code's SecretStorage API for encryption.","intents":["I want to use my own API keys without creating an account","I want Kilo Code to manage API keys for me","I need to share API key management across my team"],"best_for":["developers with existing API keys from model providers","organizations managing API keys centrally","developers prioritizing privacy by using their own keys"],"limitations":["Key storage mechanism is undocumented — unclear if keys are encrypted or stored in plaintext","No key rotation or expiration management documented","Team key sharing is undocumented — unclear if accounts support team management","No audit logging documented — unclear if key usage is logged"],"requires":["VS Code 1.80+","API key from model provider (OpenAI, Anthropic, Google, or OpenRouter) OR Kilo Code account"],"input_types":["API key or account credentials"],"output_types":["authenticated requests to model providers"],"categories":["tool-use-integration","safety-moderation"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"vscode-kilocode-kilo-code__cap_12","uri":"capability://code.generation.editing.multi.language.code.generation.and.completion","name":"multi-language code generation and completion","description":"Supports code generation and completion across 40+ programming languages (JavaScript, Python, TypeScript, Go, Rust, Java, C++, C#, PHP, Ruby, Kotlin, Swift, etc.). Language detection is automatic based on file extension, and the AI model is prompted with language-specific context (syntax, idioms, frameworks). Completion suggestions respect language-specific conventions (e.g., snake_case for Python, camelCase for JavaScript). No language-specific tuning is documented — same model is used for all languages.","intents":["I want code generation to work across multiple languages in my polyglot project","I need completions that respect my language's syntax and conventions","I want to use the same tool for JavaScript, Python, and Go without reconfiguration"],"best_for":["developers working in polyglot projects","teams using multiple languages","developers learning new languages"],"limitations":["No language-specific model tuning documented — same model used for all languages","Completion quality varies by language — popular languages (Python, JavaScript) may have better suggestions than niche languages","No framework-specific context documented — suggestions may not respect framework conventions (e.g., React vs Vue)","Language detection relies on file extension — may fail for ambiguous files"],"requires":["VS Code 1.80+","API key for selected model provider","File with recognized language extension"],"input_types":["code in any supported language","natural language description"],"output_types":["generated or completed code in same language"],"categories":["code-generation-editing"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"vscode-kilocode-kilo-code__cap_2","uri":"capability://code.generation.editing.automated.code.refactoring.with.scope.control","name":"automated code refactoring with scope control","description":"Applies AI-driven refactoring transformations to selected code, entire files, or project-wide patterns. User specifies refactoring intent (e.g., 'extract method', 'rename variables for clarity', 'convert to async/await') in natural language, and the selected model generates refactored code while preserving functionality. Integrates with VS Code's edit API to apply changes atomically, with undo support. Scope (selection, file, or project) is user-controlled via command palette or sidebar UI.","intents":["I want to refactor a function to be more readable without manually rewriting it","I need to convert legacy code patterns to modern syntax across multiple files","I want to extract repeated code into reusable functions automatically"],"best_for":["teams modernizing legacy codebases","developers improving code quality without manual refactoring","projects with consistent coding standards that can be described in natural language"],"limitations":["Refactoring scope (file vs. project) is not clearly documented — unclear if project-wide refactoring is supported or limited to single files","No syntax validation before applying changes — generated code may have syntax errors if model hallucinates","Refactoring intent must be specified in natural language — no structured refactoring rules (e.g., 'extract method if function > 50 lines')","No rollback mechanism beyond VS Code's undo — if refactoring breaks tests, user must manually revert"],"requires":["VS Code 1.80+","API key for selected model provider","Code selection or file open in editor"],"input_types":["selected code or entire file","natural language refactoring intent","language identifier"],"output_types":["refactored code","diff preview (inferred)"],"categories":["code-generation-editing"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"vscode-kilocode-kilo-code__cap_3","uri":"capability://automation.workflow.terminal.command.generation.and.execution","name":"terminal command generation and execution","description":"Generates shell commands from natural language descriptions (e.g., 'find all TypeScript files modified in the last week') and executes them in the user's local terminal with explicit user confirmation. Integrates with VS Code's terminal API to run commands in the integrated terminal, capturing output and displaying results in the editor or terminal panel. Supports bash, zsh, PowerShell, and other shells based on user's environment.","intents":["I want to run a complex shell command without remembering the exact syntax","I need to automate repetitive terminal tasks like file cleanup or git operations","I want to execute build or deployment commands generated from natural language"],"best_for":["developers automating DevOps or build tasks","teams standardizing command patterns across environments","developers unfamiliar with shell syntax"],"limitations":["Execution context is user's full shell permissions — no sandboxing, so generated commands can access/modify any file the user can access","No command validation before execution — user must review generated commands to prevent accidental data loss","Shell compatibility varies — generated commands may fail on Windows PowerShell if written for bash","Output capture is limited to terminal stdout/stderr — no structured data extraction from command output"],"requires":["VS Code 1.80+ with terminal API support","API key for selected model provider","Local shell environment (bash, zsh, PowerShell, etc.)"],"input_types":["natural language command description","optional context (current directory, file paths)"],"output_types":["generated shell command","command execution output (stdout/stderr)"],"categories":["automation-workflow","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"vscode-kilocode-kilo-code__cap_4","uri":"capability://automation.workflow.browser.automation.with.natural.language.control","name":"browser automation with natural language control","description":"Automates browser interactions (clicking, typing, navigation, form submission) based on natural language instructions. Mechanism is undocumented but likely uses Playwright or Puppeteer to control a browser instance. User describes desired browser action (e.g., 'fill in the login form and submit'), and the AI generates automation code or directly controls the browser. Supports multi-step workflows (e.g., navigate to URL, fill form, submit, verify result).","intents":["I want to automate repetitive web testing tasks without writing Selenium code","I need to scrape data from a website by describing the extraction logic in natural language","I want to automate form filling or data entry workflows"],"best_for":["QA teams automating web testing workflows","developers building web scraping tools","teams automating data entry or form submission tasks"],"limitations":["Browser automation mechanism is undocumented — unclear if it uses Playwright, Puppeteer, or custom implementation","No support for JavaScript-heavy SPAs documented — may fail on dynamic content","Scope is unclear — can it control any browser tab or only a dedicated automation browser?","No error recovery documented — if a step fails, unclear if automation retries or halts","CAPTCHA and anti-bot protection will block automation — no bypass mechanism documented"],"requires":["VS Code 1.80+","API key for selected model provider","Browser installed (Chrome, Firefox, or Chromium-based)"],"input_types":["natural language browser action description","optional URL or page context"],"output_types":["automation code (Playwright/Puppeteer script) or direct browser control","execution result (success/failure, captured data)"],"categories":["automation-workflow","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"vscode-kilocode-kilo-code__cap_5","uri":"capability://tool.use.integration.multi.model.routing.with.provider.abstraction","name":"multi-model routing with provider abstraction","description":"Abstracts away model provider differences by routing requests to 500+ AI models (Claude, GPT-4, Gemini, Llama, Mistral, etc.) via OpenRouter API. Users select a model via UI dropdown or configuration, and all requests (code generation, completion, refactoring) are routed to that model without extension changes. Supports switching models mid-session and per-task model selection (e.g., use Claude for planning, GPT-4 for coding). Handles API key management, rate limiting, and billing aggregation via OpenRouter.","intents":["I want to use Claude for code generation but GPT-4 for refactoring","I need to switch AI models without reconfiguring the extension","I want to experiment with different models to find the best one for my workflow"],"best_for":["developers evaluating multiple AI models","teams standardizing on a specific model for consistency","organizations with existing OpenRouter accounts"],"limitations":["OpenRouter dependency — if OpenRouter is down, all model access is unavailable","Model availability depends on OpenRouter's catalog — not all models may be available at all times","Pricing varies by model — users must understand per-token costs for each model","No local model inference documented — all inference is remote, requiring network connectivity","API key management is undocumented — unclear if keys are stored locally or in cloud"],"requires":["OpenRouter account or API key for direct model provider (OpenAI, Anthropic, Google)","Network connectivity to OpenRouter or model provider","VS Code 1.80+"],"input_types":["model selection (dropdown or config)","API key or OpenRouter token"],"output_types":["model inference results","usage statistics (tokens, cost)"],"categories":["tool-use-integration","memory-knowledge"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"vscode-kilocode-kilo-code__cap_6","uri":"capability://tool.use.integration.mcp.server.discovery.and.integration","name":"mcp server discovery and integration","description":"Discovers and integrates Model Context Protocol (MCP) servers to extend agent capabilities beyond built-in features. Users can install MCP servers from a marketplace or configure custom servers, and the agent automatically discovers available tools (e.g., file system access, database queries, API calls). Requests are routed through MCP protocol to appropriate servers, enabling the agent to perform complex multi-step tasks (e.g., 'query the database and generate a report'). Integration is transparent — users describe intent in natural language, and the agent selects appropriate MCP tools.","intents":["I want to extend the agent with custom tools like database access or API integrations","I need the agent to query my company's internal systems to generate code","I want to use MCP servers to give the agent access to specialized capabilities"],"best_for":["teams building custom agent workflows with specialized tools","organizations with internal APIs or databases that need agent access","developers extending Kilo Code with domain-specific capabilities"],"limitations":["MCP server discovery mechanism is undocumented — unclear how servers are registered or discovered","Tool selection is automatic — no user control over which tools are used for a given task","MCP server reliability depends on third-party implementations — no guarantee of correctness or performance","Security model is undocumented — unclear if MCP servers have access controls or sandboxing"],"requires":["VS Code 1.80+","MCP server installed and configured (local or remote)","API key for selected model provider"],"input_types":["natural language task description","MCP server configuration"],"output_types":["MCP tool execution results","agent response based on tool output"],"categories":["tool-use-integration","memory-knowledge"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"vscode-kilocode-kilo-code__cap_7","uri":"capability://planning.reasoning.custom.agent.mode.creation.and.configuration","name":"custom agent mode creation and configuration","description":"Enables users to create custom agent modes (specialized workflows) tailored to specific tasks. Pre-built modes include 'Architect' (planning), 'Coder' (code generation), and 'Debugger' (debugging). Users define custom modes by specifying system prompts, tool availability, model preferences, and execution constraints. Modes are invoked via command palette or sidebar, and the agent operates within the mode's constraints (e.g., 'Architect' mode may prioritize planning over code generation). Mode configuration is stored locally in VS Code settings.","intents":["I want to create a specialized agent mode for my team's coding standards","I need different agent behaviors for different tasks (planning vs. coding vs. debugging)","I want to enforce specific constraints or tool usage patterns in agent workflows"],"best_for":["teams standardizing agent behavior across developers","organizations with domain-specific coding practices","developers building custom workflows for specialized tasks"],"limitations":["Mode creation mechanism is undocumented — unclear if users write JSON config, Python scripts, or use UI builder","Mode constraints are not formally enforced — agent may ignore mode constraints if model decides to","No mode versioning or sharing mechanism documented — modes are local to user's VS Code instance","Mode performance impact is undocumented — complex modes may add latency"],"requires":["VS Code 1.80+","API key for selected model provider","Understanding of mode configuration format (undocumented)"],"input_types":["mode configuration (system prompt, tools, constraints)","natural language task description"],"output_types":["agent response constrained by mode"],"categories":["planning-reasoning","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"vscode-kilocode-kilo-code__cap_8","uri":"capability://code.generation.editing.context.aware.code.completion.with.project.understanding","name":"context-aware code completion with project understanding","description":"Enhances code completion by analyzing project structure, imports, and dependencies to provide contextually relevant suggestions. Completion engine infers user's intent from cursor position, recent edits, and file structure (e.g., if user is in a React component, suggestions favor React patterns). Integrates with language servers (LSP) to understand syntax and type information, enabling more accurate suggestions than simple pattern matching. Context is sent to selected AI model along with completion request.","intents":["I want code suggestions that understand my project's architecture and patterns","I need completions that respect my project's dependencies and imports","I want suggestions that match my team's coding style"],"best_for":["developers working in large codebases with consistent patterns","teams with standardized project structures","developers using TypeScript or other strongly-typed languages"],"limitations":["Context window is limited by model — large projects may exceed token limits","Project understanding is heuristic-based — may fail on unconventional project structures","No explicit style learning — suggestions are based on model's training, not project-specific patterns","LSP integration is undocumented — unclear which languages are supported"],"requires":["VS Code 1.80+","API key for selected model provider","Language server for language-specific context (optional but recommended)"],"input_types":["current file content","project structure (inferred)","cursor position","recent edits"],"output_types":["context-aware completion suggestions"],"categories":["code-generation-editing","memory-knowledge"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"vscode-kilocode-kilo-code__cap_9","uri":"capability://code.generation.editing.debugging.assistance.with.error.analysis","name":"debugging assistance with error analysis","description":"Analyzes runtime errors, stack traces, and test failures to suggest fixes. User selects error output or stack trace, and the 'Debugger' mode analyzes the error using the selected AI model to identify root cause and suggest code changes. Integration with VS Code's debug adapter protocol (DAP) enables breakpoint inspection and variable analysis. Suggestions include code patches, configuration changes, or debugging strategies.","intents":["I want the AI to explain what's causing this error and suggest a fix","I need help debugging a complex stack trace","I want to understand why my test is failing and how to fix it"],"best_for":["developers debugging complex issues","teams reducing time spent on error analysis","developers learning new languages or frameworks"],"limitations":["Error analysis is heuristic-based — may misdiagnose root cause if error message is unclear","DAP integration is undocumented — unclear if breakpoint inspection is supported","No integration with test runners documented — test failure analysis may be limited","Suggested fixes may not address root cause — user must validate suggestions"],"requires":["VS Code 1.80+","API key for selected model provider","Error output or stack trace"],"input_types":["error message or stack trace","relevant code context","test output (optional)"],"output_types":["error analysis","suggested fixes","debugging strategies"],"categories":["code-generation-editing","planning-reasoning"],"confidence":0.5,"matches":0,"success_rate":0}],"trust":{"score":52,"verified":false,"data_access_risk":"high","permissions":["VS Code 1.80+ (inferred from extension architecture)","API key for at least one supported model provider (OpenAI, Anthropic, Google, or OpenRouter account)","Network connectivity for remote model inference","VS Code 1.80+ with InlineCompletionItemProvider support","API key for selected model provider","Network connectivity with <500ms latency for acceptable UX","API key for model provider or OpenRouter account","Understanding of per-token pricing for selected models","VS Code 1.80+","API key from model provider (OpenAI, Anthropic, Google, or OpenRouter) OR Kilo Code account"],"failure_modes":["Self-verification mechanism implementation is undocumented — unclear if it uses separate model calls, token-based scoring, or syntax validation","No built-in version control integration — generated code is not automatically committed or tracked","Context window limited by selected model — large codebases may exceed token limits","No guarantee of correctness — verification is heuristic-based, not formal proof","Streaming latency depends on model provider and network — no local inference option documented","Inline completion may conflict with other completion providers (GitHub Copilot, Codeium) if both are enabled","No language-specific tuning documented — same model used for all languages","Completion quality varies by model — smaller models (Llama 2) may produce lower-quality suggestions than Claude or GPT-4","Pricing display is undocumented — unclear if costs are shown before or after request","No spending limits or quotas documented — users may accidentally incur high costs","builder identity is not verified yet","no observed match outcomes yet"],"rank_breakdown":{"adoption":0.8,"quality":0.5,"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":"2026-05-03T15:20:29.937Z","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=kilo-code-ai-coding-agent-copilot-and-autocomplete","compare_url":"https://unfragile.ai/compare?artifact=kilo-code-ai-coding-agent-copilot-and-autocomplete"}},"signature":"uYhWCX4G5ejWxQ7f04IqvU8OFF7VkbcQhY52TmPigcZbLlpQeyaGeB1LAYOER9pFXbMOP5mzrBo5CR2wU1QUBQ==","signedAt":"2026-06-21T15:28:07.418Z","signedBy":"unfragile.ai","version":1},"_links":{"self":"https://unfragile.ai/api/v1/passport/kilo-code-ai-coding-agent-copilot-and-autocomplete","artifact":"https://unfragile.ai/kilo-code-ai-coding-agent-copilot-and-autocomplete","verify":"https://unfragile.ai/api/v1/verify?slug=kilo-code-ai-coding-agent-copilot-and-autocomplete","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"}}