{"passport":{"unfragile":{"@version":"1.0","version":"2026-05","artifact":{"id":"tool_askcodi","slug":"askcodi","name":"AskCodi","type":"product","url":"https://www.askcodi.com","page_url":"https://unfragile.ai/askcodi","categories":["code-editors"],"tags":[],"pricing":{"model":"freemium","free":true,"starting_price":null},"status":"active","verified":false},"capabilities":[{"id":"tool_askcodi__cap_0","uri":"capability://code.generation.editing.real.time.inline.code.completion.across.50.languages","name":"real-time inline code completion across 50+ languages","description":"Generates contextual code suggestions as developers type within the IDE editor, leveraging language-specific syntax trees and local buffer context to predict next tokens. AskCodi integrates directly into VS Code, IntelliJ, and PyCharm via native extension APIs, analyzing the current file's AST and surrounding code context to produce suggestions without requiring explicit prompts. The system maintains language-specific models for 50+ languages including mainstream (Python, JavaScript, Java) and niche (Rust, Go, Kotlin) languages, allowing it to handle diverse syntax patterns and idioms.","intents":["I want code completions to appear automatically as I type without switching windows","I need suggestions that understand my project's coding style and patterns","I'm working in a less common language and want IDE support beyond what's available","I want to reduce boilerplate typing for repetitive code patterns"],"best_for":["Junior developers learning multiple programming languages","Small teams with polyglot codebases who can't afford per-language tooling","Developers using niche languages (Rust, Go, Kotlin) where Copilot support is weaker"],"limitations":["Code quality degrades on complex logic patterns and architectural decisions — requires manual refinement more often than Copilot","Smaller training dataset means weaker understanding of proprietary frameworks and bleeding-edge library syntax","Completion latency increases with file size and complexity due to local context analysis","No cross-file codebase indexing — suggestions based only on current file and immediate context"],"requires":["VS Code 1.50+ OR JetBrains IDE (IntelliJ 2020.1+, PyCharm 2020.1+)","AskCodi extension installed from marketplace","API key from AskCodi account (free tier available)","Active internet connection for model inference"],"input_types":["code (current file buffer)","cursor position (line and column)","file type/language identifier","surrounding code context (preceding lines)"],"output_types":["code snippet (single or multi-line)","completion text","confidence score (implicit via UI presentation)"],"categories":["code-generation-editing","ide-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_askcodi__cap_1","uri":"capability://code.generation.editing.intelligent.code.debugging.with.error.explanation","name":"intelligent code debugging with error explanation","description":"Analyzes code errors and exceptions within the IDE, providing explanations of root causes and suggesting fixes. AskCodi integrates with IDE error reporting (red squiggles, exception logs) and uses language-specific linters and runtime error messages as input, then generates natural language explanations and code patches. The system maps error types (syntax, runtime, type mismatches) to common patterns and suggests corrections by analyzing the error context and surrounding code structure.","intents":["I see an error message and want to understand what went wrong without searching Stack Overflow","I want suggested fixes for common bugs like null pointer exceptions or type mismatches","I need to debug code in an unfamiliar language and want AI-guided explanations","I want to learn from my mistakes by understanding the root cause of errors"],"best_for":["Junior developers learning to debug unfamiliar languages","Teams working across multiple languages who need consistent error guidance","Solo developers who want faster error resolution without external documentation lookup"],"limitations":["Explanations are generic and may not capture domain-specific error contexts (e.g., framework-specific exceptions)","Suggested fixes are heuristic-based and may not address the actual root cause in complex multi-file scenarios","No integration with runtime debuggers — relies on static error analysis and exception messages only","Limited ability to trace errors across multiple files or asynchronous code paths"],"requires":["VS Code 1.50+ OR JetBrains IDE (IntelliJ 2020.1+, PyCharm 2020.1+)","AskCodi extension installed","API key from AskCodi account","IDE error detection enabled (built-in linters or language servers)"],"input_types":["error message (text)","error type/code (e.g., SyntaxError, NullPointerException)","code snippet containing the error","stack trace (if available)"],"output_types":["error explanation (natural language)","suggested code fix (code snippet)","learning resource link (optional)"],"categories":["code-generation-editing","planning-reasoning"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_askcodi__cap_2","uri":"capability://code.generation.editing.ide.native.code.refactoring.suggestions","name":"ide-native code refactoring suggestions","description":"Suggests code refactoring opportunities (variable renaming, function extraction, dead code removal, pattern improvements) by analyzing code structure and complexity metrics. AskCodi uses static analysis to identify refactoring candidates (long functions, duplicate code blocks, unused variables) and generates refactoring suggestions with preview diffs. The system integrates with IDE refactoring APIs to apply changes directly, supporting language-specific refactoring patterns (e.g., method extraction in Java, function composition in JavaScript).","intents":["I want to improve code readability and maintainability without manually identifying refactoring opportunities","I need to extract duplicated code into reusable functions","I want to simplify complex functions by breaking them into smaller, testable units","I need to clean up unused variables and dead code before committing"],"best_for":["Teams maintaining legacy codebases with technical debt","Developers learning refactoring patterns and best practices","Small teams without dedicated code review infrastructure"],"limitations":["Refactoring suggestions are based on syntactic patterns, not semantic understanding — may miss context-dependent refactoring opportunities","No awareness of business logic or architectural constraints — suggested refactorings may violate design patterns","Limited support for complex refactorings that span multiple files or require API changes","Refactoring previews may not account for all side effects (e.g., performance implications, breaking changes)"],"requires":["VS Code 1.50+ OR JetBrains IDE (IntelliJ 2020.1+, PyCharm 2020.1+)","AskCodi extension installed","API key from AskCodi account","Language server or linter support for the target language"],"input_types":["code (current file or selection)","complexity metrics (function length, cyclomatic complexity)","code patterns (duplicates, unused variables)","language/syntax type"],"output_types":["refactoring suggestion (text description)","refactored code (code snippet with diff preview)","refactoring rationale (explanation)"],"categories":["code-generation-editing","planning-reasoning"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_askcodi__cap_3","uri":"capability://code.generation.editing.natural.language.to.code.generation.from.comments","name":"natural language to code generation from comments","description":"Converts natural language comments or descriptions into executable code by parsing intent from text and generating language-appropriate implementations. Developers write comments describing desired functionality (e.g., '// sort array in descending order'), and AskCodi generates the corresponding code snippet. The system uses language-specific code generation models trained on common patterns and idioms, supporting function generation, class scaffolding, and algorithm implementations across 50+ languages.","intents":["I want to describe what I need in plain English and have code generated automatically","I need to scaffold boilerplate code (classes, functions, API handlers) from a description","I want to implement an algorithm without looking up the syntax in a new language","I need to generate test cases or mock data from a description"],"best_for":["Rapid prototyping and MVP development where speed matters more than optimization","Developers new to a language who want to focus on logic rather than syntax","Teams with non-technical stakeholders who can describe requirements in plain language"],"limitations":["Generated code often requires refinement for production use — quality degrades with complex logic","No understanding of project-specific conventions, naming patterns, or architectural constraints","Limited ability to generate code that integrates with existing codebase patterns","Generated code may not follow performance best practices or handle edge cases","Requires clear, specific comments — ambiguous descriptions produce low-quality code"],"requires":["VS Code 1.50+ OR JetBrains IDE (IntelliJ 2020.1+, PyCharm 2020.1+)","AskCodi extension installed","API key from AskCodi account","Clear, descriptive comments in the code"],"input_types":["natural language comment (text)","function signature or context (optional)","language/syntax type","surrounding code context"],"output_types":["generated code (function, class, or snippet)","multiple code variants (if applicable)","explanation of generated code"],"categories":["code-generation-editing","text-generation-language"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_askcodi__cap_4","uri":"capability://search.retrieval.multi.language.code.snippet.search.and.retrieval","name":"multi-language code snippet search and retrieval","description":"Searches a knowledge base of code snippets and patterns across 50+ languages to find relevant implementations matching a developer's query. AskCodi indexes common patterns, algorithms, and library usage examples, allowing developers to search by intent (e.g., 'sort array', 'parse JSON', 'make HTTP request') and retrieve language-specific implementations. The system uses semantic matching to find relevant snippets even when query language differs from target language, and provides context about when and how to use each pattern.","intents":["I need to find how to implement a common pattern (sorting, parsing, API calls) in a language I'm less familiar with","I want to see multiple implementations of the same algorithm across different languages","I need to understand library-specific syntax for common tasks (e.g., making HTTP requests in Python vs JavaScript)","I want to discover best practices and idiomatic patterns for a language"],"best_for":["Developers learning new languages who want to see idiomatic patterns","Polyglot teams working across multiple languages who need quick reference implementations","Developers without strong documentation familiarity who prefer learning by example"],"limitations":["Snippet knowledge base may be outdated or incomplete for bleeding-edge libraries and frameworks","No personalization based on project-specific patterns or conventions","Snippets are decontextualized — may not account for project dependencies or environment setup","Search quality depends on query clarity — vague queries produce irrelevant results","No integration with project-specific code or internal libraries"],"requires":["VS Code 1.50+ OR JetBrains IDE (IntelliJ 2020.1+, PyCharm 2020.1+)","AskCodi extension installed","API key from AskCodi account","Active internet connection to query snippet database"],"input_types":["natural language query (text)","target language (optional)","context or use case (optional)"],"output_types":["code snippet (language-specific)","multiple snippet variants","usage explanation and context","related patterns or alternatives"],"categories":["search-retrieval","code-generation-editing"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_askcodi__cap_5","uri":"capability://tool.use.integration.freemium.ide.extension.with.tiered.feature.access","name":"freemium ide extension with tiered feature access","description":"Provides a freemium business model where free tier users access core features (code completion, debugging suggestions, basic refactoring) with rate limits, while premium users unlock unlimited usage and advanced features. AskCodi manages feature access through API-level gating, tracking usage quotas per user account and enforcing limits on completion requests, debugging queries, and refactoring suggestions. The system integrates with IDE extension lifecycle to manage authentication, license validation, and feature availability without disrupting the development workflow.","intents":["I want to try an AI coding assistant without paying upfront","I need unlimited code completions and debugging for my professional work","I want to evaluate whether AskCodi is worth the subscription cost before committing","I need to manage team licensing and feature access across multiple developers"],"best_for":["Solo developers and hobbyists evaluating AI coding tools with limited budgets","Small teams wanting to pilot AI coding assistance before enterprise adoption","Organizations seeking affordable alternatives to GitHub Copilot for cost-sensitive teams"],"limitations":["Free tier has strict rate limits (e.g., 10-20 completions per day) that may frustrate active developers","Feature parity between free and premium is limited — advanced features (codebase indexing, custom models) may be premium-only","No offline mode — free tier requires active internet and API connectivity","Account-based licensing makes it difficult to share across team members or CI/CD pipelines"],"requires":["VS Code 1.50+ OR JetBrains IDE (IntelliJ 2020.1+, PyCharm 2020.1+)","AskCodi extension installed","AskCodi account (free or paid)","Active internet connection for API calls"],"input_types":["user account credentials","license/subscription status","usage metrics (API calls, completions)"],"output_types":["feature access level (free/premium)","usage quota and remaining limits","upgrade prompts and pricing information"],"categories":["tool-use-integration","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_askcodi__cap_6","uri":"capability://tool.use.integration.cross.ide.extension.ecosystem.vs.code.intellij.pycharm","name":"cross-ide extension ecosystem (vs code, intellij, pycharm)","description":"Maintains native extensions for multiple IDE platforms (VS Code, IntelliJ IDEA, PyCharm) with consistent feature parity and unified backend API. AskCodi develops language-specific IDE plugins that integrate with each platform's extension APIs (VS Code Language Server Protocol, JetBrains Plugin SDK) to provide inline suggestions, error analysis, and refactoring within each IDE's native UI. The system uses a shared backend API to ensure consistent behavior across IDEs while adapting UI/UX to each platform's conventions and capabilities.","intents":["I use VS Code for some projects and IntelliJ for others — I want the same AI assistant in both","I need PyCharm-specific support for Python development without switching to VS Code","I want consistent AI coding assistance across my team's diverse IDE preferences","I need to migrate from one IDE to another without losing AI assistant functionality"],"best_for":["Teams with heterogeneous IDE preferences (VS Code, IntelliJ, PyCharm users)","Organizations standardizing on JetBrains IDEs where Copilot support is weaker","Developers who switch between IDEs for different projects or languages"],"limitations":["Feature parity across IDEs is imperfect — some advanced features may be IDE-specific or unavailable","IDE-specific bugs and compatibility issues require separate maintenance and debugging","Performance characteristics vary by IDE (e.g., VS Code may be faster due to lighter architecture)","UI/UX inconsistencies across IDEs may confuse users switching between platforms","Requires maintaining separate codebases and release cycles for each IDE plugin"],"requires":["VS Code 1.50+ OR IntelliJ IDEA 2020.1+ OR PyCharm 2020.1+","AskCodi extension installed from respective marketplace (VS Code Marketplace, JetBrains Marketplace)","API key from AskCodi account","Active internet connection"],"input_types":["IDE type and version","extension configuration","IDE-specific context (editor state, file type)"],"output_types":["IDE-native UI elements (inline suggestions, error squiggles, refactoring dialogs)","code completions and suggestions","error explanations and fixes"],"categories":["tool-use-integration","ide-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_askcodi__cap_7","uri":"capability://planning.reasoning.language.agnostic.error.pattern.recognition","name":"language-agnostic error pattern recognition","description":"Recognizes common error patterns across 50+ programming languages and maps them to standardized explanations and fixes. AskCodi uses a language-agnostic error taxonomy (null pointer exceptions, type mismatches, syntax errors, resource leaks) and matches runtime errors and linter warnings to this taxonomy, then generates language-specific explanations and suggested fixes. The system learns from error patterns across languages to identify similar issues in different syntactic contexts (e.g., null pointer exceptions in Java, None checks in Python, nil checks in Go).","intents":["I'm working in a language I don't know well and need help understanding an error message","I want to understand the root cause of an error without searching language-specific documentation","I need to learn how different languages handle the same error patterns (null safety, type checking)","I want to prevent similar errors in the future by understanding the underlying pattern"],"best_for":["Developers learning multiple languages who want to understand error patterns across languages","Polyglot teams where developers frequently switch between languages","Junior developers building mental models of common error types"],"limitations":["Language-agnostic explanations may miss language-specific nuances and idioms","Error pattern recognition relies on standard error messages — custom or framework-specific errors may not be recognized","No integration with language-specific debugging tools or runtime introspection","Explanations are generic and may not address domain-specific error contexts","Limited ability to trace errors across multiple files or complex call stacks"],"requires":["VS Code 1.50+ OR JetBrains IDE (IntelliJ 2020.1+, PyCharm 2020.1+)","AskCodi extension installed","API key from AskCodi account","IDE error detection enabled (linters, language servers, or runtime error reporting)"],"input_types":["error message (text)","error type/code (standardized or language-specific)","source code context","language/syntax type"],"output_types":["standardized error explanation (language-agnostic)","language-specific fix suggestion","cross-language pattern explanation"],"categories":["planning-reasoning","code-generation-editing"],"confidence":0.5,"matches":0,"success_rate":0}],"trust":{"score":39,"verified":false,"data_access_risk":"high","permissions":["VS Code 1.50+ OR JetBrains IDE (IntelliJ 2020.1+, PyCharm 2020.1+)","AskCodi extension installed from marketplace","API key from AskCodi account (free tier available)","Active internet connection for model inference","AskCodi extension installed","API key from AskCodi account","IDE error detection enabled (built-in linters or language servers)","Language server or linter support for the target language","Clear, descriptive comments in the code","Active internet connection to query snippet database"],"failure_modes":["Code quality degrades on complex logic patterns and architectural decisions — requires manual refinement more often than Copilot","Smaller training dataset means weaker understanding of proprietary frameworks and bleeding-edge library syntax","Completion latency increases with file size and complexity due to local context analysis","No cross-file codebase indexing — suggestions based only on current file and immediate context","Explanations are generic and may not capture domain-specific error contexts (e.g., framework-specific exceptions)","Suggested fixes are heuristic-based and may not address the actual root cause in complex multi-file scenarios","No integration with runtime debuggers — relies on static error analysis and exception messages only","Limited ability to trace errors across multiple files or asynchronous code paths","Refactoring suggestions are based on syntactic patterns, not semantic understanding — may miss context-dependent refactoring opportunities","No awareness of business logic or architectural constraints — suggested refactorings may violate design patterns","builder identity is not verified yet","no observed match outcomes yet"],"rank_breakdown":{"adoption":0.31666666666666665,"quality":0.67,"ecosystem":0.15000000000000002,"match_graph":0.25,"freshness":0.75,"weights":{"adoption":0.25,"quality":0.25,"ecosystem":0.1,"match_graph":0.35,"freshness":0.05}},"observed_outcomes":{"matches":0,"success_rate":0,"avg_confidence":0,"top_intents":[],"last_matched_at":null},"maintenance":{"status":"active","updated_at":"2026-05-24T12:16:29.133Z","last_scraped_at":"2026-04-05T13:23:42.561Z","last_commit":null},"community":{"stars":null,"forks":null,"weekly_downloads":null,"model_downloads":null,"model_likes":null}},"distribution":{"claim_url":"https://unfragile.ai/submit?claim=askcodi","compare_url":"https://unfragile.ai/compare?artifact=askcodi"}},"signature":"IaRhoyXsUbVOT4aOAvzNiYZic9jnDy0sBNDGD0DqwgkfUsu5ZrWnVMHjJmMU2rhYV/90dNXea65OLXqgtznHBA==","signedAt":"2026-06-21T14:08:35.806Z","signedBy":"unfragile.ai","version":1},"_links":{"self":"https://unfragile.ai/api/v1/passport/askcodi","artifact":"https://unfragile.ai/askcodi","verify":"https://unfragile.ai/api/v1/verify?slug=askcodi","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"}}