{"passport":{"unfragile":{"@version":"1.0","version":"2026-05","artifact":{"id":"hn-47460525","slug":"opencode-open-source-ai-coding-agent","name":"OpenCode – Open source AI coding agent","type":"agent","url":"https://opencode.ai/","page_url":"https://unfragile.ai/opencode-open-source-ai-coding-agent","categories":["ai-agents"],"tags":["hackernews","show-hn"],"pricing":{"model":"unknown","free":false,"starting_price":null},"status":"active","verified":false},"capabilities":[{"id":"hn-47460525__cap_0","uri":"capability://code.generation.editing.autonomous.code.generation.from.natural.language.specifications","name":"autonomous code generation from natural language specifications","description":"Accepts natural language task descriptions and generates complete, functional code implementations through an agentic loop that iteratively refines outputs. The agent decomposes requirements into subtasks, generates code candidates, and validates against implicit or explicit acceptance criteria before returning final implementations. Uses multi-turn reasoning to handle complex specifications that require multiple file modifications or architectural decisions.","intents":["I want to describe what code should do in plain English and get a working implementation without writing it myself","I need to generate boilerplate or scaffold code for a new feature quickly","I want an AI to handle multi-file code generation where changes span multiple modules"],"best_for":["solo developers prototyping features rapidly","teams reducing time-to-implementation for well-specified features","developers working in languages where they lack deep expertise"],"limitations":["Requires clear, unambiguous specifications — vague requirements lead to multiple refinement loops","No guaranteed correctness for complex algorithmic problems or security-critical code","Context window limitations may prevent handling very large codebases or deeply nested requirements","Generated code may not follow team-specific conventions without explicit style guidance"],"requires":["API access to underlying LLM (OpenAI, Anthropic, or local model)","Clear task description with sufficient technical detail","Target language/framework specification"],"input_types":["natural language task description","code snippets for context","existing codebase references"],"output_types":["source code files","multi-file code patches","structured code with comments"],"categories":["code-generation-editing","planning-reasoning"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"hn-47460525__cap_1","uri":"capability://memory.knowledge.codebase.aware.context.injection.and.retrieval","name":"codebase-aware context injection and retrieval","description":"Maintains awareness of existing codebase structure, dependencies, and conventions to inform code generation decisions. The agent likely indexes or analyzes the target codebase to extract patterns, naming conventions, and architectural decisions, then injects this context into prompts to ensure generated code aligns with project standards. May use file-level or symbol-level retrieval to surface relevant existing code during generation.","intents":["I want generated code to follow my project's existing patterns and conventions automatically","I need the agent to understand my codebase structure so it generates code that integrates seamlessly","I want to avoid having to manually specify architectural constraints for each generation task"],"best_for":["teams with established codebases and strong architectural conventions","projects where consistency across files is critical","developers working in monorepos or multi-module projects"],"limitations":["Indexing large codebases (>100k LOC) may introduce latency or memory overhead","Context injection adds tokens to each request, increasing API costs","May struggle with highly unconventional or legacy code patterns","Requires codebase to be accessible and parseable by the agent"],"requires":["Access to local or remote codebase files","Sufficient storage for codebase index or AST representation","Language-specific parsers for accurate pattern extraction"],"input_types":["codebase directory structure","existing source files","configuration files (package.json, requirements.txt, etc.)"],"output_types":["context-aware code suggestions","code that matches project conventions"],"categories":["memory-knowledge","code-generation-editing"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"hn-47460525__cap_10","uri":"capability://code.generation.editing.dependency.management.and.library.integration","name":"dependency management and library integration","description":"Manages project dependencies and integrates external libraries into generated code. The agent understands available libraries, their APIs, and best practices for integration, then generates code that uses appropriate libraries. May automatically add dependencies to package managers (npm, pip, etc.) and generate import statements or configuration.","intents":["I want the agent to use appropriate libraries when generating code","I need the agent to add dependencies automatically and generate correct import statements","I want the agent to suggest libraries for specific tasks"],"best_for":["teams using package managers and dependency management","projects with specific library preferences or constraints","developers who want to avoid manual dependency management"],"limitations":["Agent knowledge of libraries may be outdated or incomplete","Dependency conflicts or version incompatibilities may not be detected","Agent may not understand team-specific library preferences or constraints","Generated code may use libraries inefficiently or incorrectly"],"requires":["Package manager access (npm, pip, etc.)","Knowledge of available libraries and their APIs","Dependency resolution capability"],"input_types":["task description","project configuration"],"output_types":["code with library usage","dependency specifications","import statements"],"categories":["code-generation-editing","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"hn-47460525__cap_2","uri":"capability://code.generation.editing.iterative.code.refinement.with.validation.feedback.loops","name":"iterative code refinement with validation feedback loops","description":"Implements a feedback loop where generated code is validated (via linting, type checking, test execution, or manual review) and failures are fed back to the agent for refinement. The agent analyzes error messages, compilation failures, or test results and regenerates code to address specific issues. This loop continues until code passes validation or reaches a maximum iteration threshold.","intents":["I want the agent to fix its own code when it doesn't compile or pass tests","I need generated code to be validated automatically before I review it","I want to provide feedback on generated code and have the agent improve it iteratively"],"best_for":["teams with automated test suites that can validate generated code","projects where code quality gates are non-negotiable","developers who want to reduce manual review cycles"],"limitations":["Validation infrastructure must be accessible to the agent (test runners, linters, type checkers)","Feedback loops add latency — each iteration requires a new LLM call","Agent may get stuck in local optima or infinite loops if validation criteria are contradictory","Cost scales with number of refinement iterations"],"requires":["Automated validation tools (test framework, linter, type checker)","Ability to execute validation in agent environment","Clear error messages from validation tools"],"input_types":["generated code","validation error messages","test failure logs"],"output_types":["refined code","validation status reports"],"categories":["code-generation-editing","planning-reasoning"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"hn-47460525__cap_3","uri":"capability://code.generation.editing.multi.language.code.generation.with.language.specific.optimization","name":"multi-language code generation with language-specific optimization","description":"Supports code generation across multiple programming languages with language-specific optimizations for syntax, idioms, and best practices. The agent likely uses language-specific prompting, tokenization, or validation rules to ensure generated code follows language conventions. May include language-specific linters, type checkers, or runtime validators to improve code quality.","intents":["I need to generate code in multiple languages for a polyglot project","I want generated code to follow language-specific idioms and best practices","I need the agent to understand language-specific constraints (type systems, memory management, etc.)"],"best_for":["polyglot teams working across multiple languages","projects with language-specific performance or safety requirements","developers who want idiomatic code in languages they're less familiar with"],"limitations":["Quality varies significantly across languages — some languages may have less training data","Language-specific validation tools must be installed and configured","Idiomatic code generation requires deep language knowledge in the underlying model","Support for niche or new languages may be limited"],"requires":["Language-specific parsers or AST tools","Language-specific linters and validators","Underlying LLM with training data for target languages"],"input_types":["target language specification","language-agnostic task description"],"output_types":["language-specific source code","idiomatic implementations"],"categories":["code-generation-editing"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"hn-47460525__cap_4","uri":"capability://planning.reasoning.agentic.task.decomposition.and.multi.step.code.generation","name":"agentic task decomposition and multi-step code generation","description":"Breaks down complex coding tasks into subtasks, generates code for each subtask, and orchestrates integration of subtask outputs into a cohesive solution. The agent uses planning or reasoning steps to identify dependencies between subtasks, determine execution order, and validate that subtask outputs compose correctly. This enables handling of tasks that require multiple files, architectural decisions, or cross-cutting concerns.","intents":["I want to describe a complex feature that spans multiple files and have the agent handle all the pieces","I need the agent to identify what needs to be built and build it in the right order","I want to generate code for a feature that requires changes to multiple layers (API, database, UI)"],"best_for":["teams building features that span multiple architectural layers","projects with complex interdependencies between modules","developers who want to avoid manually coordinating multi-file changes"],"limitations":["Decomposition quality depends on agent's reasoning capability — poor decomposition leads to integration failures","Subtask interdependencies may not be fully captured, leading to missing or conflicting changes","Orchestration adds latency — each subtask requires separate LLM calls","Debugging failures across subtasks is more complex than single-file generation"],"requires":["Reasoning or planning capability in underlying LLM","Ability to track and manage multiple code generation tasks","Integration validation mechanism"],"input_types":["high-level feature description","architectural constraints"],"output_types":["multiple coordinated code files","task decomposition plan","integration validation results"],"categories":["planning-reasoning","code-generation-editing"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"hn-47460525__cap_5","uri":"capability://code.generation.editing.interactive.code.generation.with.user.feedback.integration","name":"interactive code generation with user feedback integration","description":"Supports iterative refinement of generated code through user feedback in a conversational interface. The agent accepts corrections, clarifications, or new requirements from the user and regenerates code accordingly. Maintains conversation context across multiple turns to understand user preferences and apply them consistently across refinements.","intents":["I want to iteratively refine generated code by providing feedback and seeing improvements","I need to clarify requirements mid-generation and have the agent adjust its output","I want to explore alternative implementations by asking the agent to try different approaches"],"best_for":["exploratory development where requirements evolve","teams with non-technical stakeholders who need to guide code generation","developers who want to collaborate with an AI agent on code design"],"limitations":["Conversation context grows with each turn, increasing token usage and latency","User feedback quality directly impacts code quality — vague feedback leads to poor refinements","Agent may misinterpret user intent or apply feedback inconsistently","No persistent memory across sessions — context resets between conversations"],"requires":["Conversational interface (CLI, web UI, IDE plugin)","Ability to maintain conversation history","User access to provide feedback"],"input_types":["natural language feedback","code corrections","clarification questions"],"output_types":["refined code","explanations of changes","alternative implementations"],"categories":["code-generation-editing","text-generation-language"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"hn-47460525__cap_6","uri":"capability://text.generation.language.code.explanation.and.documentation.generation","name":"code explanation and documentation generation","description":"Analyzes generated or existing code and produces natural language explanations, documentation, or comments. The agent uses code understanding techniques (AST analysis, semantic understanding, or LLM-based analysis) to extract intent and functionality, then generates human-readable documentation. May produce docstrings, README sections, or architectural documentation.","intents":["I want the agent to explain what the code it generated does","I need to generate documentation for code automatically","I want to add comments and docstrings to generated code"],"best_for":["teams that prioritize code documentation","projects with high onboarding requirements","developers who want to understand generated code before using it"],"limitations":["Documentation quality depends on code clarity — poorly written code produces poor documentation","Generated explanations may be verbose or miss important details","Language-specific documentation formats (docstrings, JSDoc, etc.) require language-specific templates","No guarantee that documentation stays in sync with code changes"],"requires":["Code analysis capability (AST parsing or semantic understanding)","Language-specific documentation format knowledge"],"input_types":["source code","code context or intent"],"output_types":["natural language explanations","docstrings","README sections","architectural documentation"],"categories":["text-generation-language","code-generation-editing"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"hn-47460525__cap_7","uri":"capability://code.generation.editing.test.generation.and.test.driven.code.generation","name":"test generation and test-driven code generation","description":"Automatically generates unit tests, integration tests, or end-to-end tests for generated code. May support test-driven development workflows where tests are generated first and code is generated to satisfy tests. Uses code analysis to identify test cases, edge cases, and coverage gaps, then generates test implementations in the appropriate testing framework.","intents":["I want the agent to generate tests for the code it creates","I need to write tests first and have the agent generate code that passes them","I want to ensure generated code has adequate test coverage"],"best_for":["teams with strong testing cultures","projects where code quality is enforced through test coverage","developers practicing test-driven development"],"limitations":["Generated tests may not cover all edge cases or security concerns","Test quality depends on agent's understanding of requirements — incomplete requirements lead to incomplete tests","Testing framework must be installed and configured","Generated tests may be brittle or overly specific to implementation details"],"requires":["Testing framework (Jest, pytest, JUnit, etc.)","Ability to execute tests in agent environment","Clear requirements or existing code to analyze"],"input_types":["source code","requirements or specifications","existing tests (for test-driven workflows)"],"output_types":["test code","test coverage reports"],"categories":["code-generation-editing"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"hn-47460525__cap_8","uri":"capability://code.generation.editing.code.refactoring.and.optimization.suggestions","name":"code refactoring and optimization suggestions","description":"Analyzes existing code and suggests or automatically applies refactorings to improve readability, performance, or maintainability. The agent uses code analysis to identify anti-patterns, inefficiencies, or style violations, then generates refactored versions with explanations of changes. May support targeted refactorings (extract method, rename variable, etc.) or broad optimizations (algorithmic improvements, memory optimization).","intents":["I want the agent to suggest ways to improve my code's readability or performance","I need to refactor code automatically while maintaining functionality","I want to understand why a refactoring is beneficial before applying it"],"best_for":["teams maintaining legacy codebases","developers improving code quality incrementally","projects with performance optimization requirements"],"limitations":["Refactoring suggestions may not preserve all behavioral nuances (e.g., error handling, side effects)","Performance optimizations are speculative without profiling data","Large refactorings may introduce subtle bugs that require testing to catch","Agent may not understand domain-specific performance requirements"],"requires":["Code analysis capability","Refactoring validation (tests, type checking)","Optional: performance profiling data"],"input_types":["source code","refactoring goals or constraints"],"output_types":["refactored code","refactoring explanations","performance impact estimates"],"categories":["code-generation-editing"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"hn-47460525__cap_9","uri":"capability://code.generation.editing.debugging.assistance.and.error.diagnosis","name":"debugging assistance and error diagnosis","description":"Analyzes error messages, stack traces, or failing code and provides debugging assistance or automatic fixes. The agent uses error analysis to identify root causes, suggests fixes, or automatically generates corrected code. May integrate with debuggers or logging systems to gather additional context for diagnosis.","intents":["I have a compilation or runtime error and want the agent to help me fix it","I want the agent to diagnose why my code is failing","I need the agent to suggest debugging steps or provide fixes automatically"],"best_for":["developers debugging unfamiliar code or languages","teams reducing time spent on bug fixing","projects with automated error reporting systems"],"limitations":["Diagnosis accuracy depends on error message quality — cryptic errors are hard to diagnose","Agent may suggest fixes that address symptoms rather than root causes","Complex bugs involving multiple systems or race conditions are difficult to diagnose automatically","Fixes may introduce new bugs or side effects"],"requires":["Error messages or stack traces","Access to source code and context","Optional: debugger integration or logging data"],"input_types":["error messages","stack traces","source code","logs"],"output_types":["debugging suggestions","corrected code","root cause analysis"],"categories":["code-generation-editing","planning-reasoning"],"confidence":0.5,"matches":0,"success_rate":0}],"trust":{"score":49,"verified":false,"data_access_risk":"low","permissions":["API access to underlying LLM (OpenAI, Anthropic, or local model)","Clear task description with sufficient technical detail","Target language/framework specification","Access to local or remote codebase files","Sufficient storage for codebase index or AST representation","Language-specific parsers for accurate pattern extraction","Package manager access (npm, pip, etc.)","Knowledge of available libraries and their APIs","Dependency resolution capability","Automated validation tools (test framework, linter, type checker)"],"failure_modes":["Requires clear, unambiguous specifications — vague requirements lead to multiple refinement loops","No guaranteed correctness for complex algorithmic problems or security-critical code","Context window limitations may prevent handling very large codebases or deeply nested requirements","Generated code may not follow team-specific conventions without explicit style guidance","Indexing large codebases (>100k LOC) may introduce latency or memory overhead","Context injection adds tokens to each request, increasing API costs","May struggle with highly unconventional or legacy code patterns","Requires codebase to be accessible and parseable by the agent","Agent knowledge of libraries may be outdated or incomplete","Dependency conflicts or version incompatibilities may not be detected","builder identity is not verified yet","no observed match outcomes yet"],"rank_breakdown":{"adoption":0.92,"quality":0.32,"ecosystem":0.21000000000000002,"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":"2026-05-24T12:16:23.326Z","last_scraped_at":"2026-05-04T08:10:16.626Z","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=opencode-open-source-ai-coding-agent","compare_url":"https://unfragile.ai/compare?artifact=opencode-open-source-ai-coding-agent"}},"signature":"NtBEDL/G8nCHtAOZjEuGxCY6G78eRmBG6HJNT9Ws7a0pil3ej5CdvTpsAIGlbPX0cwcuKhImQvWB8C+2+FpmBw==","signedAt":"2026-06-20T14:26:38.973Z","signedBy":"unfragile.ai","version":1},"_links":{"self":"https://unfragile.ai/api/v1/passport/opencode-open-source-ai-coding-agent","artifact":"https://unfragile.ai/opencode-open-source-ai-coding-agent","verify":"https://unfragile.ai/api/v1/verify?slug=opencode-open-source-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"}}