{"passport":{"unfragile":{"@version":"1.0","version":"2026-05","artifact":{"id":"vscode-augment-vscode-augment","slug":"augment-coding-agent-built-for-large-complex-codebases","name":"Augment: Coding Agent Built for Large, Complex Codebases","type":"agent","url":"https://marketplace.visualstudio.com/items?itemName=augment.vscode-augment","page_url":"https://unfragile.ai/augment-coding-agent-built-for-large-complex-codebases","categories":["code-editors"],"tags":["agents","ai","ai agents","artificial intelligence","assistant","autocomplete","c","c#","c++","chat","code completion","coding assistant","copilot","css","go","html","intellisense","java","javascript","keybindings","mcp","node.js","pair programming","php","python","react","remote agents","ruby","rust","swift","typescript"],"pricing":{"model":"freemium","free":true,"starting_price":null},"status":"active","verified":false},"capabilities":[{"id":"vscode-augment-vscode-augment__cap_0","uri":"capability://code.generation.editing.codebase.aware.code.completion.with.architectural.context","name":"codebase-aware code completion with architectural context","description":"Generates inline code suggestions as developers type by analyzing the entire codebase structure, dependencies, and project style conventions. Unlike token-based completion, Augment's context engine indexes architectural patterns, API signatures, and legacy code conventions to produce suggestions tailored to the specific project's structure and coding patterns. Completions appear inline in the editor and adapt to the developer's local coding style and project dependencies.","intents":["Get fast, contextually relevant code suggestions while typing without breaking flow","Reduce boilerplate by auto-completing API calls and patterns specific to my project","Maintain consistency with existing codebase style and conventions automatically"],"best_for":["developers working in large, complex codebases with established patterns","teams maintaining legacy systems with non-standard conventions","polyglot projects where style varies significantly across modules"],"limitations":["Context window size not disclosed — may degrade on extremely large monorepos (>1M LOC)","Indexing mechanism and refresh frequency not documented — potential staleness on rapidly changing code","No configuration options documented for tuning completion aggressiveness or context depth","Performance impact on VS Code startup and background indexing not quantified"],"requires":["VS Code (minimum version not specified)","Augment extension installed from marketplace","Active sign-in to Augment account (free or paid tier)","Codebase must be accessible within VS Code workspace"],"input_types":["code context (current file, surrounding lines, project structure)","implicit user intent (cursor position, partial tokens typed)"],"output_types":["inline code suggestions (single or multi-line completions)","completion metadata (confidence, alternative suggestions if available)"],"categories":["code-generation-editing","memory-knowledge"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"vscode-augment-vscode-augment__cap_1","uri":"capability://code.generation.editing.multi.file.code.modification.with.turn.by.turn.guidance","name":"multi-file code modification with turn-by-turn guidance","description":"Executes coordinated code changes across multiple files (source code, tests, documentation) through a 'Next Edit' workflow that breaks complex refactors into sequential, reviewable steps. The agent analyzes dependencies and impact scope, then guides developers through edits with explicit instructions for each file modification. Changes are applied incrementally with a 'Smart Apply' feature that intelligently updates code in context rather than requiring manual merge resolution.","intents":["Refactor APIs or functions across an entire codebase without manually tracking all call sites","Rename or restructure code elements while automatically updating tests and documentation","Execute complex multi-file changes with clear, step-by-step guidance to understand impact"],"best_for":["teams performing large-scale refactors across monorepos or multi-module projects","developers unfamiliar with codebase structure who need guided, safe multi-file edits","projects where test and documentation updates must stay synchronized with code changes"],"limitations":["Scope of 'agent autonomy' not specified — unclear which edits are suggested vs. auto-applied","No rollback mechanism documented — if multi-file edit partially fails, recovery process unknown","Dependency analysis depth not disclosed — may miss indirect dependencies or dynamic imports","No explicit conflict resolution strategy documented for overlapping edits in shared files","Turn-by-turn guidance workflow requires human approval at each step, limiting true automation"],"requires":["VS Code workspace with multiple files accessible","Augment extension with 'Next Edit' feature (availability by tier unknown)","Active sign-in to Augment account","Codebase must be indexed and analyzed by Augment's context engine"],"input_types":["natural language instruction (e.g., 'rename UserService to AuthService everywhere')","implicit context (current file, cursor position, selected code)"],"output_types":["sequential edit instructions (one per file, with before/after code diffs)","applied code changes (via Smart Apply feature)","impact summary (files affected, changes made)"],"categories":["code-generation-editing","planning-reasoning"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"vscode-augment-vscode-augment__cap_10","uri":"capability://code.generation.editing.code.review.and.validation.with.architectural.awareness","name":"code review and validation with architectural awareness","description":"Reviews code changes for correctness, style consistency, architectural alignment, and potential issues by analyzing against codebase patterns and conventions. The agent can validate that new code follows established patterns, uses APIs correctly, maintains consistency with existing style, and doesn't introduce architectural violations. This capability supports both pre-commit validation and post-commit review workflows.","intents":["Validate code changes against project conventions and architectural patterns before committing","Identify potential bugs or issues in code changes using codebase-aware analysis","Ensure API usage is correct and consistent with project patterns"],"best_for":["teams with strict code quality standards and established architectural patterns","projects where manual code review is bottleneck and AI-assisted review can reduce cycle time","distributed teams where code review expertise is concentrated"],"limitations":["Review criteria and validation rules not documented — unclear what issues are detected","No integration with CI/CD systems documented for automated pre-commit validation","Review accuracy not benchmarked — may miss subtle bugs or architectural issues","No mechanism for customizing review rules or severity levels","False positive rate not specified — may flag valid code as problematic","No integration with code review tools (GitHub, GitLab, Gerrit) documented","Review reasoning is opaque — no visibility into why code was flagged as problematic"],"requires":["Augment extension with code review capability (availability by tier unknown)","Codebase indexed and analyzed for pattern extraction","Code changes to review (format not specified)"],"input_types":["code diff or changed files (format not specified)","implicit codebase context (patterns, conventions, architecture)"],"output_types":["review comments and suggestions (text)","identified issues (categorized by severity or type)","suggested fixes (code snippets or patches)"],"categories":["code-generation-editing","safety-moderation"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"vscode-augment-vscode-augment__cap_11","uri":"capability://automation.workflow.pricing.tier.gated.feature.access.with.freemium.model","name":"pricing-tier-gated feature access with freemium model","description":"Provides tiered access to Augment's capabilities through Indie, Standard, Max, and Enterprise pricing tiers. The extension operates on a freemium model where basic features are available to free users, with advanced capabilities (agent autonomy, MCP integration, higher context limits) restricted to paid tiers. Specific feature availability by tier is not documented, but the pricing structure enables monetization while providing entry-level access.","intents":["Provide free entry-level access to Augment for individual developers and small teams","Enable scaling of capabilities and support as teams grow and requirements increase","Monetize advanced features (autonomous agent, MCP integration) for enterprise customers"],"best_for":["individual developers and small teams evaluating Augment with limited budget","growing teams that need more advanced features as codebase and team size increase","enterprises requiring dedicated support and advanced capabilities"],"limitations":["Feature availability by tier not documented — unclear which capabilities are free vs. paid","Pricing details not provided — cost per tier unknown","Upgrade/downgrade process not documented","No trial period or money-back guarantee mentioned","Free tier limitations not specified (e.g., request limits, context window size, feature restrictions)","No clear upgrade path or feature comparison table provided","Enterprise tier customization options not documented"],"requires":["Augment account (free or paid)","VS Code extension installed","Selection of appropriate pricing tier based on needs"],"input_types":["pricing tier selection (implicit, during account setup)"],"output_types":["access to tier-specific features and capabilities"],"categories":["automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"vscode-augment-vscode-augment__cap_2","uri":"capability://code.generation.editing.natural.language.code.generation.and.modification.from.editor.prompts","name":"natural language code generation and modification from editor prompts","description":"Accepts natural language instructions directly in the VS Code editor (via 'Instructions' feature) to generate or modify code without switching to a chat interface. Developers write prompts in-editor (mechanism for prompt entry not specified), and Augment generates code changes ranging from simple edits to complex refactors. The agent understands project context (architecture, dependencies, style) to produce code that integrates seamlessly with existing codebase rather than generating isolated snippets.","intents":["Write code by describing intent in natural language without manually typing boilerplate","Refactor tedious code patterns (e.g., converting callbacks to async/await) with a single prompt","Generate test cases or documentation based on existing code without context switching"],"best_for":["developers seeking faster code authoring through natural language descriptions","teams with mixed skill levels who benefit from AI-guided code generation","projects where maintaining consistent style and patterns is critical"],"limitations":["Prompt entry mechanism not documented — unclear if prompts are inline comments, special syntax, or sidebar input","No specification of prompt length limits or complexity thresholds","Generated code quality and correctness not benchmarked — relies on model capability without validation","No explicit mechanism for rejecting or iterating on generated code shown","Context window constraints not disclosed — may fail on very large or complex refactor requests"],"requires":["VS Code extension installed and signed in","Codebase indexed by Augment's context engine","Natural language prompt (format and entry method not specified)","Sufficient context in codebase for agent to understand style and patterns"],"input_types":["natural language instruction (text prompt)","implicit code context (current file, selection, project structure)"],"output_types":["generated code (inline insertion or diff preview)","modified code (refactored existing code)"],"categories":["code-generation-editing"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"vscode-augment-vscode-augment__cap_3","uri":"capability://text.generation.language.conversational.codebase.q.a.with.smart.code.application","name":"conversational codebase q&a with smart code application","description":"Provides a chat interface for asking questions about the codebase, planning features, and defining code changes. The 'Chat' feature integrates with 'Smart Apply' to convert conversational suggestions into applied code changes with a single click, bridging the gap between discussion and implementation. Developers can ask about architecture, APIs, bugs, or request feature implementations, and the agent responds with explanations and actionable code suggestions.","intents":["Ask questions about codebase architecture, APIs, and patterns without manual documentation review","Plan features or refactors conversationally and immediately apply suggested code changes","Get instant answers about how to implement specific functionality in the project's context"],"best_for":["developers onboarding to new codebases who need rapid architectural understanding","teams using AI-assisted pair programming for feature planning and implementation","projects where codebase knowledge is distributed and chat-based discovery is faster than docs"],"limitations":["Chat context window size not specified — may lose conversation history on long sessions","Smart Apply mechanism not detailed — unclear how it handles conflicts or validates changes","No conversation persistence or history management documented","Accuracy of architectural understanding not benchmarked — may provide incorrect or outdated information","No explicit guardrails for preventing dangerous code suggestions (e.g., SQL injection, security issues)"],"requires":["VS Code extension installed and signed in","Codebase indexed by Augment's context engine","Active chat session within Augment sidebar or panel","Sufficient codebase context for meaningful Q&A"],"input_types":["natural language questions and requests (text)","implicit codebase context (indexed files, architecture)"],"output_types":["conversational responses (text explanations)","code suggestions (with Smart Apply integration)","applied code changes (via Smart Apply)"],"categories":["text-generation-language","memory-knowledge"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"vscode-augment-vscode-augment__cap_4","uri":"capability://planning.reasoning.autonomous.agent.task.execution.for.feature.development.and.bug.resolution","name":"autonomous agent task execution for feature development and bug resolution","description":"Executes complex tasks autonomously (scope and autonomy level not fully specified) to complete features, build functionality, and solve production problems. The 'Agent' feature claims to handle end-to-end task execution, though the mechanism for task definition, execution boundaries, and human oversight is not documented. Agent operates within the codebase context to understand dependencies and impact, theoretically enabling multi-step problem-solving without explicit step-by-step guidance.","intents":["Delegate feature development tasks to AI agent that handles implementation across multiple files","Automatically diagnose and fix production bugs by analyzing code, tests, and error context","Execute complex, multi-step refactors or migrations without manual coordination"],"best_for":["teams with high-velocity development where AI can handle routine feature implementation","on-call engineers debugging production issues who need rapid root-cause analysis and fixes","projects with well-defined patterns and conventions that agent can learn and apply"],"limitations":["Autonomy scope not specified — unclear which tasks agent can execute independently vs. requiring approval","No rollback or undo mechanism documented for failed autonomous changes","Task definition format not documented — unclear how to specify complex, multi-step tasks","No explicit validation or testing of generated code before application","Risk of unintended side effects or breaking changes not addressed","No audit trail or change logging for autonomous modifications","Agent decision-making process is opaque — no visibility into reasoning or alternative approaches considered"],"requires":["VS Code extension with 'Agent' feature (availability by tier unknown)","Augment account with appropriate permissions for autonomous execution","Codebase fully indexed and analyzed by Augment's context engine","Clear task definition or natural language instruction"],"input_types":["task description (natural language or structured format unknown)","implicit codebase context (architecture, dependencies, patterns)"],"output_types":["executed code changes (applied directly or with approval workflow unknown)","task completion status and summary","generated tests or validation results (if applicable)"],"categories":["planning-reasoning","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"vscode-augment-vscode-augment__cap_5","uri":"capability://memory.knowledge.codebase.indexing.and.architectural.analysis.for.context.awareness","name":"codebase indexing and architectural analysis for context awareness","description":"Indexes the entire codebase to build an internal model of architecture, dependencies, APIs, style conventions, and legacy code patterns. This indexing enables all other capabilities (completion, chat, agent) to operate with full codebase context rather than relying on limited local file context or general model knowledge. The indexing mechanism, refresh frequency, and storage location (local vs. remote) are not documented, but the capability is foundational to Augment's differentiation.","intents":["Enable AI features to understand project architecture and dependencies for accurate suggestions","Maintain consistency across codebase by learning and applying established patterns and conventions","Support rapid onboarding by providing AI with complete codebase knowledge without manual documentation"],"best_for":["large, complex codebases (>100K LOC) where local context is insufficient for accurate suggestions","monorepos and multi-module projects with complex dependency graphs","teams with established architectural patterns and conventions that should be preserved"],"limitations":["Indexing mechanism not documented — unclear if AST-based, semantic analysis, or embedding-based","Maximum codebase size not specified — performance on very large monorepos (>10M LOC) unknown","Refresh frequency not documented — may become stale on rapidly changing codebases","Index storage location not specified — unclear if local (disk space impact) or remote (privacy implications)","No configuration options for tuning index depth, refresh rate, or context window size","Indexing time estimates not provided — initial setup time for large codebases unknown","No mechanism documented for excluding files or directories from indexing (e.g., generated code, node_modules)"],"requires":["VS Code workspace with codebase accessible","Augment extension installed","Initial indexing process (time and resource requirements unknown)","Sufficient disk space for index storage (size not specified)"],"input_types":["codebase files (all supported languages)","project structure and configuration files (package.json, pom.xml, etc.)"],"output_types":["internal codebase model (not directly exposed to user)","context vectors or embeddings used by other capabilities"],"categories":["memory-knowledge","data-processing-analysis"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"vscode-augment-vscode-augment__cap_6","uri":"capability://tool.use.integration.mcp.based.tool.integration.with.100.external.tools","name":"mcp-based tool integration with 100+ external tools","description":"Integrates with Model Context Protocol (MCP) to access 100+ external tools and services, enabling the agent to call external APIs, run commands, and interact with third-party systems. The integration mechanism, tool registry, and configuration process are not documented, but the capability allows Augment's agent to extend beyond code generation into broader development workflows (e.g., running tests, deploying code, querying APIs).","intents":["Enable agent to run tests, linters, and build tools as part of task execution","Allow agent to query external APIs or databases to inform code generation decisions","Integrate with deployment, monitoring, or CI/CD systems for end-to-end automation"],"best_for":["teams using MCP-compatible tools and services in their development workflow","projects requiring agent to validate code changes through automated testing or linting","organizations with complex deployment or integration pipelines that agent should orchestrate"],"limitations":["Tool list not provided — unclear which of the '100+ tools' are available or how to discover them","MCP configuration process not documented — unclear how to set up or authorize tool access","Tool availability by pricing tier not specified — may be limited to higher tiers","No explicit security model documented for tool access — unclear how credentials are managed or scoped","Tool execution timeout or resource limits not specified","No error handling or fallback mechanism documented if tool calls fail","Tool output integration with agent reasoning not explained — unclear how tool results inform decisions"],"requires":["Augment extension with MCP support (availability unknown)","MCP-compatible tools installed and configured (specific tools not listed)","API keys or credentials for external tools (management mechanism not documented)","Network access to external services (if applicable)"],"input_types":["tool invocation requests from agent (format not specified)","tool parameters and configuration (format not documented)"],"output_types":["tool execution results (format varies by tool)","structured or unstructured output integrated into agent context"],"categories":["tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"vscode-augment-vscode-augment__cap_7","uri":"capability://planning.reasoning.bug.investigation.and.diagnosis.with.codebase.context","name":"bug investigation and diagnosis with codebase context","description":"Analyzes error messages, stack traces, and code context to diagnose root causes of bugs and suggest fixes. The agent leverages full codebase understanding to trace error origins across multiple files, understand call chains, and identify problematic patterns. This capability is positioned as a production problem-solving tool, enabling developers to quickly move from error report to root cause and fix.","intents":["Quickly diagnose root cause of production errors by analyzing stack traces and codebase context","Identify which code changes or patterns introduced a bug by analyzing dependencies and call chains","Generate fixes for common bug patterns (null pointer exceptions, off-by-one errors, etc.) with codebase awareness"],"best_for":["on-call engineers responding to production incidents who need rapid diagnosis","teams with large, complex codebases where manual root-cause analysis is time-consuming","projects with legacy code where bug origins are difficult to trace manually"],"limitations":["Diagnosis accuracy not benchmarked — no data on false positive or false negative rates","Error message format requirements not specified — unclear which error types are supported","Stack trace parsing mechanism not documented — may fail on non-standard formats","No explicit mechanism for handling multi-threaded or async bugs where stack traces are incomplete","Fix suggestions may be incorrect or incomplete without human validation","No integration with error tracking systems (Sentry, DataDog, etc.) documented","Diagnosis reasoning is opaque — no visibility into how agent arrived at root cause"],"requires":["Augment extension with bug diagnosis capability (availability by tier unknown)","Error message or stack trace (format not specified)","Codebase indexed and analyzed by Augment's context engine","Sufficient context in codebase for agent to understand error origin"],"input_types":["error message or exception (text)","stack trace (format varies by language/runtime)","implicit codebase context (indexed files, architecture)"],"output_types":["root cause analysis (text explanation)","suggested fixes (code changes or patches)","affected files and functions (list with locations)"],"categories":["planning-reasoning","code-generation-editing"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"vscode-augment-vscode-augment__cap_8","uri":"capability://memory.knowledge.api.and.schema.learning.from.codebase","name":"api and schema learning from codebase","description":"Automatically learns and understands APIs, data schemas, and external service integrations by analyzing codebase usage patterns. The agent extracts API signatures, parameter types, return values, and usage examples from existing code to build a project-specific knowledge base. This enables accurate code generation and suggestions that correctly use project-specific APIs and schemas without requiring manual documentation.","intents":["Generate code that correctly uses project-specific APIs without manual API documentation review","Understand data schemas and structures by analyzing how they're used throughout the codebase","Learn external service integrations (payment APIs, cloud services, etc.) from existing code examples"],"best_for":["projects with custom or internal APIs that aren't well-documented","teams integrating multiple external services with complex, non-standard configurations","codebases with evolving APIs where documentation lags behind implementation"],"limitations":["API extraction mechanism not documented — unclear if based on AST analysis, type hints, or usage patterns","Accuracy of learned APIs not benchmarked — may misinterpret complex or non-standard usage","No mechanism documented for validating learned APIs against actual definitions","Dynamic APIs or runtime-generated schemas may not be captured","No explicit handling of API versioning or deprecation","Learning scope limited to codebase — external API documentation not integrated","No mechanism for correcting or refining learned API knowledge"],"requires":["Codebase with sufficient API usage examples (minimum coverage unknown)","Augment's codebase indexing and analysis engine","Type hints or documentation comments for accurate API extraction (optional but helpful)"],"input_types":["codebase files with API usage (implicit, not user-provided)"],"output_types":["learned API signatures and schemas (internal representation)","accurate code suggestions using project-specific APIs"],"categories":["memory-knowledge","data-processing-analysis"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"vscode-augment-vscode-augment__cap_9","uri":"capability://memory.knowledge.codebase.onboarding.and.navigation.assistance","name":"codebase onboarding and navigation assistance","description":"Helps developers rapidly understand large, complex codebases by providing guided tours, architectural explanations, and navigation assistance. The agent can answer questions about codebase structure, explain how components interact, identify key files and modules, and guide developers to relevant code sections. This capability is positioned as a solution for reducing onboarding time and enabling faster context acquisition for new team members.","intents":["Quickly understand codebase architecture and key components without manual exploration","Find relevant code sections for a specific feature or bug without manual searching","Learn how different modules interact and depend on each other"],"best_for":["new team members onboarding to large, complex codebases","developers switching between projects who need rapid context acquisition","teams with high turnover or distributed knowledge where documentation is incomplete"],"limitations":["Onboarding workflow and guidance format not specified","No metrics provided on time saved or effectiveness of onboarding","Explanation accuracy depends on codebase indexing quality — may be incomplete or incorrect","No interactive exploration features documented (e.g., guided tours, step-by-step walkthroughs)","Navigation assistance limited to codebase understanding — no integration with documentation or wikis","No personalization based on developer role or experience level"],"requires":["Augment extension installed and signed in","Codebase fully indexed by Augment's context engine","Natural language questions or navigation requests"],"input_types":["natural language questions about codebase (text)","implicit context (current file, cursor position)"],"output_types":["architectural explanations (text)","navigation suggestions (file paths, function names, line numbers)","component interaction diagrams or summaries (format not specified)"],"categories":["memory-knowledge","text-generation-language"],"confidence":0.5,"matches":0,"success_rate":0}],"trust":{"score":51,"verified":false,"data_access_risk":"high","permissions":["VS Code (minimum version not specified)","Augment extension installed from marketplace","Active sign-in to Augment account (free or paid tier)","Codebase must be accessible within VS Code workspace","VS Code workspace with multiple files accessible","Augment extension with 'Next Edit' feature (availability by tier unknown)","Active sign-in to Augment account","Codebase must be indexed and analyzed by Augment's context engine","Augment extension with code review capability (availability by tier unknown)","Codebase indexed and analyzed for pattern extraction"],"failure_modes":["Context window size not disclosed — may degrade on extremely large monorepos (>1M LOC)","Indexing mechanism and refresh frequency not documented — potential staleness on rapidly changing code","No configuration options documented for tuning completion aggressiveness or context depth","Performance impact on VS Code startup and background indexing not quantified","Scope of 'agent autonomy' not specified — unclear which edits are suggested vs. auto-applied","No rollback mechanism documented — if multi-file edit partially fails, recovery process unknown","Dependency analysis depth not disclosed — may miss indirect dependencies or dynamic imports","No explicit conflict resolution strategy documented for overlapping edits in shared files","Turn-by-turn guidance workflow requires human approval at each step, limiting true automation","Review criteria and validation rules not documented — unclear what issues are detected","builder identity is not verified yet","no observed match outcomes yet"],"rank_breakdown":{"adoption":0.77,"quality":0.49,"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":"2026-05-24T12:16:34.118Z","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=augment-coding-agent-built-for-large-complex-codebases","compare_url":"https://unfragile.ai/compare?artifact=augment-coding-agent-built-for-large-complex-codebases"}},"signature":"DYSbD0+lAb3ujieoTh5lv1nlzkVjJCktOxXyMwkzT51gdZraIueLorE8JC1QQG1VvAJX0ZNp1U5f5Zz9KEHlCA==","signedAt":"2026-06-21T03:27:22.673Z","signedBy":"unfragile.ai","version":1},"_links":{"self":"https://unfragile.ai/api/v1/passport/augment-coding-agent-built-for-large-complex-codebases","artifact":"https://unfragile.ai/augment-coding-agent-built-for-large-complex-codebases","verify":"https://unfragile.ai/api/v1/verify?slug=augment-coding-agent-built-for-large-complex-codebases","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"}}