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Uses fuzzy matching on surrounding context lines to determine if a patch can be applied despite minor whitespace or formatting changes.","intents":["Prevent corrupted file merges by validating patches before applying them","Detect when source files have changed since the AI suggestion was generated","Understand why a patch failed to apply and what manual fixes are needed"],"best_for":["teams with strict code quality requirements and CI/CD pipelines","developers working in fast-moving codebases where files change frequently","automated systems that need to fail safely rather than silently corrupt code"],"limitations":["Fuzzy matching heuristics may incorrectly validate patches that appear compatible but introduce subtle bugs","No semantic understanding of code — validation is purely syntactic/structural","Cannot resolve conflicts automatically; only detects and reports them","Performance scales linearly with file size — validation on 10MB+ files may add 500ms+ latency"],"requires":["Source files accessible and readable","Patches in unified diff format with valid hunk headers","Relace Apply 3 API endpoint"],"input_types":["unified diff format (text)","source code files (text)","validation strictness level (optional parameter)"],"output_types":["validation result (boolean/enum: valid, conflict, error)","detailed conflict report with line numbers and context (structured data)"],"categories":["code-generation-editing","safety-moderation"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"openrouter-relace-relace-apply-3__cap_3","uri":"capability://automation.workflow.batch.multi.file.patch.orchestration","name":"batch-multi-file-patch-orchestration","description":"Orchestrates application of multiple patches across different files in a single atomic operation, maintaining transactional semantics where all patches succeed or all fail together. Internally sequences patch applications to respect file dependencies (e.g., applying schema changes before data migrations) and rolls back all changes if any patch fails validation or application.","intents":["Apply coordinated code changes across multiple files (e.g., refactoring that touches 5+ files) in one operation","Ensure consistency when AI suggestions span multiple interdependent files","Safely revert all changes if any patch in a batch fails, preventing partial/corrupted state"],"best_for":["teams performing large-scale refactorings via AI assistance","CI/CD pipelines applying coordinated code changes from multiple AI suggestions","developers needing transactional guarantees for multi-file edits"],"limitations":["Transactional rollback requires file system write permissions and may be slow on network-mounted storage","No built-in dependency graph analysis — must specify patch order manually or rely on heuristics","Atomic semantics only within a single batch operation; no cross-batch transactions","Large batches (>100 files) may exceed API timeout limits depending on file sizes"],"requires":["Multiple patches in unified diff format","Write permissions to all target files","Sufficient disk space for temporary rollback state","Relace Apply 3 API with batch endpoint support"],"input_types":["array of patches (unified diff format)","array of file paths (string)","optional: patch ordering/dependency specification (structured data)"],"output_types":["batch application result (success/failure enum)","per-file application status with error details (structured data)","modified source files (text)"],"categories":["automation-workflow","code-generation-editing"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"openrouter-relace-relace-apply-3__cap_4","uri":"capability://code.generation.editing.structured.patch.generation.from.natural.language.intent","name":"structured-patch-generation-from-natural-language-intent","description":"Accepts natural language descriptions of desired code changes and generates valid unified diff patches that can be applied to source files. Uses the underlying LLM to understand intent, analyze current code structure, and produce syntactically correct patches with proper hunk headers, line numbers, and context lines that match the actual source file state.","intents":["Describe what code changes I want in plain English and get a patch I can apply immediately","Generate patches from high-level refactoring goals without manually writing diffs","Create patches that are guaranteed to apply cleanly to my current codebase"],"best_for":["non-technical stakeholders describing desired changes to developers","developers rapidly iterating on code changes without manually writing diffs","automated systems generating code modifications from requirements"],"limitations":["Patch generation accuracy depends on LLM's understanding of intent — ambiguous descriptions produce invalid or incorrect patches","Generated patches may not apply if source code structure differs from LLM's training data","No guarantee that generated patches are semantically correct — syntax validation only","Large codebases (>1MB) may exceed context window, forcing truncation of source code"],"requires":["Source code files accessible to the model","Natural language description of desired changes (string)","Relace Apply 3 API with generation endpoint","API key for underlying LLM provider (OpenAI, Anthropic, etc.)"],"input_types":["natural language intent description (text)","source code files (text)","optional: code style/formatting preferences (structured data)"],"output_types":["unified diff format patch (text)","patch explanation/rationale (text)","confidence score for patch applicability (numeric)"],"categories":["code-generation-editing","text-generation-language"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"openrouter-relace-relace-apply-3__cap_5","uri":"capability://code.generation.editing.language.aware.syntax.preservation.during.patching","name":"language-aware-syntax-preservation-during-patching","description":"Preserves language-specific syntax, formatting, and style conventions during patch application by parsing code using language-specific AST parsers (for supported languages like Python, JavaScript, Java, Go) rather than treating all code as plain text. Maintains indentation, bracket styles, comment formatting, and other syntactic conventions that generic diff tools would corrupt.","intents":["Apply patches without breaking language-specific formatting rules or style guides","Ensure AI-generated code changes respect my project's coding conventions","Merge patches that span multiple languages in a polyglot codebase"],"best_for":["teams with strict code style requirements (linters, formatters)","polyglot projects mixing multiple programming languages","organizations where code formatting is enforced via CI/CD"],"limitations":["Language support is limited to pre-trained parsers — unsupported languages fall back to plain-text diffing","AST parsing adds 100-300ms latency per file depending on language and file size","Cannot preserve formatting if patch changes fundamental syntax structure (e.g., converting function to class)","Style preservation depends on accurate AST parsing — malformed code may fail to parse"],"requires":["Source files in supported programming languages (Python, JavaScript, TypeScript, Java, Go, C++, Rust, etc.)","Relace Apply 3 API with language detection enabled","Optional: project-specific style configuration (eslint, black, etc.)"],"input_types":["source code files (text)","unified diff patches (text)","optional: language identifier (string)","optional: style configuration files (JSON/YAML)"],"output_types":["modified source files with preserved formatting (text)","style compliance report (structured data)"],"categories":["code-generation-editing","data-processing-analysis"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"openrouter-relace-relace-apply-3__cap_6","uri":"capability://automation.workflow.incremental.patch.application.with.state.tracking","name":"incremental-patch-application-with-state-tracking","description":"Tracks the state of applied patches across multiple invocations, enabling incremental application of dependent patches and detection of previously-applied changes. Maintains a patch history log that records which patches were applied, when, and to which file versions, allowing rollback to previous states or re-application of patches to updated code.","intents":["Apply a sequence of dependent patches where later patches depend on earlier ones being applied","Detect if a patch was already applied to avoid duplicate changes","Rollback to a previous code state by unapplying patches in reverse order"],"best_for":["teams managing long-running refactoring campaigns across multiple sprints","CI/CD pipelines that need to track which AI-generated patches have been applied","developers experimenting with different patch sequences and needing to revert"],"limitations":["State tracking requires persistent storage — no built-in database, must integrate with external state store","Rollback is not guaranteed to produce clean state if files were modified outside the patch system","Patch history grows unbounded — requires manual cleanup or archival policies","No conflict detection between patches applied via different systems or manually"],"requires":["External state store for patch history (database, file system, or cloud storage)","Unique identifiers for each patch (hash, UUID, or semantic version)","Relace Apply 3 API with state tracking endpoint","Write permissions to state store"],"input_types":["unified diff patches (text)","patch metadata (ID, timestamp, dependencies)","source code files (text)"],"output_types":["patch application result with state update (structured data)","patch history log (structured data)","modified source files (text)"],"categories":["automation-workflow","memory-knowledge"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"openrouter-relace-relace-apply-3__cap_7","uri":"capability://planning.reasoning.ai.suggestion.quality.scoring.and.ranking","name":"ai-suggestion-quality-scoring-and-ranking","description":"Evaluates the quality and applicability of AI-generated code suggestions before applying them by scoring based on multiple criteria: patch syntactic validity, likelihood of successful application, estimated code quality impact, and compatibility with existing codebase style. Ranks multiple suggestions from the same or different LLMs to help developers prioritize which changes to apply first.","intents":["Understand which AI suggestions are most likely to apply cleanly and improve code quality","Compare suggestions from multiple LLMs and pick the best one","Automatically filter out low-quality or risky suggestions before applying them"],"best_for":["teams using multiple LLM providers and needing to choose between suggestions","developers wanting automated quality gates before applying AI-generated changes","CI/CD pipelines that need to accept/reject suggestions based on quality thresholds"],"limitations":["Quality scoring is heuristic-based and may not correlate with actual code quality improvements","No semantic analysis of code correctness — scoring is based on syntactic and structural metrics","Scoring weights are fixed and not customizable per project or team","Cannot detect subtle bugs or logic errors that pass syntactic validation"],"requires":["Multiple AI-generated suggestions in unified diff format","Source code files for context analysis","Relace Apply 3 API with scoring endpoint"],"input_types":["array of unified diff patches (text)","source code files (text)","optional: quality criteria weights (numeric parameters)"],"output_types":["quality scores per suggestion (numeric)","ranked list of suggestions (structured data)","scoring rationale/breakdown (text)"],"categories":["planning-reasoning","code-generation-editing"],"confidence":0.5,"matches":0,"success_rate":0}],"trust":{"score":24,"verified":false,"data_access_risk":"high","permissions":["Source files in text format (UTF-8 or compatible encoding)","Patches in unified diff format (standard output from diff/git diff tools)","API access to Relace Apply 3 via OpenRouter or direct endpoint","Write permissions to target file system","API keys or credentials for target LLM providers (OpenAI, Anthropic, etc.)","Network connectivity to OpenRouter API or direct provider endpoints","Relace Apply 3 API access via OpenRouter","Source files accessible and readable","Patches in unified diff format with valid hunk headers","Relace Apply 3 API endpoint"],"failure_modes":["Patch application fails gracefully if source file has diverged significantly from patch baseline — requires manual conflict resolution","No built-in three-way merge capability for conflicting changes from multiple sources","Performance degrades on very large files (>50MB) due to line-by-line matching overhead","Does not handle binary file patches or non-text formats","Normalization overhead adds 50-150ms latency per suggestion due to format conversion","Quality of patch application depends on upstream LLM's ability to generate valid diffs — garbage input produces garbage output","No automatic fallback or retry logic if one provider's suggestion fails to apply","Fuzzy matching heuristics may incorrectly validate patches that appear compatible but introduce subtle bugs","No semantic understanding of code — validation is purely syntactic/structural","Cannot resolve conflicts automatically; only detects and reports them","builder identity is not verified yet","no observed match outcomes yet"],"rank_breakdown":{"adoption":0.05,"quality":0.41,"ecosystem":0.24,"match_graph":0.25,"freshness":0.75,"weights":{"adoption":0.35,"quality":0.2,"ecosystem":0.1,"match_graph":0.3,"freshness":0.05}},"observed_outcomes":{"matches":0,"success_rate":0,"avg_confidence":0,"top_intents":[],"last_matched_at":null},"maintenance":{"status":"active","updated_at":"2026-05-24T12:16:24.485Z","last_scraped_at":"2026-05-03T15:20:45.776Z","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=relace-relace-apply-3","compare_url":"https://unfragile.ai/compare?artifact=relace-relace-apply-3"}},"signature":"XAwEym1dBY+t7A+KTMeZ0D413ISUfCjDOqsN21ooCFH/E9JO8BXo9pnxg+nxpKHOHVi3Yzto+s7Nj6aKb4BXAw==","signedAt":"2026-06-19T17:22:22.755Z","signedBy":"unfragile.ai","version":1},"_links":{"self":"https://unfragile.ai/api/v1/passport/relace-relace-apply-3","artifact":"https://unfragile.ai/relace-relace-apply-3","verify":"https://unfragile.ai/api/v1/verify?slug=relace-relace-apply-3","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"}}