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The model generates explicit reasoning traces while dynamically deciding when to invoke Perplexity's search API to ground reasoning in current information, enabling multi-step problem decomposition with real-time fact verification.","intents":["I need to solve a complex multi-step problem that requires both reasoning and current information","I want to verify claims during reasoning rather than after generating an answer","I need transparent reasoning traces that show how the model arrived at conclusions"],"best_for":["researchers and analysts requiring fact-grounded reasoning","developers building reasoning-heavy AI agents that need current information","teams solving complex problems where intermediate verification is critical"],"limitations":["CoT reasoning adds latency — typical response times 10-30 seconds for complex queries","Search integration increases per-request costs compared to pure reasoning models","Reasoning traces are verbose and not optimized for low-bandwidth contexts","No control over search query generation — model decides autonomously when to search"],"requires":["Perplexity API key with Sonar Reasoning Pro access","HTTP/2 capable client for streaming reasoning tokens","Tolerance for variable latency based on search query complexity"],"input_types":["text prompts","multi-turn conversation context","structured queries with domain context"],"output_types":["text with embedded reasoning traces","structured reasoning steps with citations","search queries executed during reasoning"],"categories":["planning-reasoning","search-retrieval"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"openrouter-perplexity-sonar-reasoning-pro__cap_1","uri":"capability://search.retrieval.real.time.web.search.with.semantic.ranking","name":"real-time web search with semantic ranking","description":"Executes live web searches through Perplexity's proprietary search infrastructure, returning ranked results based on semantic relevance to the query rather than link popularity. Results are integrated into reasoning context with source attribution, enabling the model to cite specific URLs and passages when answering questions.","intents":["I need current information about recent events or rapidly changing topics","I want answers with verifiable sources and citations","I need to search across multiple domains simultaneously"],"best_for":["news analysis and current events research","fact-checking and verification workflows","applications requiring source attribution and transparency"],"limitations":["Search results depend on Perplexity's crawler coverage — some niche or paywalled content may be unavailable","Semantic ranking may deprioritize authoritative sources if they use different terminology","No control over search result freshness — cached results may be hours old","Search queries are generated by the model, not user-controlled"],"requires":["Active internet connectivity for search execution","Perplexity API key with search quota","Acceptance of Perplexity's search terms and content policies"],"input_types":["natural language queries","domain-specific search terms","follow-up questions in conversation context"],"output_types":["ranked search results with snippets","source URLs with passage citations","structured metadata (publication date, domain authority)"],"categories":["search-retrieval","memory-knowledge"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"openrouter-perplexity-sonar-reasoning-pro__cap_2","uri":"capability://memory.knowledge.multi.turn.conversation.with.persistent.reasoning.context","name":"multi-turn conversation with persistent reasoning context","description":"Maintains conversation state across multiple turns, allowing the model to reference previous reasoning steps, search results, and conclusions without re-executing searches or re-reasoning from scratch. The model can build on prior context to refine answers or explore tangential questions while preserving the reasoning chain.","intents":["I want to ask follow-up questions that build on previous reasoning","I need the model to remember what it searched for and verified earlier","I want to explore multiple angles of a problem without losing context"],"best_for":["interactive research and analysis workflows","iterative problem-solving sessions","educational and tutoring applications"],"limitations":["Context window is finite — very long conversations will lose early reasoning traces","Each turn still incurs search costs if the model decides to search again","No explicit memory mechanism — context is limited to the conversation window","Model may re-search for information already found in earlier turns"],"requires":["Stateful client implementation to maintain conversation history","Session management to track conversation ID across API calls","Sufficient token budget for multi-turn interactions"],"input_types":["follow-up text queries","clarifications and refinements","requests to explore related topics"],"output_types":["contextually aware responses","references to prior reasoning steps","incremental reasoning traces"],"categories":["memory-knowledge","planning-reasoning"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"openrouter-perplexity-sonar-reasoning-pro__cap_3","uri":"capability://data.processing.analysis.structured.extraction.with.reasoning.validation","name":"structured extraction with reasoning validation","description":"Extracts structured data (JSON, tables, key-value pairs) from unstructured text or search results while using chain-of-thought reasoning to validate the extraction logic. The model explicitly reasons about which fields are present, how to handle missing data, and whether the extraction is complete before returning structured output.","intents":["I need to extract structured data from web search results with high confidence","I want to validate that extracted data is consistent and complete","I need to handle ambiguous or incomplete source data gracefully"],"best_for":["data pipeline builders extracting information from web sources","researchers aggregating structured data from unstructured documents","applications requiring high-confidence data extraction"],"limitations":["Reasoning overhead adds 5-15 seconds per extraction task","No schema validation — model must be prompted with expected structure","Extraction quality depends on source data clarity — ambiguous sources may produce inconsistent results","No built-in retry or fallback mechanism for failed extractions"],"requires":["Clear prompt specification of desired output structure","Tolerance for variable extraction quality based on source data","JSON parsing capability on the client side"],"input_types":["unstructured text","web search results","semi-structured documents"],"output_types":["JSON objects","CSV/tabular data","key-value pairs with reasoning annotations"],"categories":["data-processing-analysis","planning-reasoning"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"openrouter-perplexity-sonar-reasoning-pro__cap_4","uri":"capability://safety.moderation.fact.checking.with.source.verification","name":"fact-checking with source verification","description":"Evaluates claims by searching for supporting or contradicting evidence, then reasoning about the credibility of sources and the strength of evidence. The model generates explicit reasoning about source reliability, potential biases, and the confidence level of its fact-check conclusion, with full citation trails.","intents":["I need to verify whether a claim is accurate or misleading","I want to understand the evidence for and against a statement","I need to identify potential biases in sources"],"best_for":["misinformation detection and fact-checking workflows","content moderation and verification teams","researchers validating claims in academic or journalistic contexts"],"limitations":["Fact-checking quality depends on search result availability — some claims may lack sufficient evidence online","Model reasoning about source credibility is heuristic-based, not authoritative","No access to paywalled or subscription-only sources","Reasoning traces may be verbose and require human interpretation"],"requires":["Clear specification of the claim to be fact-checked","Acceptance that fact-checking is probabilistic, not deterministic","Human review of reasoning traces for high-stakes decisions"],"input_types":["text claims or statements","URLs to articles containing claims","multi-sentence passages"],"output_types":["fact-check verdict (true/false/mixed/unverifiable)","reasoning trace with evidence citations","confidence scores per claim component"],"categories":["safety-moderation","search-retrieval","planning-reasoning"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"openrouter-perplexity-sonar-reasoning-pro__cap_5","uri":"capability://data.processing.analysis.comparative.analysis.with.multi.source.synthesis","name":"comparative analysis with multi-source synthesis","description":"Searches for information about multiple entities or concepts simultaneously, then reasons about similarities, differences, and trade-offs by synthesizing evidence from multiple sources. The model generates explicit comparisons with source attribution for each claim, enabling transparent side-by-side analysis.","intents":["I need to compare multiple products, services, or concepts objectively","I want to understand trade-offs between different approaches","I need to synthesize information from multiple sources into a coherent comparison"],"best_for":["product research and competitive analysis","decision-making frameworks for teams evaluating options","educational content comparing concepts or approaches"],"limitations":["Search results may have uneven coverage across compared entities","Reasoning about trade-offs is subjective and may reflect model biases","No built-in weighting mechanism for source importance or recency","Comparison quality depends on search result diversity"],"requires":["Clear specification of entities or concepts to compare","Acceptance that comparisons are based on available search results","Tolerance for potential gaps in coverage"],"input_types":["list of entities to compare","comparison criteria or dimensions","context about use case or decision"],"output_types":["structured comparison tables","narrative analysis with citations","trade-off matrices with reasoning"],"categories":["data-processing-analysis","search-retrieval","planning-reasoning"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"openrouter-perplexity-sonar-reasoning-pro__cap_6","uri":"capability://code.generation.editing.code.explanation.and.debugging.with.web.context","name":"code explanation and debugging with web context","description":"Analyzes code snippets or error messages, searches for relevant documentation and Stack Overflow discussions, then generates explanations or debugging suggestions grounded in current best practices and community solutions. The model reasons about the root cause while citing relevant external resources.","intents":["I need to understand what a code snippet does and why it might be problematic","I'm debugging an error and want solutions from current documentation and community discussions","I need to learn best practices for a specific programming task"],"best_for":["developers learning new languages or frameworks","debugging workflows where current documentation is critical","code review and knowledge-sharing in teams"],"limitations":["Search results may include outdated or deprecated solutions","Model reasoning about code correctness is heuristic-based, not verified","No execution environment — cannot test code suggestions","Search coverage varies by language and framework popularity"],"requires":["Code snippet or error message as input","Acceptance that suggestions should be validated before use","Familiarity with the programming language or framework"],"input_types":["code snippets","error messages and stack traces","programming questions"],"output_types":["explanations with documentation links","debugging suggestions with reasoning","best practice recommendations"],"categories":["code-generation-editing","search-retrieval","planning-reasoning"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"openrouter-perplexity-sonar-reasoning-pro__cap_7","uri":"capability://search.retrieval.research.synthesis.with.citation.tracking","name":"research synthesis with citation tracking","description":"Searches for academic papers, articles, and reports on a topic, then synthesizes findings into a coherent narrative while maintaining explicit citation trails for each claim. The model reasons about the strength of evidence, identifies consensus vs. disagreement in sources, and flags areas of uncertainty.","intents":["I need to understand the current state of research on a topic","I want a literature review with proper citations and evidence assessment","I need to identify gaps or disagreements in existing research"],"best_for":["researchers conducting literature reviews","students writing research papers","teams synthesizing knowledge across multiple sources"],"limitations":["Search coverage is limited to publicly available sources — paywalled academic papers may be inaccessible","Citation formatting is not standardized — may require manual adjustment for specific citation styles","No access to specialized academic databases (PubMed, JSTOR, etc.)","Reasoning about research quality is heuristic-based, not peer-reviewed"],"requires":["Clear research question or topic","Acceptance that synthesis is based on available search results","Manual verification of citations and claims"],"input_types":["research topics or questions","keywords or author names","date ranges for filtering results"],"output_types":["narrative synthesis with citations","structured literature review","evidence assessment with confidence levels"],"categories":["search-retrieval","data-processing-analysis","planning-reasoning"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"openrouter-perplexity-sonar-reasoning-pro__cap_8","uri":"capability://planning.reasoning.decision.making.support.with.multi.factor.analysis","name":"decision-making support with multi-factor analysis","description":"Helps evaluate complex decisions by searching for relevant information about each option, reasoning about multiple factors (cost, risk, timeline, etc.), and synthesizing trade-offs into a structured analysis. The model generates explicit reasoning about decision criteria and their relative importance.","intents":["I need to make a complex decision and want to consider all relevant factors","I want to understand the trade-offs between different options","I need a structured framework for evaluating alternatives"],"best_for":["business decision-making and strategy teams","product managers evaluating feature or vendor options","individuals making significant personal or professional decisions"],"limitations":["Decision recommendations are based on available information — may miss critical factors","Model reasoning about importance of factors is heuristic-based, not personalized","No built-in mechanism for incorporating user preferences or constraints","Final decision remains the user's responsibility"],"requires":["Clear specification of decision options and criteria","Acceptance that analysis is advisory, not prescriptive","Domain knowledge to validate reasoning and recommendations"],"input_types":["decision options or alternatives","evaluation criteria","constraints or preferences"],"output_types":["structured decision matrices","trade-off analysis with reasoning","recommendations with confidence levels"],"categories":["planning-reasoning","search-retrieval","data-processing-analysis"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"openrouter-perplexity-sonar-reasoning-pro__cap_9","uri":"capability://code.generation.editing.technical.documentation.generation.with.current.api.references","name":"technical documentation generation with current api references","description":"Generates technical documentation by searching for current API specifications, code examples, and best practices, then synthesizing them into coherent documentation with proper citations. The model reasons about completeness and accuracy while generating examples grounded in current library versions.","intents":["I need to generate documentation for an API or library","I want examples that work with current versions of dependencies","I need to ensure documentation reflects current best practices"],"best_for":["open-source maintainers documenting projects","teams generating internal API documentation","developers creating tutorials or guides"],"limitations":["Generated documentation may contain inaccuracies or outdated examples","No verification that examples actually work — requires testing","Search results may not cover all API endpoints or features","Documentation structure is generated, not customized to project conventions"],"requires":["Clear specification of what to document","Manual review and testing of generated examples","Acceptance that output requires editing before publication"],"input_types":["API specifications or code","documentation structure or outline","target audience or use cases"],"output_types":["markdown or HTML documentation","code examples with explanations","API reference tables"],"categories":["code-generation-editing","search-retrieval","text-generation-language"],"confidence":0.5,"matches":0,"success_rate":0}],"trust":{"score":27,"verified":false,"data_access_risk":"low","permissions":["Perplexity API key with Sonar Reasoning Pro access","HTTP/2 capable client for streaming reasoning tokens","Tolerance for variable latency based on search query complexity","Active internet connectivity for search execution","Perplexity API key with search quota","Acceptance of Perplexity's search terms and content policies","Stateful client implementation to maintain conversation history","Session management to track conversation ID across API calls","Sufficient token budget for multi-turn interactions","Clear prompt specification of desired output structure"],"failure_modes":["CoT reasoning adds latency — typical response times 10-30 seconds for complex queries","Search integration increases per-request costs compared to pure reasoning models","Reasoning traces are verbose and not optimized for low-bandwidth contexts","No control over search query generation — model decides autonomously when to search","Search results depend on Perplexity's crawler coverage — some niche or paywalled content may be unavailable","Semantic ranking may deprioritize authoritative sources if they use different terminology","No control over search result freshness — cached results may be hours old","Search queries are generated by the model, not user-controlled","Context window is finite — very long conversations will lose early reasoning traces","Each turn still incurs search costs if the model decides to search again","builder identity is not verified yet","no observed match outcomes yet"],"rank_breakdown":{"adoption":0.05,"quality":0.55,"ecosystem":0.27,"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=perplexity-sonar-reasoning-pro","compare_url":"https://unfragile.ai/compare?artifact=perplexity-sonar-reasoning-pro"}},"signature":"IH73bGsMvRUckvjwMryBUONAlWRg8+8EGlcBvvHoaDli7sgbelEhRWceTlpN6AEC6o/ZwiMvhRlRhcUCVqsECA==","signedAt":"2026-06-19T22:23:23.193Z","signedBy":"unfragile.ai","version":1},"_links":{"self":"https://unfragile.ai/api/v1/passport/perplexity-sonar-reasoning-pro","artifact":"https://unfragile.ai/perplexity-sonar-reasoning-pro","verify":"https://unfragile.ai/api/v1/verify?slug=perplexity-sonar-reasoning-pro","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"}}