{"passport":{"unfragile":{"@version":"1.0","version":"2026-05","artifact":{"id":"tool_ritual","slug":"ritual","name":"Ritual","type":"product","url":"https://www.ritual.work","page_url":"https://unfragile.ai/ritual","categories":["app-builders"],"tags":[],"pricing":{"model":"freemium","free":true,"starting_price":null},"status":"active","verified":false},"capabilities":[{"id":"tool_ritual__cap_0","uri":"capability://planning.reasoning.structured.decision.framework.templating","name":"structured-decision-framework-templating","description":"Provides pre-built decision-making templates (RACI matrices, decision trees, pros/cons frameworks) that guide users through structured problem decomposition. The system enforces a consistent schema for decision inputs, reducing cognitive load and ensuring teams capture critical context (stakeholders, constraints, timeline) before AI analysis. Templates are customizable and persist as organizational decision-making standards.","intents":["I want to standardize how my team documents decisions so we can reference them later and learn from patterns","I need a framework to ensure we're considering all stakeholders and trade-offs before committing to a decision","I want to eliminate the blank-page problem when starting a new decision discussion"],"best_for":["Mid-market product and engineering teams making frequent cross-functional decisions","Organizations with distributed teams needing async-friendly decision records","Teams transitioning from informal to documented decision-making processes"],"limitations":["Templates are generic by default—customization requires upfront investment and discipline to maintain","Framework enforcement can feel rigid for teams with highly contextual or novel decision types","No automatic detection of when a decision should be escalated or re-evaluated based on template completeness"],"requires":["Web browser with modern JavaScript support","Team account creation (freemium tier available)","Minimum 2-3 stakeholders per decision for alignment features to be effective"],"input_types":["text (problem statement, context, constraints)","structured form fields (stakeholders, timeline, decision type)"],"output_types":["structured decision record (JSON/document format)","decision matrix or RACI chart (visual/tabular)","shareable decision artifact for team reference"],"categories":["planning-reasoning","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_ritual__cap_1","uri":"capability://planning.reasoning.ai.powered.decision.recommendation.generation","name":"ai-powered-decision-recommendation-generation","description":"Analyzes structured decision inputs (problem statement, constraints, stakeholders, timeline) and generates contextual recommendations using LLM reasoning. The system synthesizes trade-offs, flags potential blind spots, and suggests decision criteria based on the template schema and historical organizational decisions. Recommendations are ranked by confidence and include reasoning chains explaining the logic.","intents":["I want AI to help me think through trade-offs and identify options I might have missed","I need to justify a decision recommendation to skeptical stakeholders with clear reasoning","I want to see how similar decisions were made in the past and apply those patterns here"],"best_for":["Teams making high-stakes decisions with multiple competing priorities","Organizations with limited decision-making experience or domain expertise","Cross-functional teams needing neutral, structured analysis to break deadlocks"],"limitations":["AI recommendations are only as good as the context provided—surface-level problem statements yield generic suggestions that don't justify premium tier","No real-time feedback loop to refine recommendations based on decision outcomes","Recommendations may reflect biases in training data or organizational historical decisions if those are used as context","Cannot account for implicit organizational politics or unstated stakeholder preferences"],"requires":["Completed decision template with minimum context (problem, constraints, stakeholders)","API access to LLM provider (OpenAI, Anthropic, or internal model)","Decision history or knowledge base for pattern matching (optional but improves quality)"],"input_types":["text (problem statement, constraints, success criteria)","structured metadata (stakeholders, timeline, decision type, budget)"],"output_types":["ranked recommendation list with confidence scores","reasoning chain explaining trade-offs","decision criteria matrix","risk/opportunity assessment"],"categories":["planning-reasoning","text-generation-language"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_ritual__cap_2","uri":"capability://automation.workflow.real.time.collaborative.voting.and.alignment","name":"real-time-collaborative-voting-and-alignment","description":"Enables asynchronous stakeholder voting on decision options with real-time visibility into preference distribution, reasoning, and dissent. The system tracks individual votes, aggregates preferences by stakeholder group (using RACI roles), and surfaces disagreement patterns that require discussion. Voting can be weighted by role or expertise, and the interface shows live vote counts and comment threads tied to specific options.","intents":["I want to quickly gauge team consensus on a decision without scheduling another meeting","I need to see which stakeholders disagree and why so we can address concerns before finalizing","I want to weight votes by expertise or decision authority rather than giving everyone equal say"],"best_for":["Distributed or async-first teams avoiding meeting fatigue","Organizations with clear decision authority structures (RACI roles)","Teams making decisions with multiple valid options and competing priorities"],"limitations":["Voting can create false consensus if stakeholders vote without reading context or reasoning","No built-in escalation mechanism if voting reveals fundamental disagreement—requires manual follow-up","Weighted voting requires upfront RACI/role definition, which adds setup friction","Voting results don't automatically resolve to a final decision—requires explicit decision-maker action"],"requires":["Team members with assigned roles or RACI designations","Web browser with real-time notification support","Minimum 2-3 stakeholders per decision for voting to be meaningful"],"input_types":["decision options (text descriptions)","stakeholder list with roles/weights","voting deadline (optional)"],"output_types":["vote aggregation dashboard (counts, percentages, by role)","dissent visualization (showing disagreement patterns)","comment threads tied to specific options","alignment report (consensus level, key concerns)"],"categories":["automation-workflow","planning-reasoning"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_ritual__cap_3","uri":"capability://memory.knowledge.decision.record.persistence.and.retrieval","name":"decision-record-persistence-and-retrieval","description":"Automatically captures and stores completed decisions as searchable, timestamped records with full context (problem statement, options considered, final choice, reasoning, stakeholders, outcome tracking). Records are indexed by decision type, stakeholder, and outcome, enabling teams to query historical decisions and identify patterns. The system supports full-text search, filtering by metadata, and linking related decisions.","intents":["I want to look up how we decided on a similar problem 6 months ago and apply that logic here","I need to audit why a particular decision was made and who approved it","I want to see if our decision-making process is improving over time (e.g., faster decisions, better outcomes)"],"best_for":["Organizations making recurring decisions across teams","Teams with high turnover needing institutional memory","Compliance-heavy industries requiring decision audit trails"],"limitations":["No automatic outcome tracking—teams must manually update decision records with results, creating maintenance burden","Search quality depends on consistent tagging and metadata—inconsistent record-keeping reduces discoverability","Historical decisions may reflect outdated context or constraints, leading to false pattern matches","No built-in mechanism to deprecate or archive decisions that are no longer relevant"],"requires":["Completed decision records with structured metadata","Consistent tagging/categorization discipline across team","Minimum 10-20 historical decisions to enable meaningful pattern detection"],"input_types":["completed decision records (structured)","search queries (text or metadata filters)","outcome updates (optional)"],"output_types":["decision record (full context with timestamps)","search results ranked by relevance","decision pattern analysis (e.g., 'decisions with X constraint tend to choose Y')","audit trail (who decided, when, with what reasoning)"],"categories":["memory-knowledge","search-retrieval"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_ritual__cap_4","uri":"capability://planning.reasoning.stakeholder.alignment.conflict.detection","name":"stakeholder-alignment-conflict-detection","description":"Monitors voting patterns, comments, and decision metadata to identify misalignment between stakeholders or roles. The system flags when key decision-makers disagree, when a stakeholder's concerns are unaddressed, or when voting patterns suggest insufficient context. Conflicts are surfaced with severity levels and recommended resolution actions (e.g., 'schedule discussion with Finance and Product', 'provide additional context on constraint X').","intents":["I want to know if there's hidden disagreement that will cause problems after we decide","I need to identify which stakeholders have concerns that haven't been addressed","I want to catch misalignment early before we commit to a decision"],"best_for":["Cross-functional teams with competing priorities (Product, Engineering, Finance)","Organizations with distributed decision authority where misalignment is costly","Teams making high-stakes decisions where stakeholder buy-in is critical"],"limitations":["Conflict detection is pattern-based and may flag false positives (e.g., healthy debate vs. fundamental disagreement)","Cannot detect implicit or political disagreement—only surfaces explicit voting/comment patterns","Recommended resolution actions are generic and may not address root causes of misalignment","Requires sufficient voting/comment activity to detect patterns—sparse participation reduces signal quality"],"requires":["Minimum 3+ stakeholders with assigned roles","Active voting or commenting on decision options","Clear RACI or role definitions to identify key decision-makers"],"input_types":["voting patterns (by stakeholder and role)","comment threads and reasoning","stakeholder metadata (role, expertise, decision authority)"],"output_types":["conflict alert (severity level, affected stakeholders)","misalignment summary (which options/constraints are contested)","recommended resolution actions","alignment score (0-100 indicating consensus level)"],"categories":["planning-reasoning","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_ritual__cap_5","uri":"capability://data.processing.analysis.decision.outcome.tracking.and.learning.loops","name":"decision-outcome-tracking-and-learning-loops","description":"Enables teams to record decision outcomes (success/failure, actual vs. expected results, lessons learned) and correlate them with past decisions to identify patterns in decision quality. The system tracks whether decisions achieved their stated success criteria, captures post-decision reflections, and surfaces insights like 'decisions made with X stakeholder group have 20% higher success rate' or 'decisions with incomplete constraint documentation tend to fail'. Outcomes feed back into recommendation generation to improve future suggestions.","intents":["I want to know if our decisions are actually working out or if we're making the same mistakes repeatedly","I need to identify which decision-making processes or stakeholder groups produce better outcomes","I want to use past decision outcomes to improve AI recommendations for future decisions"],"best_for":["Organizations making frequent, similar decisions where learning loops compound value","Teams with strong retrospective culture and discipline to track outcomes","Decision-heavy domains (product strategy, resource allocation, technical architecture)"],"limitations":["Outcome tracking requires manual effort and discipline—teams often abandon this after initial setup","Outcomes are subjective and hard to measure objectively (e.g., 'was this decision successful?')","Correlation between decision process and outcomes is confounded by external factors (market changes, execution quality)","Requires 50+ historical decisions with outcomes to enable statistically meaningful pattern detection","Feedback loops are slow—outcomes may take weeks or months to materialize, delaying learning"],"requires":["Completed decisions with clear success criteria defined upfront","Discipline to update decision records with outcomes after 30-90 days","Minimum 20-30 historical decisions with outcome data to enable pattern detection"],"input_types":["outcome assessment (success/failure, actual results vs. expected)","lessons learned (text reflection)","external factors that influenced outcome (optional)"],"output_types":["outcome report (success rate, time to decision, stakeholder satisfaction)","pattern analysis (e.g., 'decisions with X characteristic have Y% success rate')","learning insights (e.g., 'incomplete constraint documentation correlates with 30% failure rate')","feedback to recommendation engine (improving future suggestions)"],"categories":["data-processing-analysis","planning-reasoning"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_ritual__cap_6","uri":"capability://data.processing.analysis.organizational.decision.pattern.analysis","name":"organizational-decision-pattern-analysis","description":"Analyzes aggregated decision history to identify organizational patterns: which decision types are most common, how long decisions typically take, which stakeholder groups are most frequently involved, and whether certain decision patterns correlate with better outcomes. The system generates reports on decision velocity, stakeholder participation, and decision quality trends over time. Patterns can be filtered by team, decision type, or time period.","intents":["I want to understand how my organization makes decisions and identify bottlenecks or inefficiencies","I need to benchmark our decision-making speed and quality against industry standards or past performance","I want to see which teams or stakeholders are involved in most decisions and identify over-reliance on key people"],"best_for":["Leadership teams optimizing organizational decision-making processes","Organizations scaling and needing to standardize decision practices","Teams conducting process improvement initiatives focused on decision velocity"],"limitations":["Pattern analysis requires 100+ historical decisions to be statistically meaningful—early-stage teams won't see useful insights","Patterns may reflect organizational dysfunction (e.g., slow decisions because of excessive stakeholder involvement) rather than best practices","Correlation between decision patterns and outcomes is confounded by execution quality, market conditions, and other external factors","No built-in mechanism to act on insights—requires manual process redesign to improve decision-making"],"requires":["Minimum 50-100 historical decisions with complete metadata and outcomes","Consistent tagging and categorization across all decisions","Stakeholder role definitions to enable participation analysis"],"input_types":["aggregated decision records (metadata, outcomes, stakeholders)","time period filters (optional)","team or decision-type filters (optional)"],"output_types":["decision velocity report (average time to decision by type)","stakeholder participation analysis (who's involved in which decisions)","decision quality metrics (success rate, outcome satisfaction)","trend analysis (improving/declining decision quality over time)","bottleneck identification (which decision types are slowest)"],"categories":["data-processing-analysis","planning-reasoning"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_ritual__cap_7","uri":"capability://automation.workflow.customizable.decision.workflow.automation","name":"customizable-decision-workflow-automation","description":"Allows teams to define custom workflows that automate decision routing, notification, and escalation based on decision type, stakeholder involvement, or urgency. Workflows can specify: who must be notified, voting deadlines, escalation triggers (e.g., 'if no consensus after 48 hours, escalate to VP'), and post-decision actions (e.g., 'create Jira tickets for implementation'). Workflows are template-based and can be reused across similar decision types.","intents":["I want to automate the routine parts of decision-making (notifications, voting deadlines, escalation) so we can focus on the hard thinking","I need different decision workflows for different types of decisions (e.g., fast-track for low-risk, formal for high-stakes)","I want to automatically trigger follow-up actions (like creating implementation tasks) after a decision is made"],"best_for":["Organizations with high decision volume and clear decision governance","Teams with repeating decision patterns that benefit from standardized workflows","Organizations integrating Ritual with other tools (Jira, Slack, email) for end-to-end automation"],"limitations":["Workflow definition requires upfront investment and technical understanding—non-technical users may struggle","Workflows are rigid and may not adapt to edge cases or novel decision types","Escalation triggers can create false escalations if thresholds are poorly calibrated","No built-in integration with external tools (Jira, Slack, email)—requires custom webhooks or API calls","Workflows don't account for implicit organizational politics or unstated decision criteria"],"requires":["Clear decision governance and stakeholder roles defined upfront","API access to external tools if integrating with Jira, Slack, or email","Minimum 3-5 repeating decision types to justify workflow setup effort"],"input_types":["workflow definition (decision type, stakeholders, voting deadline, escalation rules)","decision metadata (type, urgency, stakeholders)"],"output_types":["automated notifications (to stakeholders)","voting deadline enforcement","escalation alerts (if thresholds triggered)","post-decision action triggers (e.g., Jira ticket creation)"],"categories":["automation-workflow","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_ritual__cap_8","uri":"capability://text.generation.language.ai.powered.decision.summarization.and.briefing","name":"ai-powered-decision-summarization-and-briefing","description":"Automatically generates concise summaries of complex decisions for stakeholders who need to understand the outcome but not the full deliberation. Summaries include: the decision made, key trade-offs considered, why alternatives were rejected, and implementation implications. The system can generate summaries at different detail levels (executive brief vs. technical deep-dive) and in different formats (text, slides, video transcript). Summaries are generated from decision records and can be shared with non-participants.","intents":["I need to brief executives on a decision without making them read through all the voting and discussion","I want to explain to the broader team why we chose option A over option B","I need to document a decision for compliance or audit purposes in a concise format"],"best_for":["Organizations with large teams where decisions need to be communicated broadly","Compliance-heavy industries requiring decision documentation","Distributed teams where not everyone participates in every decision"],"limitations":["Summaries are generated from structured decision records—if context is missing or poorly documented, summaries will be superficial","AI-generated summaries may omit important nuances or stakeholder concerns","Different stakeholders may need different summary angles (e.g., Finance cares about cost, Engineering cares about implementation), but system generates generic summaries","Summaries don't capture implicit reasoning or political context that influenced the decision"],"requires":["Completed decision record with structured metadata and reasoning","API access to LLM provider for summary generation","Optional: stakeholder feedback to refine summary quality"],"input_types":["decision record (full context, voting, comments)","summary detail level (executive brief, technical, etc.)","target audience (optional)"],"output_types":["text summary (1-2 paragraphs)","detailed brief (1-2 pages with trade-offs and rationale)","slide deck (visual summary with key points)","FAQ (addressing common questions about the decision)"],"categories":["text-generation-language","planning-reasoning"],"confidence":0.5,"matches":0,"success_rate":0}],"trust":{"score":41,"verified":false,"data_access_risk":"high","permissions":["Web browser with modern JavaScript support","Team account creation (freemium tier available)","Minimum 2-3 stakeholders per decision for alignment features to be effective","Completed decision template with minimum context (problem, constraints, stakeholders)","API access to LLM provider (OpenAI, Anthropic, or internal model)","Decision history or knowledge base for pattern matching (optional but improves quality)","Team members with assigned roles or RACI designations","Web browser with real-time notification support","Minimum 2-3 stakeholders per decision for voting to be meaningful","Completed decision records with structured metadata"],"failure_modes":["Templates are generic by default—customization requires upfront investment and discipline to maintain","Framework enforcement can feel rigid for teams with highly contextual or novel decision types","No automatic detection of when a decision should be escalated or re-evaluated based on template completeness","AI recommendations are only as good as the context provided—surface-level problem statements yield generic suggestions that don't justify premium tier","No real-time feedback loop to refine recommendations based on decision outcomes","Recommendations may reflect biases in training data or organizational historical decisions if those are used as context","Cannot account for implicit organizational politics or unstated stakeholder preferences","Voting can create false consensus if stakeholders vote without reading context or reasoning","No built-in escalation mechanism if voting reveals fundamental disagreement—requires manual follow-up","Weighted voting requires upfront RACI/role definition, which adds setup friction","builder identity is not verified yet","no observed match outcomes yet"],"rank_breakdown":{"adoption":0.36666666666666664,"quality":0.7300000000000001,"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":"2026-05-24T12:16:33.095Z","last_scraped_at":"2026-04-05T13:23:42.551Z","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=ritual","compare_url":"https://unfragile.ai/compare?artifact=ritual"}},"signature":"zL9HpOo6dq08dbqFsJvVTuXEHlKYSOAtlkgv52h06bHcFXY7OXnQxCvaVGi/l2E6vL6XXuNjhpbP8IiuWx1SAQ==","signedAt":"2026-06-22T10:37:56.815Z","signedBy":"unfragile.ai","version":1},"_links":{"self":"https://unfragile.ai/api/v1/passport/ritual","artifact":"https://unfragile.ai/ritual","verify":"https://unfragile.ai/api/v1/verify?slug=ritual","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"}}