--- name: intent-analyzer-advanced-user-intent-interpretation description: "/*============================================================================*/ /* WHEN-ANALYZING-USER-INTENT-USE-INTENT-ANALYZER SKILL :: VERILINGUA x VERIX EDITION */ /*============================================================================*/" --- /*============================================================================*/ /* WHEN-ANALYZING-USER-INTENT-USE-INTENT-ANALYZER SKILL :: VERILINGUA x VERIX EDITION */ /*============================================================================*/ --- name: when-analyzing-user-intent-use-intent-analyzer version: 1.0.0 description: | [assert|neutral] Advanced intent interpretation system using cognitive science principles and probabilistic intent mapping [ground:given] [conf:0.95] [state:confirmed] category: utilities tags: - intent-analysis - cognitive-science - disambiguation - user-understanding author: ruv cognitive_frame: primary: honorific goal_analysis: first_order: "Execute when-analyzing-user-intent-use-intent-analyzer workflow" second_order: "Ensure quality and consistency" third_order: "Enable systematic utilities processes" --- /*----------------------------------------------------------------------------*/ /* S0 META-IDENTITY */ /*----------------------------------------------------------------------------*/ [define|neutral] SKILL := { name: "when-analyzing-user-intent-use-intent-analyzer", category: "utilities", version: "1.0.0", layer: L1 } [ground:given] [conf:1.0] [state:confirmed] /*----------------------------------------------------------------------------*/ /* S1 COGNITIVE FRAME */ /*----------------------------------------------------------------------------*/ [define|neutral] COGNITIVE_FRAME := { frame: "Honorific", source: "Japanese", force: "Who is the audience?" } [ground:cognitive-science] [conf:0.92] [state:confirmed] ## Kanitsal Cerceve (Evidential Frame Activation) Kaynak dogrulama modu etkin. /*----------------------------------------------------------------------------*/ /* S2 TRIGGER CONDITIONS */ /*----------------------------------------------------------------------------*/ [define|neutral] TRIGGER_POSITIVE := { keywords: ["when-analyzing-user-intent-use-intent-analyzer", "utilities", "workflow"], context: "user needs when-analyzing-user-intent-use-intent-analyzer capability" } [ground:given] [conf:1.0] [state:confirmed] /*----------------------------------------------------------------------------*/ /* S3 CORE CONTENT */ /*----------------------------------------------------------------------------*/ # Intent Analyzer - Advanced User Intent Interpretation ## Kanitsal Cerceve (Evidential Frame Activation) Kaynak dogrulama modu etkin. ## Overview Advanced intent interpretation system that analyzes user requests using cognitive science principles and extrapolates logical volition. Use when user requests are ambiguous, when deeper understanding would improve response quality, or when helping users clarify what they truly need. ## When to Use This Skill - User request is vague or ambiguous - Multiple interpretations are possible - High-stakes decision requires clarity - User may not know exactly what they need - Complex requirements need decomposition - Implicit assumptions need surfacing ## Theoretical Foundation ### Cognitive Science Principles 1. **Probabilistic Intent Mapping**: Assign likelihood scores to possible interpretations 2. **First Principles Decomposition**: Break complex requests into fundamental components 3. **Socratic Clarification**: Ask targeted questions to narrow possibilities 4. **Context Integration**: Leverage environment and history for disambiguation 5. **Volition Extrapolation**: Infer underlying goals beyond stated request ### Evidence-Based Patterns - **Self-Consistency**: Generate multiple interpretations and find consensus - **Chain-of-Thought**: Trace reasoning from input to understanding - **Program-of-Thought**: Structure analysis as executable logic - **Plan-and-Solve**: Decompose understanding into steps ## Phase 1: Capture User Input ### Objective Gather complete user request with full context ### Agent Coordination ```bash # Pre-task hook npx claude-flow@alpha hooks pre-task \ --description "Capture user input for intent analysis" \ --complexity "low" \ --expected-duration "2min" # Session restore npx claude-flow@alpha hooks session-restore \ --session-id "intent-analyzer-${TIMESTAMP}" ``` ### Implementation **Step 1.1: Extract Raw Input** ```javascript const userInput = { request: "[User's exact words]", context: { environment: process.env, workingDirectory: process.cwd(), recentHistory: [] // Last 5 interactions }, timestamp: new Date().toISOString() }; // Store in memory await memory.store('intent/raw-input', userInput); ``` **Step 1.2: Identify Input Characteristics** ```javascript const characteristics = { length: userInput.request.split(' ').length, hasMultipleParts: /and|then|also|additionally/i.test(userInput.request), containsQuestions: /\?/.test(userInput.request), specificityScore: calculateSpecificity(userInput.request), domainIndicators: extractDomains(userInput.request) }; await memory.store('intent/characteristics', characteristics); ``` **Step 1.3: Gather Context Clues** ```javascript const contextClues = { fileSystem: await analyzeFileSystem(), recentEdits: await getRecentEdits(), projectType: await inferProjectType(), userExpertise: await estimateExpertiseLevel() }; await memory.store('intent/context-clues', contextClues); ``` ### Validation Criteria - [ ] Complete user request captured - [ ] Context information gathered - [ ] Characteristics identified - [ ] Memory storage confirmed ### Memory Pattern ```bash # Store phase completion npx claude-flow@alpha hooks post-edit \ --file "memory://intent/raw-input" \ --memory-key "intent-analyzer/phase1/completion" ``` ## Phase 2: Decompose Intent ### Objective Break down request into fundamental components using first principles ### Agent: Researcher **Step 2.1: Tokenize Request** ```javascript const tokens = { actions: extractActionVerbs(userInput.request), subjects: extractSubjects(userInput.request), constraints: extractConstraints(userInput.request), outcomes: extractDesiredOutcomes(userInput.request) }; // Example output: // { // actions: ['create', 'optimize', 'test'], // subjects: ['API', 'database', 'authentication'], // constraints: ['must be secure', 'under 100ms'], // outcomes: ['production-ready', 'scalable'] // } ``` * /*----------------------------------------------------------------------------*/ /* S4 SUCCESS CRITERIA */ /*----------------------------------------------------------------------------*/ [define|neutral] SUCCESS_CRITERIA := { primary: "Skill execution completes successfully", quality: "Output meets quality thresholds", verification: "Results validated against requirements" } [ground:given] [conf:1.0] [state:confirmed] /*----------------------------------------------------------------------------*/ /* S5 MCP INTEGRATION */ /*----------------------------------------------------------------------------*/ [define|neutral] MCP_INTEGRATION := { memory_mcp: "Store execution results and patterns", tools: ["mcp__memory-mcp__memory_store", "mcp__memory-mcp__vector_search"] } [ground:witnessed:mcp-config] [conf:0.95] [state:confirmed] /*----------------------------------------------------------------------------*/ /* S6 MEMORY NAMESPACE */ /*----------------------------------------------------------------------------*/ [define|neutral] MEMORY_NAMESPACE := { pattern: "skills/utilities/when-analyzing-user-intent-use-intent-analyzer/{project}/{timestamp}", store: ["executions", "decisions", "patterns"], retrieve: ["similar_tasks", "proven_patterns"] } [ground:system-policy] [conf:1.0] [state:confirmed] [define|neutral] MEMORY_TAGGING := { WHO: "when-analyzing-user-intent-use-intent-analyzer-{session_id}", WHEN: "ISO8601_timestamp", PROJECT: "{project_name}", WHY: "skill-execution" } [ground:system-policy] [conf:1.0] [state:confirmed] /*----------------------------------------------------------------------------*/ /* S7 SKILL COMPLETION VERIFICATION */ /*----------------------------------------------------------------------------*/ [direct|emphatic] COMPLETION_CHECKLIST := { agent_spawning: "Spawn agents via Task()", registry_validation: "Use registry agents only", todowrite_called: "Track progress with TodoWrite", work_delegation: "Delegate to specialized agents" } [ground:system-policy] [conf:1.0] [state:confirmed] /*----------------------------------------------------------------------------*/ /* S8 ABSOLUTE RULES */ /*----------------------------------------------------------------------------*/ [direct|emphatic] RULE_NO_UNICODE := forall(output): NOT(unicode_outside_ascii) [ground:windows-compatibility] [conf:1.0] [state:confirmed] [direct|emphatic] RULE_EVIDENCE := forall(claim): has(ground) AND has(confidence) [ground:verix-spec] [conf:1.0] [state:confirmed] [direct|emphatic] RULE_REGISTRY := forall(agent): agent IN AGENT_REGISTRY [ground:system-policy] [conf:1.0] [state:confirmed] /*----------------------------------------------------------------------------*/ /* PROMISE */ /*----------------------------------------------------------------------------*/ [commit|confident] WHEN_ANALYZING_USER_INTENT_USE_INTENT_ANALYZER_VERILINGUA_VERIX_COMPLIANT [ground:self-validation] [conf:0.99] [state:confirmed] --- Source attribution: DNYoussef Original project: https://github.com/DNYoussef/context-cascade/blob/8c12bb178f0aab4a9c52b8645d3972e6de5e659b/skills/research/when-analyzing-user-intent-use-intent-analyzer/SKILL.md License: MIT License information: https://opensource.org/license/mit Original upstream instructions; downloaded from Dave AI. ## Upstream license notice MIT License Copyright (c) 2025 ruvnet Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. # Dave AI resource metadata Creator / publisher: DNYoussef Original project: https://github.com/DNYoussef/context-cascade/blob/8c12bb178f0aab4a9c52b8645d3972e6de5e659b/skills/research/when-analyzing-user-intent-use-intent-analyzer/SKILL.md Attribution basis: Recovered original package and original project license at a pinned revision Fields of work: Marketing, Product Management, Customer Support Roles: Content Marketer, Customer Experience, Growth Marketer, Marketing Analyst, Product Manager Specialties: API Tools: Tool not specified Country applicability: Country not specified Classification basis: Source catalog labels Instruction SHA-256: 1424091eb3bd54b7e9d88a911254c77ff2e810736ecaf2714d1f7cf7becc2aa6 Metadata reviewed: 2026-10-27 This metadata supersedes earlier Dave AI catalog attribution. Original instruction and supporting files are preserved.