when-analyzing-user-intent-use-intent-analyzer
Advanced intent interpretation system using cognitive science principles and probabilistic intent mapping
Profile →npx skills add majiayu000/claude-skill-registry --skill when-analyzing-user-intent-use-intent-analyzer-dnyoussef-ai-chro --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
What it does
Defines an intent analysis workflow that captures user input, decomposes it into components, maps possible interpretations with probabilities, clarifies ambiguities via targeted questions, and synthesizes a final actionable understanding with an execution brief. It expects to coordinate with claude-flow@alpha and hooks-integration, and supports producing an interpreted intent document, clarifying questions, and an action plan.
How it works
Phase 1 captures the user request and context, stores raw input and derived characteristics, and prepares context clues using pre-task hooks and memory storage. Phase 2 decomposes the request into components, builds a component tree, and identifies dependencies (sequential, parallel, conditional). Phase 3 generates interpretations, applies Bayesian reasoning to update probabilities, and ranks interpretations by confidence. Phase 4 identifies high-impact ambiguities, generates and prioritizes clarifying questions, formats them for user presentation, and updates interpretations based on responses. Phase 5 synthesizes understanding by selecting the final interpretation, creating an execution brief with metadata and an action plan, and optionally handing off to execution when confidence is high.
When to use it
Use when the user request is vague or ambiguous, when multiple interpretations are possible, for high-stakes or complex requirements, or when implicit assumptions need surfacing.
What it can touch
The skill references tools and commands such as:
- "npx claude-flow@alpha" commands for hooks, agent-spawn, and memory storage
- memory storage keys like "intent/raw-input", "intent/characteristics", "intent/component-tree", "intent/interpretations", and related keys throughout phases
- files and scripts for memory and output handling are shown in the steps and memory patterns
Caveats
Relies on memory storage and simulated agent interactions via claude-flow; outcomes depend on user responses and probabilistic reasoning; no guarantees of exact interpretation, only probabilistic rankings and structured clarifications.
# Intent Analyzer - Advanced User Intent Interpretation ## 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 - **
- Overview
- When to Use This Skill
- Theoretical Foundation
- Cognitive Science Principles
- Evidence-Based Patterns
- Phase 1: Capture User Input
- Objective
- Agent Coordination
- Implementation
- Validation Criteria
- Memory Pattern
- Phase 2: Decompose Intent
- Agent: Researcher
- Script Template
Pre-task hook npx claude-flow@alpha hooks pre-task \ Session restore npx claude-flow@alpha hooks session-restore \ Store phase completion npx claude-flow@alpha hooks post-edit \ decompose-intent.sh Read user input Decompose using researcher agent npx claude-flow@alpha agent-spawn \
What does the when-analyzing-user-intent-use-intent-analyzer skill do?
Advanced intent interpretation system using cognitive science principles and probabilistic intent mapping
How do I install it?
Run `npx skills add majiayu000/claude-skill-registry --skill when-analyzing-user-intent-use-intent-analyzer-dnyoussef-ai-chro --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From majiayu000/claude-skill-registry, a repository with 534 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.