/============================================================================/ /* SLASH-COMMAND-ENCODER SKILL :: VERILINGUA x VERIX EDITION / /============================================================================*/
name: slash-command-encoder version: 2.0.0 description: | [assert|neutral] Creates ergonomic slash commands (/command) that provide fast, unambiguous access to micro-skills, cascades, and agents. Enhanced with auto-discovery, intelligent routing, parameter validation, and co [ground:given] [conf:0.95] [state:confirmed] category: orchestration tags:
- commands
- interface
- ergonomics
- auto-discovery
- composition author: ruv cognitive_frame: primary: aspectual goal_analysis: first_order: "Execute slash-command-encoder workflow" second_order: "Ensure quality and consistency" third_order: "Enable systematic orchestration processes"
/----------------------------------------------------------------------------/ /* S0 META-IDENTITY / /----------------------------------------------------------------------------*/
[define|neutral] SKILL := { name: "slash-command-encoder", category: "orchestration", version: "2.0.0", layer: L1 } [ground:given] [conf:1.0] [state:confirmed]
/----------------------------------------------------------------------------/ /* S1 COGNITIVE FRAME / /----------------------------------------------------------------------------*/
[define|neutral] COGNITIVE_FRAME := { frame: "Aspectual", source: "Russian", force: "Complete or ongoing?" } [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: ["slash-command-encoder", "orchestration", "workflow"], context: "user needs slash-command-encoder capability" } [ground:given] [conf:1.0] [state:confirmed]
/----------------------------------------------------------------------------/ /* S3 CORE CONTENT / /----------------------------------------------------------------------------*/
Orchestration Skill Guidelines
When to Use This Skill
- Multi-stage workflows requiring sequential, parallel, or conditional execution
- Complex pipelines coordinating multiple micro-skills or agents
- Iterative processes with Codex sandbox testing and auto-fix loops
- Multi-model routing requiring intelligent AI selection per stage
- Production workflows needing GitHub integration and memory persistence
When NOT to Use This Skill
- Single-agent tasks with no coordination requirements
- Simple sequential work that doesn't need stage management
- Trivial operations completing in <5 minutes
- Pure research without implementation stages
Success Criteria
- [assert|neutral] All stages complete* with 100% success rate [ground:acceptance-criteria] [conf:0.90] [state:provisional]
- [assert|neutral] Dependency resolution* with no circular dependencies [ground:acceptance-criteria] [conf:0.90] [state:provisional]
- [assert|neutral] Model routing optimal* for each stage (Gemini/Codex/Claude) [ground:acceptance-criteria] [conf:0.90] [state:provisional]
- [assert|neutral] Memory persistence* maintained across all stages [ground:acceptance-criteria] [conf:0.90] [state:provisional]
- [assert|neutral] No orphaned stages* - all stages tracked and completed [ground:acceptance-criteria] [conf:0.90] [state:provisional]
Edge Cases to Handle
- Stage failure mid-cascade - Implement retry with exponential backoff
- Circular dependencies - Validate DAG structure before execution
- Model unavailability - Have fallback model selection per stage
- Memory overflow - Implement stage result compression
- Timeout on long stages - Configure per-stage timeout limits
Guardrails (NEVER Violate)
- [assert|emphatic] NEVER: lose stage state** - Persist after each stage completion [ground:policy] [conf:0.98] [state:confirmed]
- [assert|neutral] ALWAYS: validate dependencies** - Check DAG acyclic before execution [ground:policy] [conf:0.98] [state:confirmed]
- [assert|neutral] ALWAYS: track cascade progress** - Update memory with real-time status [ground:policy] [conf:0.98] [state:confirmed]
- [assert|emphatic] NEVER: skip error handling** - Every stage needs try/catch with fallback [ground:policy] [conf:0.98] [state:confirmed]
- [assert|neutral] ALWAYS: cleanup on failure** - Release resources, clear temp state [ground:policy] [conf:0.98] [state:confirmed]
Evidence-Based Validation
- Verify stage outputs - Check actual results vs expected schema
- Validate data flow - Confirm outputs passed correctly to next stage
- Check model routing - Verify correct AI used per stage requirements
- Measure cascade performance - Track execution time vs estimates
- Audit memory usage - Ensure no memory leaks across stages
Slash Command Encoder (Enhanced)
Kanitsal Cerceve (Evidential Frame Activation)
Kaynak dogrulama modu etkin.
Overview
Creates fast, scriptable /command interfaces for micro-skills, cascades, and agents. This enhanced version includes automatic skill discovery, intelligent command generation, parameter validation, multi-model routing, and command chaining patterns.
Philosophy: Expert Efficiency
Command Line UX for AI: Expert users benefit from fast, precise, scriptable interfaces over natural language when performing repeated operations.
Enhanced Capabilities:
- Auto-Discovery: Scans and catalogs all installed skills automatically
- Intelligent Routing: Commands invoke optimal AI/agent for task
- Parameter Validation: Type-checked, auto-completed parameters
- Command Chaining: Compose commands into pipelines
- Multi-Model Integration: Direct access to Gemini/Codex via commands
Key Principles:
- Fast and unambiguous invocation
- Self-documenting through naming
- Composable and scriptable
- Type-safe parameter handling
- Muscle memory for power users
When to Create Slash Commands
✅ **Per
/----------------------------------------------------------------------------/ /* 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/orchestration/slash-command-encoder/{project}/{timestamp}", store: ["executions", "decisions", "patterns"], retrieve: ["similar_tasks", "proven_patterns"] } [ground:system-policy] [conf:1.0] [state:confirmed]
[define|neutral] MEMORY_TAGGING := { WHO: "slash-command-encoder-{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]