Agent skill

meta-loop-orchestrator

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Install this agent skill to your Project

npx add-skill https://github.com/DNYoussef/context-cascade/tree/main/skills/orchestration/meta-loop-orchestrator

SKILL.md

/============================================================================/ /* META-LOOP-ORCHESTRATOR SKILL :: VERILINGUA x VERIX EDITION / /============================================================================*/

name: meta-loop-orchestrator version: 1.0.0 description: | [assert|neutral] Orchestrates the recursive self-improvement meta loop by coordinating foundry skills (agent-creator, skill-forge, prompt-forge) with Ralph Wiggum persistence loops. Use when running recursive improvem [ground:given] [conf:0.95] [state:confirmed] category: orchestration tags:

  • orchestration
  • meta-loop
  • recursive-improvement
  • foundry
  • ralph-wiggum author: Context Cascade cognitive_frame: primary: aspectual goal_analysis: first_order: "Execute meta-loop-orchestrator workflow" second_order: "Ensure quality and consistency" third_order: "Enable systematic orchestration processes"

/----------------------------------------------------------------------------/ /* S0 META-IDENTITY / /----------------------------------------------------------------------------*/

[define|neutral] SKILL := { name: "meta-loop-orchestrator", category: "orchestration", version: "1.0.0", 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: ["meta-loop-orchestrator", "orchestration", "workflow"], context: "user needs meta-loop-orchestrator capability" } [ground:given] [conf:1.0] [state:confirmed]

/----------------------------------------------------------------------------/ /* S3 CORE CONTENT / /----------------------------------------------------------------------------*/

Meta Loop Orchestrator

Kanitsal Cerceve (Evidential Frame Activation)

Kaynak dogrulama modu etkin.

Orchestrates the recursive self-improvement pipeline by coordinating foundry skills with Ralph Wiggum persistence loops. This skill enables bounded self-improvement where skills, agents, and prompts can improve themselves while being gated by frozen eval harness validation.

SKILL-SPECIFIC GUIDANCE

When to Use This Skill

  • Recursive improvement of foundry skills (agent-creator, skill-forge, prompt-forge)
  • Self-improvement cycles on the plugin's own components
  • Coordinating multiple foundry skills in a pipeline
  • Running auditor validation on foundry outputs
  • Executing eval harness gated improvement cycles

When NOT to Use This Skill

  • One-time skill/agent creation (use individual foundry skills directly)
  • Tasks not involving self-improvement of plugin components
  • Non-foundry skills (use cascade-orchestrator instead)
  • Quick fixes without full validation cycle

Success Criteria

  • [assert|neutral] All nested Ralph loops complete within max iterations [ground:acceptance-criteria] [conf:0.90] [state:provisional]
  • [assert|neutral] All 4 auditors pass validation [ground:acceptance-criteria] [conf:0.90] [state:provisional]
  • [assert|neutral] Eval harness shows improvement >= 0% (no regression) [ground:acceptance-criteria] [conf:0.90] [state:provisional]
  • [assert|neutral] Changes committed and monitoring initiated [ground:acceptance-criteria] [conf:0.90] [state:provisional]

Edge Cases

  • If nested Ralph loop hits max iterations: Escalate to human
  • If auditor fails repeatedly: Route back to foundry skill
  • If eval harness regression detected: REJECT and rollback

Critical Guardrails

NEVER:

  • Modify eval harness code (FROZEN)
  • Skip auditor validation
  • Commit without eval harness pass
  • Disable monitoring phase
  • Bypass human gates for large changes (>500 lines)

ALWAYS:

  • Run all 4 auditors in parallel
  • Store all intermediate states in memory-mcp
  • Maintain rollback capability
  • Log all iterations for debugging

Core Architecture

META-LOOP ORCHESTRATION FLOW
============================

INPUT: Task + Target + Foundry Skill
                |
                v
        +---------------+
        |   PREPARE     |
        |   - Parse     |
        |   - Load exp  |
        |   - Select    |
        +---------------+
                |
                v
    +=======================+
    |   EXECUTE (Ralph #1)  |
    |   Foundry skill runs  |
    |   until proposal ready|
    +=======================+
                |
                v
    +=======================+
    |  IMPLEMENT (Ralph #2) |
    |   Apply changes to    |
    |   target file(s)      |
    +=======================+
                |
                v
    +-------+-------+-------+-------+
    |       |       |       |       |
    v       v       v       v       v
  [R#3]   [R#4]   [R#5]   [R#6]   <- Parallel Ralph Loops
  Prompt  Skill   Expert  Output
  Audit   Audit   Audit   Audit
    |       |       |       |
    +-------+-------+-------+
                |
                v
    +=======================+
    |    EVAL (Ralph #7)    |
    |    Run eval harness   |
    |    Fix until pass     |
    +=======================+
                |
                v
        +---------------+
        |    COMPARE    |
        |   baseline vs |
        |   candidate   |
        +---------------+
                |
        +-------+-------+
        |               |
        v               v
     ACCEPT          REJECT
        |               |
        v               v
     COMMIT        LOG FAILURE
        |           (retry)
        v
    +=======================+
    |  MONITOR (Ralph #8)   |
    |    7-day watch        |
    +=======================+
        |
        v
     COMPLETE

Phase Definitions

Phase 1: PREPARE

yaml
prepare:
  actions:
    - Parse task and target from input
    - Detect domain from target

/*----------------------------------------------------------------------------*/
/* 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/meta-loop-orchestrator/{project}/{timestamp}",
  store: ["executions", "decisions", "patterns"],
  retrieve: ["similar_tasks", "proven_patterns"]
} [ground:system-policy] [conf:1.0] [state:confirmed]

[define|neutral] MEMORY_TAGGING := {
  WHO: "meta-loop-orchestrator-{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] <promise>META_LOOP_ORCHESTRATOR_VERILINGUA_VERIX_COMPLIANT</promise> [ground:self-validation] [conf:0.99] [state:confirmed]

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