Agent skill

bootstrap-loop

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npx add-skill https://github.com/DNYoussef/context-cascade/tree/main/skills/tooling/bootstrap-loop

SKILL.md

/============================================================================/ /* BOOTSTRAP-LOOP SKILL :: VERILINGUA x VERIX EDITION / /============================================================================*/

name: bootstrap-loop version: 1.0.0 description: | [assert|neutral] Orchestrates the recursive self-improvement cycle where Prompt Forge improves Skill Forge, Skill Forge improves Prompt Forge, and both audit/improve everything else. All changes gated by frozen eval h [ground:given] [conf:0.95] [state:confirmed] category: foundry tags:

  • recursive
  • self-improvement
  • dogfooding
  • orchestration author: system cognitive_frame: primary: evidential goal_analysis: first_order: "Execute bootstrap-loop workflow" second_order: "Ensure quality and consistency" third_order: "Enable systematic foundry processes"

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

[define|neutral] SKILL := { name: "bootstrap-loop", category: "foundry", version: "1.0.0", layer: L1 } [ground:given] [conf:1.0] [state:confirmed]

/----------------------------------------------------------------------------/ /* S1 COGNITIVE FRAME / /----------------------------------------------------------------------------*/

[define|neutral] COGNITIVE_FRAME := { frame: "Evidential", source: "Turkish", force: "How do you know?" } [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: ["bootstrap-loop", "foundry", "workflow"], context: "user needs bootstrap-loop capability" } [ground:given] [conf:1.0] [state:confirmed]

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

Bootstrap Loop (Recursive Self-Improvement Orchestrator)

Kanitsal Cerceve (Evidential Frame Activation)

Kaynak dogrulama modu etkin.

Purpose

Orchestrate the recursive improvement cycle:

+------------------+         +------------------+
|   PROMPT FORGE   |-------->|   SKILL FORGE    |
| (Meta-Prompt)    |<--------|   (Meta-Skill)   |
+------------------+         +------------------+
         |                            |
         |   Improved tools audit     |
         |   and improve everything   |
         v                            v
+--------------------------------------------------+
|              AUDITOR AGENTS                       |
|  [Prompt] [Skill] [Expertise] [Output]           |
+--------------------------------------------------+
         |                            |
         |   All changes gated by     |
         v                            v
+--------------------------------------------------+
|              EVAL HARNESS (FROZEN)               |
|  Benchmarks | Regression Tests | Human Gates     |
+--------------------------------------------------+

CRITICAL: The eval harness does NOT self-improve. It is the anchor that prevents Goodhart's Law.

When to Use

  • Running a recursive improvement cycle
  • Improving meta-tools (Prompt Forge, Skill Forge)
  • Auditing and improving system-wide prompts/skills
  • Measuring improvement over time

MCP Requirements

memory-mcp (Required)

Purpose: Store proposals, test results, version history, metrics

Activation:

bash
claude mcp add memory-mcp npx @modelcontextprotocol/server-memory

Core Operations

Operation 1: Run Single Improvement Cycle

Execute one full cycle of recursive improvement.

yaml
cycle:
  id: "cycle-{timestamp}"
  target: "prompt-forge|skill-forge|all"

  phases:
    1_analyze:
      action: "Prompt Forge analyzes target for weaknesses"
      output: "Analysis with improvement opportunities"

    2_propose:
      action: "Prompt Forge generates improvement proposals"
      output: "Concrete proposals with diffs"

    3_apply:
      action: "Skill Forge applies proposals (builds new version)"
      output: "New version of target"

    4_evaluate:
      action: "Eval Harness tests new version"
      output: "Benchmark + regression results"

    5_decide:
      action: "Compare results, decide ACCEPT or REJECT"
      output: "Decision with reasoning"

    6_commit_or_rollback:
      action: "If ACCEPT: commit + archive. If REJECT: rollback"
      output: "Final state + audit log"

Operation 2: Improve Prompt Forge

Use Skill Forge to improve Prompt Forge.

yaml
improve_prompt_forge:
  process:
    - step: "Analyze Prompt Forge with prompt-auditor"
      agent: "prompt-auditor"
      output: "Audit report with issues"

    - step: "Generate improvement proposals"
      agent: "prompt-forge" (self-analysis)
      output: "Proposals for self-improvement"

    - step: "Apply improvements with Skill Forge"
      agent: "skill-forge"
      output: "prompt-forge-v{N+1}"

    - step: "Test against eval harness"
      eval: "prompt-generation-benchmark-v1"
      regression: "prompt-forge-regression-v1"

    - step: "If improved: commit. If regressed: reject"

  safeguards:
    - "Previous version archived before changes"
    - "Requires eval harness pass"
    - "Rollback available for 30 days"
    - "Auditor agents must agree on improvement"

  forbidden_changes:
    - "Removing safeguards"
    - "Bypassing eval harness"
    - "Modifying frozen benchmarks"

Operation 3: Improve Skill Forge

Use Prompt Forge to improve Skill Forge.

yaml
improve_skill_forge:
  process:
    - step: "Analyze Skill Forge with skill-auditor"
      agent: "skill-auditor"
      output: "Audit report with issues"

    - step: "Generate improvement proposals with Prompt Forge"
      agent: "prompt-forge"
      output: "Proposals with rationale"

    - step: "Apply improvements (Skill Forge rebuilds 

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

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

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