navidocs/INFRAFABRIC_COMPREHENSIVE_EVALUATION_PROMPT.md

InfraFabric Comprehensive Evaluation Request

Context

I'm the developer of InfraFabric, a research and development project exploring AI agent coordination, epistemic governance, and civilizational resilience frameworks. The codebase is hosted at:

Repository: https://github.com/dannystocker/infrafabric

This is a WSL CLI session. I need a thorough, multi-phase evaluation of the entire codebase to understand its current state, utility, market potential, and technical debt.

---

Evaluation Objectives

Phase 1: Repository Analysis & Segmentation Strategy

Your first task is to:

1. Survey the repository structure on GitHub (branches, directories, file count)
2. Propose a segmentation strategy for comprehensive review across multiple context windows
3. Recommend starting point (suggested: /papers/ directory for conceptual foundation)

Phase 2: Content Evaluation (Multi-Session)

For each segment, evaluate:

A. Conceptual Quality

• Substance: Is the research grounded in verifiable claims, or speculative?
• Novelty: What's genuinely new vs. repackaged existing concepts?
• Rigor: Are arguments logically sound? Are citations traceable?
• Coherence: Do ideas connect across documents, or is there conceptual drift?

B. Technical Implementation

• Code Quality: Review actual implementations (if any) for:
  • Architecture soundness
  • Security practices
  • Performance considerations
  • Testing coverage
• IF. Components:* Identify all IF.* components referenced:
  • Implemented: Which components have working code?
  • Designed: Which have specifications but no implementation?
  • Vaporware: Which are mentioned but lack both design and code?
• Dependencies: External libraries, APIs, infrastructure requirements

B.1. Citation & Documentation Verification (CRITICAL)

This is a MANDATORY evaluation dimension. Research integrity depends on traceable claims.

Papers Directory (/papers/) Audit:

• Citation Traceability:
  • Every factual claim must have a citation (DOI, URL, or internal file reference)
  • Check 100% of citations if <20 papers, or random sample of 25% if >20 papers
  • Verify at least 10 external URLs are not 404
  • Flag any "common knowledge" claims that actually need citations
• Citation Currency:
  • Papers from last 3 years = ✅ Current
  • Papers 3-10 years old = 🟡 Acceptable (note if newer research exists)
  • Papers >10 years old = 🔴 Flag for review (unless foundational work like Turing, Shannon, etc.)
• Citation Quality:
  • Prefer peer-reviewed journals/conferences over blog posts
  • Prefer DOIs over raw URLs (DOIs are permanent)
  • Check if citations actually support the claims made
  • Flag "citation needed" instances

README.md Audit:

• Accuracy: Does README match current codebase?
  • Claims vs. reality (e.g., "production-ready" when it's a prototype)
  • Feature lists vs. actual implementations
  • Architecture descriptions vs. actual code structure
• Currency: Are examples/screenshots up-to-date?
  • Check at least 3 code examples actually run
  • Verify screenshots match current UI (if applicable)
• Link Verification:
  • Check ALL links in README (100%)
  • Flag 404s, redirects, or stale content
  • Check if linked repos/resources still exist
• Installation Instructions:
  • Do install steps work on a fresh environment?
  • Are dependency versions specified and current?
  • Are there OS-specific issues not documented?

C. Utility & Market Fit

• Practical Value: What problems does this actually solve?
• Target Audience: Who would benefit from this?
  • Academic researchers?
  • Enterprise customers?
  • Open-source communities?
  • Government/policy makers?
• Monetization Potential: Is there a viable business model?
• Competitive Landscape: How does this compare to existing solutions?

D. Style & Presentation

• Documentation Quality: Clarity, completeness, accessibility
• Narrative Coherence: Does the project tell a compelling story?
• Jargon Density: Is terminology explained or assumed?
• Visual Aids: Diagrams, schemas, examples

---

Deliverables

1. Comprehensive Evaluation Report

Structured as:

# InfraFabric Evaluation Report

## Executive Summary (1 page)
- High-level assessment
- Key strengths and weaknesses
- Recommended next steps

## Part 1: Conceptual Foundation (/papers/)
- Research quality analysis
- Theoretical contributions
- Evidence base assessment

## Part 2: Technical Architecture
- IF.* component inventory (implemented vs. designed vs. missing)
- Code quality metrics
- Security & performance review

## Part 3: Market & Utility Analysis
- Target buyer personas (ranked by fit)
- Pricing/licensing recommendations
- Competitive positioning

## Part 4: Gap Analysis
- Missing implementations
- Documentation gaps
- Technical debt inventory

## Part 5: Style & Presentation
- Documentation quality
- Narrative effectiveness
- Accessibility improvements needed

2. Debug Session Prompt (Separate Deliverable)

Create a standalone prompt for a future debugging session that includes:

# InfraFabric Debug & Implementation Session

## Context Transfer
[Brief summary of evaluation findings]

## IF.* Component Status
### ✅ Fully Implemented
- IF.guard: [description, file paths, test coverage]
- IF.citate: [description, file paths, test coverage]
[...]

### 🟡 Partially Implemented / Needs Work
- IF.sam: [what exists, what's missing, blockers]
[...]

### ❌ Not Yet Built (Priority Order)
1. IF.optimize: [why needed, spec location, dependencies]
2. [...]

## Foundational Gaps
- Missing core infrastructure (authentication, storage, APIs)
- Broken dependency chains
- Security vulnerabilities
- Performance bottlenecks

## Debug Priorities (Ranked)
1. **P0 (Blockers):** [Critical issues preventing basic functionality]
2. **P1 (High):** [Important features with missing implementations]
3. **P2 (Medium):** [Polish and optimization opportunities]

## Recommended Debug Workflow
[Step-by-step guide for the debug session based on evaluation findings]

---

Execution Strategy

Suggested Approach for Multi-Context Analysis

1. Session 1: Survey & Strategy (This session)

   • Clone repository
   • Analyze directory structure
   • Propose segmentation plan
   • Read /papers/ directory (establish conceptual foundation)

2. Session 2-N: Deep Dives (Subsequent sessions)

   • Each session focuses on 1-2 major components or directories
   • Session resume protocol: Brief summary of previous findings + new segment focus
   • Cumulative findings tracked in evaluation report

3. Final Session: Synthesis & Debug Prompt Generation

   • Consolidate all findings
   • Generate comprehensive evaluation report
   • Create actionable debug session prompt

Context Window Management

To prevent information loss across sessions:

• Maintain a running EVALUATION_PROGRESS.md file with:

  • Segments reviewed so far
  • Key findings per segment (bullet points)
  • Updated IF.* component inventory
  • Running list of gaps/issues

• Each session starts with:

  Read EVALUATION_PROGRESS.md (context refresh)
  → Review new segment
  → Update EVALUATION_PROGRESS.md
  → Update main evaluation report
  

---

Specific Questions to Answer

Strategic Questions

1. Is this a product, a research project, or a marketing deck?
2. What's the fastest path to demonstrable value?
3. Who are the top 3 buyer personas, and would they actually pay?
4. Is the codebase production-ready, prototype-stage, or concept-only?

Technical Questions

1. What's the ratio of documentation to working code?
2. Are there any complete, end-to-end features?
3. What external dependencies exist (APIs, infrastructure, data sources)?
4. Is there a coherent architecture, or is this a collection of experiments?

Market Questions

1. What's the total addressable market (TAM)?
2. What's the go-to-market strategy implied by the documentation?
3. Are there existing competitors solving the same problems?
4. What's unique and defensible about InfraFabric?

---

Output Format (MANDATORY)

All evaluators (Codex, Gemini, Claude) MUST use this exact YAML schema:

This standardized format enables:

• Easy diffing between evaluator responses (Codex vs Gemini vs Claude)
• Automated merging of consensus findings
• Programmatic filtering (e.g., "show all P0 blockers from all evaluators")
• Metrics aggregation (e.g., "average overall_score across evaluators")

YAML Schema:

evaluator: "Codex" # or "Gemini" or "Claude"
evaluation_date: "2025-11-14"
repository: "https://github.com/dannystocker/infrafabric"
commit_hash: "<git commit sha>"

executive_summary:
  overall_score: 6.5  # 0-10 scale
  one_liner: "Research-heavy AI governance framework with limited production code"
  key_strength: "Novel epistemic coordination concepts"
  key_weakness: "90% documentation, 10% working implementations"
  buyer_fit: "Academic/research institutions (7/10), Enterprise (3/10)"
  recommended_action: "Focus on 3 core IF.* components, ship MVP"

conceptual_quality:
  substance_score: 7  # 0-10
  novelty_score: 8
  rigor_score: 6
  coherence_score: 7
  findings:
    - text: "Guardian Council framework shows originality"
      file: "papers/epistemic-governance.md"
      evidence: "Cites 15+ academic sources"
      severity: "info"
    - text: "Civilizational collapse claims lack quantitative models"
      file: "papers/collapse-patterns.md"
      evidence: "Lines 45-120 - no mathematical formalization"
      severity: "medium"

technical_implementation:
  code_quality_score: 4  # 0-10
  test_coverage: 15  # percentage
  documentation_ratio: 0.9  # docs / (docs + code)

  if_components:
    implemented:
      - name: "IF.guard"
        files: ["tools/guard.py", "schemas/guard-v1.json"]
        completeness: 75  # percentage
        test_coverage: 40
        issues: ["Missing async support", "No rate limiting"]
      - name: "IF.citate"
        files: ["tools/citation_validate.py"]
        completeness: 60
        test_coverage: 30
        issues: ["Validation incomplete", "No batch processing"]

    partial:
      - name: "IF.sam"
        design_file: "docs/IF-sam-specification.md"
        implementation_file: null
        blockers: ["Requires OpenAI API integration", "No test framework"]
        priority: "P1"
      - name: "IF.optimize"
        design_file: "agents.md:L234-289"
        implementation_file: null
        blockers: ["Needs token tracking infrastructure"]
        priority: "P2"

    vaporware:
      - name: "IF.swarm"
        mentions: ["agents.md:L45", "papers/coordination.md:L89"]
        spec_exists: false
        priority: "P3"

  dependencies:
    - name: "Meilisearch"
      used_by: ["IF.search"]
      status: "external"
      risk: "low"
    - name: "OpenRouter API"
      used_by: ["IF.sam", "IF.council"]
      status: "external"
      risk: "medium - API key exposed in docs"

  security_issues:
    - severity: "critical"
      issue: "API key in CLAUDE.md (sk-or-v1-...)"
      file: "/home/setup/.claude/CLAUDE.md:L12"
      fix: "Rotate key, use environment variables"
    - severity: "high"
      issue: "No input validation in guard.py"
      file: "tools/guard.py:L89-120"
      fix: "Add schema validation before processing"

  citation_verification:
    papers_reviewed: 12  # Total papers in /papers/ directory
    total_citations: 87
    citations_verified: 67  # How many you actually checked
    citation_quality_score: 7  # 0-10
    issues:
      - severity: "high"
        issue: "Claim about AGI timelines lacks citation"
        file: "papers/epistemic-governance.md:L234"
        fix: "Add citation or mark as speculation"
      - severity: "medium"
        issue: "DOI link returns 404"
        file: "papers/collapse-patterns.md:L89"
        citation: "https://doi.org/10.1234/broken"
        fix: "Find working link or cite archived version"
      - severity: "low"
        issue: "Citation from 2005 (20 years old)"
        file: "papers/coordination.md:L45"
        citation: "Smith et al. 2005"
        fix: "Find more recent citation or note 'foundational work'"

    readme_audit:
      accuracy_score: 6  # 0-10, does README match reality?
      links_checked: 15
      broken_links: 3
      broken_link_examples:
        - url: "https://example.com/deprecated"
          location: "README.md:L45"
      install_instructions_current: true
      code_examples_tested: 3
      code_examples_working: 2
      screenshots_current: false
      issues:
        - severity: "medium"
          issue: "README claims 'production-ready' but code is prototype"
          file: "README.md:L12"
          fix: "Change to 'research prototype' or 'MVP in development'"
        - severity: "low"
          issue: "Screenshot shows old UI from 2023"
          file: "README.md:L67"
          fix: "Update screenshot or remove"
        - severity: "medium"
          issue: "Installation example uses outdated npm commands"
          file: "README.md:L89"
          fix: "Update to current npm syntax"

market_analysis:
  tam_estimate: "$50M-$200M (AI governance/observability niche)"
  buyer_personas:
    - rank: 1
      name: "Academic AI Safety Researchers"
      fit_score: 8  # 0-10
      willingness_to_pay: 3  # 0-10
      rationale: "Novel frameworks, citations, but expect open-source"
    - rank: 2
      name: "Enterprise AI Governance Teams"
      fit_score: 6
      willingness_to_pay: 7
      rationale: "Useful concepts but needs production-ready implementation"
    - rank: 3
      name: "Open-Source Community"
      fit_score: 7
      willingness_to_pay: 1
      rationale: "Interesting project, low monetization potential"

  competitors:
    - name: "LangSmith (LangChain)"
      overlap: "Agent tracing, observability"
      differentiation: "InfraFabric adds epistemic governance layer"
    - name: "Weights & Biases"
      overlap: "ML experiment tracking"
      differentiation: "InfraFabric focuses on agent coordination vs ML training"

  monetization_paths:
    - strategy: "Open-core SaaS"
      viability: 7  # 0-10
      timeline: "12-18 months"
    - strategy: "Consulting + Custom Implementations"
      viability: 8
      timeline: "Immediate"

gaps_and_issues:
  p0_blockers:
    - issue: "No authentication system"
      impact: "Cannot deploy any multi-user features"
      effort: "3-5 days"
      files: []
    - issue: "API keys exposed in documentation"
      impact: "Security vulnerability"
      effort: "1 hour"
      files: ["/home/setup/.claude/CLAUDE.md"]

  p1_high_priority:
    - issue: "IF.sam has design but no implementation"
      impact: "Core feature missing"
      effort: "1-2 weeks"
      files: ["agents.md"]
    - issue: "No end-to-end integration tests"
      impact: "Cannot verify system behavior"
      effort: "1 week"
      files: []

  p2_medium_priority:
    - issue: "Documentation scattered across 50+ markdown files"
      impact: "Hard to onboard new developers"
      effort: "2-3 days (consolidation)"
      files: ["papers/*", "docs/*"]

style_assessment:
  documentation_quality: 7  # 0-10
  narrative_coherence: 6
  jargon_density: 8  # higher = more jargon
  accessibility: 5
  recommendations:
    - "Create single-page 'What is InfraFabric' overview"
    - "Add 5-minute video demo of working features"
    - "Glossary for IF.* components (many files use without definition)"
    - "Reduce academic tone in marketing materials"

metrics:
  total_files: 127
  total_lines_code: 2847
  total_lines_docs: 25691
  code_to_docs_ratio: 0.11
  languages:
    Python: 1823
    JavaScript: 891
    Markdown: 25691
    YAML: 133
  test_files: 8
  test_lines: 342

next_steps:
  immediate:
    - action: "Rotate exposed API keys"
      effort: "15 minutes"
    - action: "Create EVALUATION_PROGRESS.md for session tracking"
      effort: "30 minutes"
  short_term:
    - action: "Implement IF.sam (75% designed, 0% built)"
      effort: "1-2 weeks"
    - action: "Add integration tests for IF.guard + IF.citate"
      effort: "3-5 days"
  long_term:
    - action: "Consolidate documentation into coherent guide"
      effort: "1-2 weeks"
    - action: "Build authentication layer for multi-user deployment"
      effort: "2-3 weeks"

attachments:
  - name: "IF_COMPONENT_INVENTORY.yaml"
    description: "Complete IF.* component status (all 47 components)"
  - name: "DEBUG_SESSION_PROMPT.md"
    description: "Prioritized debug workflow based on findings"

---

Format Preferences

• Be brutally honest: I need truth, not validation
• Use exact YAML schema above: Makes diff/merge trivial across evaluators
• Quantify everything: 0-10 scores, percentages, counts, effort estimates
• Cite specific files/lines: Use file:line format for traceability
• Prioritize actionability: Every critique includes fix and effort estimate
• Flag vaporware clearly: Use implemented/partial/vaporware categories strictly

---

Starting Point (Recommended)

Begin with: /papers/ directory

Rationale: This likely contains the conceptual foundation. Understanding the theory first will inform evaluation of implementations.

Initial questions for /papers/ review:

1. What claims are being made?
2. What evidence supports those claims?
3. Are these papers intended for publication, internal use, or marketing?
4. Do they reference implemented features, or are they speculative?

---

Success Criteria

This evaluation is successful if it produces:

✅ Clear understanding of what InfraFabric actually is (vs. what it aspires to be) ✅ Honest assessment of market potential and buyer fit ✅ Actionable debug prompt that guides technical cleanup and implementation ✅ IF. component inventory* distinguishing built vs. designed vs. vaporware ✅ Prioritized roadmap for turning concepts into shippable products

---

Ready to begin. Please start with the repository survey and /papers/ directory analysis.