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name: qmnf-innovations description: Rigorous gap analysis and innovation audit for QMNF/NINE65/MYSTIC or related exact-arithmetic, FHE, and quantum-substrate systems. Use when asked to verify that novel implementations exist and are correct, map innovations to code/tests, design validation plans, or identify expansion opportunities in this ecosystem.

QMNF Innovations

Overview

Perform evidence-based audits that map claimed innovations to implementations, validate mathematical and engineering rigor, and surface gaps or expansion opportunities across QMNF/NINE65/MYSTIC-style systems.

Core Capabilities

• Build an innovation inventory and coverage matrix.
• Verify implementation evidence (code, tests, benchmarks) for each innovation.
• Produce rigorous gap analyses across architecture, mathematics, implementation, validation, security, and operations.
• Propose expansion or inclusion opportunities aligned with system invariants.

Workflow

1. Scope and constraints

• Confirm target repo(s), output format, and whether to write report files.
• Read AGENTS.md in the repo root if present and follow local rules.
• Identify project summaries, design docs, and prior gap analyses.

2. Build the innovation inventory

• Load references/innovation-catalog.md for canonical innovations.
• Extract additional innovations from repo docs and code comments.
• Maintain a working list grouped by domain (arithmetic, FHE, entropy, quantum, infrastructure).

3. Map innovations to evidence

• Locate implementation paths with rg for innovation names and core primitives.
• Record evidence: file paths, functions, tests, benchmarks, and outputs.
• Mark status as Implemented, Partial, or Missing with clear justification.

4. Evaluate correctness and risk

• Check boundary conditions, error handling, conditioning, and invariants.
• Identify TODOs, stubs, or placeholder logic; call out unverified claims.
• Assess performance claims only when evidence exists; otherwise flag as unvalidated.

5. Validate with a testing plan

• Enumerate existing tests and datasets; note coverage holes.
• Propose minimal high-signal tests for each critical innovation.
• Distinguish synthetic validation from real-world scenarios.

6. Identify expansion and inclusion opportunities

• Propose additions that extend the architecture without violating invariants.
• Highlight missing integration seams or adjacent research directions.
• Separate speculative research from actionable engineering.

7. Produce deliverables

• Write the default deliverables for a rigorous audit:
  • gap_analysis.md
  • mathematical_gap_analysis.md
  • critical_gaps_summary.md
• Use templates in references/report-templates.md unless the user requests another format.
• Include an Innovation Coverage Matrix (summary + detailed appendix).

Evidence Standards

• Cite concrete artifacts: file paths, functions, tests, and benchmark outputs.
• Avoid assumptions; label unknowns explicitly.
• Prefer reproducible steps and minimal test plans over broad speculation.

Output Rules

• Keep reports concise but rigorous; prioritize high-severity gaps first.
• Include a prioritized action list with clear success metrics.
• Note any access limitations (missing repos, no test data, no build).

Resources

• references/innovation-catalog.md - canonical innovation list and deep dives.
• references/report-templates.md - report templates and matrix format.