Audit Wasserstein Order Consistency

VerifiedSafe

Scans manuscript drafts and codebase for W₁ vs W₂ inconsistencies to resolve Phase 0 deliverable. Produces a structured reconciliation report without automatic fixes.

Sby Skills Guide Bot
Data & AIIntermediate
107/29/2026
Claude Code
#wasserstein#audit#consistency#manuscript#code

Recommended for

Our review

Scans manuscript drafts and code for inconsistencies between W₁ and W₂ usage, and produces a structured reconciliation report.

Strengths

  • Automatically detects ambiguous or incorrect W₁/W₂ usage across text and code.
  • References a centralized notation standard (notation.md) for consistency.
  • Outputs a structured report with suggested fixes.

Limitations

  • Requires the existence of notation.md with the correct section.
  • Does not auto-fix issues; only reports them.
  • Only checks predefined patterns; may miss some edge cases.
When to use it

When preparing a manuscript or codebase that uses Wasserstein metrics, to ensure compliance with W₂ convention.

When not to use it

When notation is already consistent or the project does not use Wasserstein metrics.

Security analysis

Safe
Quality score85/100

The skill only reads files and generates a report; it does not execute any system commands, make network requests, or alter files without user confirmation. There is no risk of data exfiltration or destructive actions.

No concerns found

Examples

Scan both papers and code
/wasserstein-audit all
Scan only manuscript files
/wasserstein-audit papers

/wasserstein-audit — Audit Wasserstein Order Consistency

Scan all manuscript drafts and codebase for W₁ vs W₂ inconsistencies. Resolves the blocking Phase 0 deliverable: the legacy P01 manuscript uses W₁ in several places while project convention mandates W₂ as the primary metric.

Usage

/wasserstein-audit
/wasserstein-audit [papers|code|all]

Example: /wasserstein-audit all


What this does

  1. Reads papers/shared/notation.md (canonical notation standard, Wasserstein Audit section)
  2. Scans manuscript .md files under papers/ for W₁, unsubscripted W, ambiguous W_p
  3. Scans Python files under all domain packages for Wasserstein calls without explicit p=2
  4. Cross-references findings against what notation.md already has "verified"
  5. Produces a structured reconciliation report — does not fix anything without confirmation

Manuscript patterns that trigger a flag

| Pattern | Issue | |---|---| | W_1 / $W_1$ / W_{1} | W₁ usage — needs justification or must change to W₂ | | $W$ (unsubscripted) | Always flag — violates notation standard | | bottleneck without alongside Wasserstein | Sole metric violation | | wasserstein without explicit order nearby | Ambiguous |

Code patterns that trigger a flag

| Pattern | Issue | |---|---| | wasserstein_distance(a, b) with no p= arg | Default may not be W₂ in all library versions | | p=1 or order=1 near Wasserstein call | Explicit W₁ usage | | bottleneck_distance(...) | Must not be used as sole metric | | gudhi.wasserstein.wasserstein_distance without order=2 | gudhi default not guaranteed |


Report format

## Wasserstein Audit Report — YYYY-MM-DD

### Manuscript Findings
| File | Line | Found | Issue | Suggested Fix |

### Code Findings
| File | Line | Found | Issue | Suggested Fix |

### Status
- Blocking Phase 0: YES / NO
- Total issues: N (manuscript: N₁, code: N₂)

### Recommended Actions

Library defaults (reference)

  • persim.wasserstein_distance — p=2 by default ✓
  • gudhi.wasserstein.wasserstein_distance — requires explicit order= arg
  • giotto-tda Wasserstein vectorisation — p=2 by default ✓
  • W₁ in theory proofs is acceptable in Methods sections if clearly labelled and distinguished from the computational metric used
Related skills